Machines

16 pages, 4644 KiB

Open AccessEditor’s ChoiceReview

An Overview of Electric Machine Trends in Modern Electric Vehicles

by Emmanuel Agamloh, Annette von Jouanne and Alexandre Yokochi

Machines 2020, 8(2), 20; https://doi.org/10.3390/machines8020020 - 17 Apr 2020

Cited by 147 | Viewed by 36033

Electric machines are critical components of the drivetrains of electric vehicles. Over the past few years the majority of traction drive systems have converged toward containing some form of a permanent magnet machine. There is increasing tendency toward the improvement of power density [...] Read more.

Electric machines are critical components of the drivetrains of electric vehicles. Over the past few years the majority of traction drive systems have converged toward containing some form of a permanent magnet machine. There is increasing tendency toward the improvement of power density and efficiency of traction machines, thereby giving rise to innovative designs and improvements of basic machine topologies and the emergence of new classes of machines. This paper provides an overview of present trends toward high specific power density machines for traction drive systems. The focus will be on current technology and the trends that are likely to be pursued in the near future to achieve the high specific power goals set for the industry. The paper discusses machines that are applied in both hybrid and battery electric drivetrains without distinction and does not discuss the associated power electronic inverters. Future electric machine trends that are likely to occur are also projected. Full article

► Show Figures

Figure 1

40 pages, 2691 KiB

Open AccessEditor’s ChoiceReview

Engineering Applications of Artificial Intelligence in Mechanical Design and Optimization

by Jozef Jenis, Jozef Ondriga, Slavomir Hrcek, Frantisek Brumercik, Matus Cuchor and Erik Sadovsky

Machines 2023, 11(6), 577; https://doi.org/10.3390/machines11060577 - 23 May 2023

Cited by 28 | Viewed by 33723

Abstract

This study offers a complete analysis of the use of deep learning or machine learning, as well as precise recommendations on how these methods could be used in the creation of machine components and nodes. The examples in this thesis are intended to [...] Read more.

This study offers a complete analysis of the use of deep learning or machine learning, as well as precise recommendations on how these methods could be used in the creation of machine components and nodes. The examples in this thesis are intended to identify areas in mechanical design and optimization where this technique could be widely applied in the future, benefiting society and advancing the current state of modern mechanical engineering. The review begins with a discussion on the workings of artificial intelligence, machine learning, and deep learning. Different techniques, classifications, and even comparisons of each method are described in detail. The most common programming languages, frameworks, and software used in mechanical engineering for this problem are gradually introduced. Input data formats and the most common datasets that are suitable for the field of machine learning in mechanical design and optimization are also discussed. The second half of the review describes the current use of machine learning in several areas of mechanical design and optimization, using specific examples that have been investigated by researchers from around the world. Further research directions on the use of machine learning and neural networks in the fields of mechanical design and optimization are discussed. Full article

(This article belongs to the Section Machine Design and Theory)

► Show Figures

Figure 1

22 pages, 2176 KiB

Open AccessEditor’s ChoiceArticle

Machine Learning Applications on Agricultural Datasets for Smart Farm Enhancement

by Fabrizio Balducci, Donato Impedovo and Giuseppe Pirlo

Machines 2018, 6(3), 38; https://doi.org/10.3390/machines6030038 - 1 Sep 2018

Cited by 175 | Viewed by 23014

Abstract

This work aims to show how to manage heterogeneous information and data coming from real datasets that collect physical, biological, and sensory values. As productive companies—public or private, large or small—need increasing profitability with costs reduction, discovering appropriate ways to exploit data that [...] Read more.

This work aims to show how to manage heterogeneous information and data coming from real datasets that collect physical, biological, and sensory values. As productive companies—public or private, large or small—need increasing profitability with costs reduction, discovering appropriate ways to exploit data that are continuously recorded and made available can be the right choice to achieve these goals. The agricultural field is only apparently refractory to the digital technology and the “smart farm” model is increasingly widespread by exploiting the Internet of Things (IoT) paradigm applied to environmental and historical information through time-series. The focus of this study is the design and deployment of practical tasks, ranging from crop harvest forecasting to missing or wrong sensors data reconstruction, exploiting and comparing various machine learning techniques to suggest toward which direction to employ efforts and investments. The results show how there are ample margins for innovation while supporting requests and needs coming from companies that wish to employ a sustainable and optimized agriculture industrial business, investing not only in technology, but also in the knowledge and in skilled workforce required to take the best out of it. Full article

(This article belongs to the Special Issue Multi-Body System Dynamics: Monitoring, Simulation and Control)

► Show Figures

Figure 1

37 pages, 1941 KiB

Open AccessEditor’s ChoiceReview

Motion Planning for Mobile Manipulators—A Systematic Review

by Thushara Sandakalum and Marcelo H. Ang, Jr.

Machines 2022, 10(2), 97; https://doi.org/10.3390/machines10020097 - 27 Jan 2022

Cited by 84 | Viewed by 17604

Abstract

One of the fundamental fields of research is motion planning. Mobile manipulators present a unique set of challenges for the planning algorithms, as they are usually kinematically redundant and dynamically complex owing to the different dynamic behavior of the mobile base and the [...] Read more.

One of the fundamental fields of research is motion planning. Mobile manipulators present a unique set of challenges for the planning algorithms, as they are usually kinematically redundant and dynamically complex owing to the different dynamic behavior of the mobile base and the manipulator. The purpose of this article is to systematically review the different planning algorithms specifically used for mobile manipulator motion planning. Depending on how the two subsystems are treated during planning, sampling-based, optimization-based, search-based, and other planning algorithms are grouped into two broad categories. Then, planning algorithms are dissected and discussed based on common components. The problem of dealing with the kinematic redundancy in calculating the goal configuration is also analyzed. While planning separately for the mobile base and the manipulator provides convenience, the results are sub-optimal. Coordinating between the mobile base and manipulator while utilizing their unique capabilities provides better solution paths. Based on the analysis, challenges faced by the current planning algorithms and future research directions are presented. Full article

(This article belongs to the Special Issue Feature Papers to Celebrate the First Impact Factor of Machines)

► Show Figures

Figure 1

29 pages, 775 KiB

Open AccessEditor’s ChoiceReview

Autonomous Vehicle Decision-Making and Control in Complex and Unconventional Scenarios—A Review

by Faizan Sana, Nasser L. Azad and Kaamran Raahemifar

Machines 2023, 11(7), 676; https://doi.org/10.3390/machines11070676 - 23 Jun 2023

Cited by 17 | Viewed by 14870

Abstract

The development of autonomous vehicles (AVs) is becoming increasingly important as the need for reliable and safe transportation grows. However, in order to achieve level 5 autonomy, it is crucial that such AVs can navigate through complex and unconventional scenarios. It has been [...] Read more.

The development of autonomous vehicles (AVs) is becoming increasingly important as the need for reliable and safe transportation grows. However, in order to achieve level 5 autonomy, it is crucial that such AVs can navigate through complex and unconventional scenarios. It has been observed that currently deployed AVs, like human drivers, struggle the most in cases of adverse weather conditions, unsignalized intersections, crosswalks, roundabouts, and near-accident scenarios. This review paper provides a comprehensive overview of the various navigation methodologies used in handling these situations. The paper discusses both traditional planning methods such as graph-based approaches and emerging solutions including machine-learning based approaches and other advanced decision-making and control techniques. The benefits and drawbacks of previous studies in this area are discussed in detail and it is identified that the biggest shortcomings and challenges are benchmarking, ensuring interpretability, incorporating safety as well as road user interactions, and unrealistic simplifications such as the availability of accurate and perfect perception information. Some suggestions to tackle these challenges are also presented. Full article

(This article belongs to the Special Issue Artificial Intelligence for Automatic Control of Vehicles)

► Show Figures

Figure 1

28 pages, 3520 KiB

Open AccessEditor’s ChoiceReview

Bearing Current and Shaft Voltage in Electrical Machines: A Comprehensive Research Review

by Kotb B. Tawfiq, Mehmet Güleç and Peter Sergeant

Machines 2023, 11(5), 550; https://doi.org/10.3390/machines11050550 - 12 May 2023

Cited by 36 | Viewed by 14330

Abstract

The reliability assessment of electric machines plays a very critical role in today’s engineering world. The reliability assessment requires a good understanding of electric motors and their root causes. Electric machines mostly fail due to mechanical problems and bearing damage is the main [...] Read more.

The reliability assessment of electric machines plays a very critical role in today’s engineering world. The reliability assessment requires a good understanding of electric motors and their root causes. Electric machines mostly fail due to mechanical problems and bearing damage is the main source of this. The bearings can be damaged by mechanical, electrical, and thermal stresses. Among all stresses, the researcher should give special attention to the electrical one, which is bearing current and shaft voltage. This review paper introduces a comprehensive study of bearing current and shaft voltage for inverter-fed electric machines. This study aims to discuss several motor failure processes, as well as the sources and definitions of bearing current and shaft voltage. The different kinds of bearing currents are addressed and the parasitic capacitances, which are the key component to describe bearing current, are determined. Several measurement approaches of bearing current will be discussed. Furthermore, modeling of bearing current will be covered together with the machine’s parasitic capacitances. Moreover, the different bearing current mitigation techniques, as described in many papers, will be thoroughly addressed. The use of rewound multiphase machines for mitigation of bearing current will be proposed and compared to a three-phase machine. Finally, various pulse width modulation techniques of multiphase systems that reduce bearing current and shaft voltage will be investigated, and the findings described in the literature will be summarized for all techniques. Full article

(This article belongs to the Special Issue Advanced Power Electronic Technologies in Electric Drive Systems)

► Show Figures

Figure 1

19 pages, 3684 KiB

Open AccessEditor’s ChoiceArticle

Cybersecurity Risk Assessment in Smart City Infrastructures

by Maxim Kalinin, Vasiliy Krundyshev and Peter Zegzhda

Machines 2021, 9(4), 78; https://doi.org/10.3390/machines9040078 - 4 Apr 2021

Cited by 90 | Viewed by 14042

Abstract

The article is devoted to cybersecurity risk assessment of the dynamic device-to-device networks of a smart city. Analysis of the modern security threats at the IoT/IIoT, VANET, and WSN inter-device infrastructures demonstrates that the main concern is a set of network security threats [...] Read more.

The article is devoted to cybersecurity risk assessment of the dynamic device-to-device networks of a smart city. Analysis of the modern security threats at the IoT/IIoT, VANET, and WSN inter-device infrastructures demonstrates that the main concern is a set of network security threats targeted at the functional sustainability of smart urban infrastructure, the most common use case of smart networks. As a result of our study, systematization of the existing cybersecurity risk assessment methods has been provided. Expert-based risk assessment and active human participation cannot be provided for the huge, complex, and permanently changing digital environment of the smart city. The methods of scenario analysis and functional analysis are specific to industrial risk management and are hardly adaptable to solving cybersecurity tasks. The statistical risk evaluation methods force us to collect statistical data for the calculation of the security indicators for the self-organizing networks, and the accuracy of this method depends on the number of calculating iterations. In our work, we have proposed a new approach for cybersecurity risk management based on object typing, data mining, and quantitative risk assessment for the smart city infrastructure. The experimental study has shown us that the artificial neural network allows us to automatically, unambiguously, and reasonably assess the cyber risk for various object types in the dynamic digital infrastructures of the smart city. Full article

(This article belongs to the Special Issue Mechatronic System for Automatic Control)

► Show Figures

Figure 1

22 pages, 1243 KiB

Open AccessEditor’s ChoiceReview

A Review of Prognostic and Health Management (PHM) Methods and Limitations for Marine Diesel Engines: New Research Directions

by Hla Gharib and György Kovács

Machines 2023, 11(7), 695; https://doi.org/10.3390/machines11070695 - 1 Jul 2023

Cited by 26 | Viewed by 13786

Abstract

Prognostic and health management (PHM) methods focus on improving the performance and reliability of systems with a high degree of complexity and criticality. These systems include engines, turbines, and robotic systems. PHM methods involve managing technical processes, such as condition monitoring, fault diagnosis, [...] Read more.

Prognostic and health management (PHM) methods focus on improving the performance and reliability of systems with a high degree of complexity and criticality. These systems include engines, turbines, and robotic systems. PHM methods involve managing technical processes, such as condition monitoring, fault diagnosis, health prognosis, and maintenance decision-making. Various software and applications deal with the processes mentioned above independently. We can also observe different development levels, making connecting all of the machine’s technical processes in one health management system with the best possible output a challenging task. This study’s objective was to outline the scope of PHM methods in real-time conditions and propose new directions to develop a decision support tool for marine diesel engines. In this paper, we illustrate PHM processes and the state of the art in the marine industry for each technical process. Then, we review PHM methods and limitations for marine diesel engines. Finally, we analyze future research opportunities for the marine industry and their role in developing systems’ performance and reliability. The main added value of the research is that a research gap was found in this research field, which is that new advanced PHM methods have to be implemented for marine diesel engines. Our suggestions to improve marine diesel engines’ operation and maintenance include implementing advanced PHM methods and utilizing predictive analytics and machine learning. Full article

(This article belongs to the Special Issue Condition-Based Maintenance, Instrumentation and Data Analysis Methods Aiming Efficient Operation of Internal Combustion Engines)

► Show Figures

Figure 1

53 pages, 6453 KiB

Open AccessEditor’s ChoiceReview

Marine Systems and Equipment Prognostics and Health Management: A Systematic Review from Health Condition Monitoring to Maintenance Strategy

by Peng Zhang, Zeyu Gao, Lele Cao, Fangyang Dong, Yongjiu Zou, Kai Wang, Yuewen Zhang and Peiting Sun

Machines 2022, 10(2), 72; https://doi.org/10.3390/machines10020072 - 19 Jan 2022

Cited by 60 | Viewed by 13599

Abstract

Prognostics and health management (PHM) is an essential means to optimize resource allocation and improve the intelligent operation and maintenance (O&M) efficiency of marine systems and equipment (MSAE). PHM generally consists of four technical processes, namely health condition motoring (HCM), fault diagnosis (FD), [...] Read more.

Prognostics and health management (PHM) is an essential means to optimize resource allocation and improve the intelligent operation and maintenance (O&M) efficiency of marine systems and equipment (MSAE). PHM generally consists of four technical processes, namely health condition motoring (HCM), fault diagnosis (FD), health prognosis (HP), and maintenance decision (MD). In recent years, a large amount of research has been implemented in each process. However, there is not any systematic review that covers the technical framework comprehensively. This article presents a review of the framework of PHM in the marine field to fill the gap. First, the essential HCM methods, which are widely observed in the academic literature, are introduced systematically. Then, the commonly used FD approaches and their applications in MSAE are summarized, and the implementation process of intelligent methods is systematically introduced. After that, the technologies of HP have been reviewed, including the construction of health indicator (HI), health stage (HS) division, and popular remaining useful life (RUL) prediction approaches. Afterwards, the evolution of maintenance strategy in the maritime field is reviewed. Finally, the challenges of implementing PHM for intelligent ships are put forward. Full article

► Show Figures

Figure 1

16 pages, 1781 KiB

Open AccessEditor’s ChoiceReview

Review of Rotor Balancing Methods

by Liqing Li, Shuqian Cao, Jing Li, Rimin Nie and Lanlan Hou

Machines 2021, 9(5), 89; https://doi.org/10.3390/machines9050089 - 29 Apr 2021

Cited by 43 | Viewed by 13358

Abstract

This review is dedicated to balancing methods that are used to solve the rotor-balancing problem. To ensure a stable operation over an operating speed range, it is necessary to balance a rotor. The traditional methods, including the influence coefficient method (ICM) and the [...] Read more.

This review is dedicated to balancing methods that are used to solve the rotor-balancing problem. To ensure a stable operation over an operating speed range, it is necessary to balance a rotor. The traditional methods, including the influence coefficient method (ICM) and the modal balancing method (MBM) are introduced, and the research progress, operation steps, advantages and disadvantages of these methods are elaborated. The classification of new balancing methods is reviewed. Readers are expected to obtain an overview of the research progress of existing balancing methods and the directions for future studies. Full article

(This article belongs to the Section Turbomachinery)

► Show Figures

Figure 1

17 pages, 6208 KiB

Open AccessEditor’s ChoiceReview

Tracked Locomotion Systems for Ground Mobile Robots: A Review

by Luca Bruzzone, Shahab Edin Nodehi and Pietro Fanghella

Machines 2022, 10(8), 648; https://doi.org/10.3390/machines10080648 - 4 Aug 2022

Cited by 52 | Viewed by 12936

Abstract

The paper discusses the state-of-the-art of locomotion systems for ground mobile robots comprising tracks. Tracked locomotion, due to the large contact surface with the ground, is particularly suitable for tackling soft, yielding, and irregular terrains, but is characterized by lower speed and energy [...] Read more.

The paper discusses the state-of-the-art of locomotion systems for ground mobile robots comprising tracks. Tracked locomotion, due to the large contact surface with the ground, is particularly suitable for tackling soft, yielding, and irregular terrains, but is characterized by lower speed and energy efficiency than wheeled locomotion, and lower obstacle-climbing capability than legged locomotion. Therefore, in recent years academic and industrial researchers have designed a wide variety of hybrid solutions, combining tracks with legs and wheels. The paper proposes three possible parallel taxonomies, based on body architecture, track profile, and track type, to help designers select the most suitable architecture on the basis of the operative necessities. Moreover, modeling, simulation, and design methodologies for tracked ground mobile robots are recalled. Full article

(This article belongs to the Special Issue Feature Review Papers on Automation Systems)

► Show Figures

Figure 1

35 pages, 771 KiB

Open AccessEditor’s ChoiceReview

A Survey on Fault Diagnosis and Fault-Tolerant Control Methods for Unmanned Aerial Vehicles

by George K. Fourlas and George C. Karras

Machines 2021, 9(9), 197; https://doi.org/10.3390/machines9090197 - 13 Sep 2021

Cited by 117 | Viewed by 12807

Abstract

The continuous evolution of modern technology has led to the creation of increasingly complex and advanced systems. This has been also reflected in the technology of Unmanned Aerial Vehicles (UAVs), where the growing demand for more reliable performance necessitates the development of sophisticated [...] Read more.

The continuous evolution of modern technology has led to the creation of increasingly complex and advanced systems. This has been also reflected in the technology of Unmanned Aerial Vehicles (UAVs), where the growing demand for more reliable performance necessitates the development of sophisticated techniques that provide fault diagnosis and fault tolerance in a timely and accurate manner. Typically, a UAV consists of three types of subsystems: actuators, main structure and sensors. Therefore, a fault-monitoring system must be specifically designed to supervise and debug each of these subsystems, so that any faults can be addressed before they lead to disastrous consequences. In this survey article, we provide a detailed overview of recent advances and studies regarding fault diagnosis, Fault-Tolerant Control (FTC) and anomaly detection for UAVs. Concerning fault diagnosis, our interest is mainly focused on sensors and actuators, as these subsystems are mostly prone to faults, while their healthy operation usually ensures the smooth and reliable performance of the aerial vehicle. Full article

(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)

► Show Figures

Figure 1

18 pages, 5063 KiB

Open AccessEditor’s ChoiceArticle

Electromagnetic Analysis and Design Methodology for Permanent Magnet Motors Using MotorAnalysis-PM Software

by Vladimir Kuptsov, Poria Fajri, Andrzej Trzynadlowski, Guoliang Zhang and Salvador Magdaleno-Adame

Machines 2019, 7(4), 75; https://doi.org/10.3390/machines7040075 - 6 Dec 2019

Cited by 21 | Viewed by 12339

Abstract

This article presents a new and powerful freeware software called MotorAnalysis-PM and discusses its application in electromagnetic design and analysis of permanent magnet (PM) motors for the electric vehicle (EV) industry. This new PM motor software utilizes both finite element (FE) and analytical [...] Read more.

This article presents a new and powerful freeware software called MotorAnalysis-PM and discusses its application in electromagnetic design and analysis of permanent magnet (PM) motors for the electric vehicle (EV) industry. This new PM motor software utilizes both finite element (FE) and analytical methods to speed up the analysis and design process of PM motors significantly. The analysis and design methodology using MotorAnalysis-PM is presented and discussed for a 50 kW PM motor utilized in a commercial EV. To validate the accuracy of the software, the numerical results obtained from the PM motor design and analysis tool are compared with experimental results. The numerical and experimental results validate the flexibility of this software in achieving accurate motor design with short design times which is of great interest to EV and PM motor manufacturers. Full article

► Show Figures

Figure 1

21 pages, 5538 KiB

Open AccessEditor’s ChoiceReview

Review on Wearable System for Positioning Ultrasound Scanner

by Lailu Li, Lei Zhao, Rayan Hassan and Hongliang Ren

Machines 2023, 11(3), 325; https://doi.org/10.3390/machines11030325 - 24 Feb 2023

Cited by 13 | Viewed by 12140

Abstract

Although ultrasound (US) scan or diagnosis became widely employed in the 20th century, it still plays a crucial part in modern medical diagnostics, serving as a diagnostic tool or a therapy process guide. This review provides information on current wearable technologies and applications [...] Read more.

Although ultrasound (US) scan or diagnosis became widely employed in the 20th century, it still plays a crucial part in modern medical diagnostics, serving as a diagnostic tool or a therapy process guide. This review provides information on current wearable technologies and applications used in external ultrasound scanning. It offers thorough explanations that could help build upon any project utilizing wearable external US devices. It touches on several aspects of US scanning and reviews basic medical procedure concepts. The paper starts with a detailed overview of ultrasound principles, including the propagation speed of sound waves, sound wave interactions, image resolution, transducers, and probe positioning. After that, it explores wearable external US mounts and wearable external US transducers applied for sonograph purposes. The subsequent section tackles artificial intelligence methods in wearable US scanners. Finally, future external US scan directions are reported, focusing on hardware and software. Full article

(This article belongs to the Section Automation and Control Systems)

► Show Figures

Figure 1

19 pages, 3899 KiB

Open AccessEditor’s ChoiceArticle

Experimental Vibration Analysis of a Small Scale Vertical Wind Energy System for Residential Use

by Francesco Castellani, Davide Astolfi, Mauro Peppoloni, Francesco Natili, Daniele Buttà and Alexander Hirschl

Machines 2019, 7(2), 35; https://doi.org/10.3390/machines7020035 - 22 May 2019

Cited by 39 | Viewed by 11754

Abstract

In the recent years, distributed energy production has been one of the main research topics about renewable energies. The decentralization of electric production from wind resources raises the issues of reducing the size of generators, from the MW scale of industrial wind farm [...] Read more.

In the recent years, distributed energy production has been one of the main research topics about renewable energies. The decentralization of electric production from wind resources raises the issues of reducing the size of generators, from the MW scale of industrial wind farm turbines to the kW scale, and possibly employing them in urban areas, where the wind flow is complex and extremely turbulent because of the presence of buildings and obstacles. On these grounds, the use of small-scale vertical axis small wind turbines (VASWT) is a valid choice for on-site generation (OSG), considering their low sensitivity with respect to turbulent flow and that there is no need to align the turbine with wind direction, as occurs with horizontal axis small wind turbines (HASWT). In addition, VASWTs have a minor acoustic impact with respect to HASWTs. The aim of this paper is to study the interactions that take place between a 1.2 kW, vertical axis, Darrieus VASWT turbine and a small, experimental building, in order to analyze the noise and the vibrations transmitted to the structure. One method to damp the vibrations is then assessed through spectral analysis of data acquired through accelerometers located both in the mast of the wind turbine and at the building walls. The results confirm the usefulness of dampers to increase the building comfort regarding vibrations. Full article

► Show Figures

Figure 1

11 pages, 3557 KiB

Open AccessEditor’s ChoiceArticle

Functional Design of a Hybrid Leg-Wheel-Track Ground Mobile Robot

by Luca Bruzzone, Mario Baggetta, Shahab E. Nodehi, Pietro Bilancia and Pietro Fanghella

Machines 2021, 9(1), 10; https://doi.org/10.3390/machines9010010 - 12 Jan 2021

Cited by 54 | Viewed by 11360

Abstract

This paper presents the conceptual and functional design of a novel hybrid leg-wheel-track ground mobile robot for surveillance and inspection, named WheTLHLoc (Wheel-Track-Leg Hybrid Locomotion). The aim of the work is the development of a general-purpose platform capable of combining tracked locomotion on [...] Read more.

This paper presents the conceptual and functional design of a novel hybrid leg-wheel-track ground mobile robot for surveillance and inspection, named WheTLHLoc (Wheel-Track-Leg Hybrid Locomotion). The aim of the work is the development of a general-purpose platform capable of combining tracked locomotion on irregular and yielding terrains, wheeled locomotion with high energy efficiency on flat and compact grounds, and stair climbing/descent ability. The architecture of the hybrid locomotion system is firstly outlined, then the validation of its stair climbing maneuver capabilities by means of multibody simulation is presented. The embodiment design and the internal mechanical layout are then discussed. Full article

(This article belongs to the Special Issue Latest Trends of Autonomous Aerial and Terrestrial Vehicles for Service Robotics Applications)

► Show Figures

Figure 1

16 pages, 9947 KiB

Open AccessEditor’s ChoiceArticle

Design of a 3D-Printed Hand Exoskeleton Based on Force-Myography Control for Assistance and Rehabilitation

by Daniele Esposito, Jessica Centracchio, Emilio Andreozzi, Sergio Savino, Gaetano D. Gargiulo, Ganesh R. Naik and Paolo Bifulco

Machines 2022, 10(1), 57; https://doi.org/10.3390/machines10010057 - 13 Jan 2022

Cited by 47 | Viewed by 11054

Abstract

Voluntary hand movements are usually impaired after a cerebral stroke, affecting millions of people per year worldwide. Recently, the use of hand exoskeletons for assistance and motor rehabilitation has become increasingly widespread. This study presents a novel hand exoskeleton, designed to be low [...] Read more.

Voluntary hand movements are usually impaired after a cerebral stroke, affecting millions of people per year worldwide. Recently, the use of hand exoskeletons for assistance and motor rehabilitation has become increasingly widespread. This study presents a novel hand exoskeleton, designed to be low cost, wearable, easily adaptable and suitable for home use. Most of the components of the exoskeleton are 3D printed, allowing for easy replication, customization and maintenance at a low cost. A strongly underactuated mechanical system allows one to synergically move the four fingers by means of a single actuator through a rigid transmission, while the thumb is kept in an adduction or abduction position. The exoskeleton’s ability to extend a typical hypertonic paretic hand of stroke patients was firstly tested using the SimScape Multibody simulation environment; this helped in the choice of a proper electric actuator. Force-myography was used instead of the standard electromyography to voluntarily control the exoskeleton with more simplicity. The user can activate the flexion/extension of the exoskeleton by a weak contraction of two antagonist muscles. A symmetrical master–slave motion strategy (i.e., the paretic hand motion is activated by the healthy hand) is also available for patients with severe muscle atrophy. An inexpensive microcontroller board was used to implement the electronic control of the exoskeleton and provide feedback to the user. The entire exoskeleton including batteries can be worn on the patient’s arm. The ability to provide a fluid and safe grip, like that of a healthy hand, was verified through kinematic analyses obtained by processing high-framerate videos. The trajectories described by the phalanges of the natural and the exoskeleton finger were compared by means of cross-correlation coefficients; a similarity of about 80% was found. The time required for both closing and opening of the hand exoskeleton was about 0.9 s. A rigid cylindric handlebar containing a load cell measured an average power grasp force of 94.61 N, enough to assist the user in performing most of the activities of daily living. The exoskeleton can be used as an aid and to promote motor function recovery during patient’s neurorehabilitation therapy. Full article

(This article belongs to the Special Issue Feature Papers to Celebrate the First Impact Factor of Machines)

► Show Figures

Figure 1

22 pages, 5766 KiB

Open AccessEditor’s ChoiceArticle

Implementing and Visualizing ISO 22400 Key Performance Indicators for Monitoring Discrete Manufacturing Systems

by Borja Ramis Ferrer, Usman Muhammad, Wael M. Mohammed and José L. Martínez Lastra

Machines 2018, 6(3), 39; https://doi.org/10.3390/machines6030039 - 1 Sep 2018

Cited by 45 | Viewed by 10877

Abstract

The employment of tools and techniques for monitoring and supervising the performance of industrial systems has become essential for enterprises that seek to be more competitive in today’s market. The main reason is the need for validating tasks that are executed by systems, [...] Read more.

The employment of tools and techniques for monitoring and supervising the performance of industrial systems has become essential for enterprises that seek to be more competitive in today’s market. The main reason is the need for validating tasks that are executed by systems, such as industrial machines, which are involved in production processes. The early detection of malfunctions and/or improvable system values permits the anticipation to critical issues that may delay or even disallow productivity. Advances on Information and Communication Technologies (ICT)-based technologies allows the collection of data on system runtime. In fact, the data is not only collected but formatted and integrated in computer nodes. Then, the formatted data can be further processed and analyzed. This article focuses on the utilization of standard Key Performance Indicators (KPIs), which are a set of parameters that permit the evaluation of the performance of systems. More precisely, the presented research work demonstrates the implementation and visualization of a set of KPIs defined in the ISO 22400 standard-Automation systems and integration, for manufacturing operations management. The approach is validated within a discrete manufacturing web-based interface that is currently used for monitoring and controlling an assembly line at runtime. The selected ISO 22400 KPIs are described within an ontology, which the description is done according to the data models included in the KPI Markup Language (KPIML), which is an XML implementation developed by the Manufacturing Enterprise Solutions Association (MESA) international organization. Full article

► Show Figures

Figure 1

22 pages, 2573 KiB

Open AccessEditor’s ChoiceArticle

Electric Machine Design Tool for Permanent Magnet Synchronous Machines and Induction Machines

by Svenja Kalt, Jonathan Erhard and Markus Lienkamp

Machines 2020, 8(1), 15; https://doi.org/10.3390/machines8010015 - 24 Mar 2020

Cited by 24 | Viewed by 10856

Abstract

The rising mobility demand of today’s society leads to an increasing strain of noise and pollutant emissions on people and the environment. An increasing environmental awareness and the scarcity of fossil fuels are increasingly placing alternative-powered vehicles in the focus of politics, research [...] Read more.

The rising mobility demand of today’s society leads to an increasing strain of noise and pollutant emissions on people and the environment. An increasing environmental awareness and the scarcity of fossil fuels are increasingly placing alternative-powered vehicles in the focus of politics, research and development. Electric vehicles represent a promising solution to this problem. The electric machine represents a design control lever for the optimization of the electric powertrain with regard to efficiency, power, weight and size. Therefore, accurate and realistic machine design tools for the design of electric machines are becoming increasingly important. In this paper, the authors present an electric machine design tool for electric machines using MATLAB^® in order to enable an automated machine design. The electric machine design tool is published under an LGPL open source license. Full article

► Show Figures

Figure 1

134 pages, 7014 KiB

Open AccessEditor’s ChoiceReview

A Comprehensive Survey on Fault Tolerance in Multiphase AC Drives, Part 1: General Overview Considering Multiple Fault Types

by Alejandro G. Yepes, Oscar Lopez, Ignacio Gonzalez-Prieto, Mario J. Duran and Jesus Doval-Gandoy

Machines 2022, 10(3), 208; https://doi.org/10.3390/machines10030208 - 14 Mar 2022

Cited by 95 | Viewed by 10312

Abstract

Multiphase drives offer enhanced fault-tolerant capabilities compared with conventional three-phase ones. Their phase redundancy makes them able to continue running in the event of faults (e.g., open/short-circuits) in certain phases. Moreover, their greater number of degrees of freedom permits improving diagnosis and performance, [...] Read more.

Multiphase drives offer enhanced fault-tolerant capabilities compared with conventional three-phase ones. Their phase redundancy makes them able to continue running in the event of faults (e.g., open/short-circuits) in certain phases. Moreover, their greater number of degrees of freedom permits improving diagnosis and performance, not only under faults affecting individual phases, but also under those affecting the machine/drive as a whole. That is the case of failures in the dc link, resolver/encoder, control unit, cooling system, etc. Accordingly, multiphase drives are becoming remarkable contenders for applications where high reliability is required, such as electric vehicles and standalone/off-shore generation. Actually, the literature on the subject has grown exponentially in recent years. Various review papers have been published, but none of them currently cover the state-of-the-art in a comprehensive and up-to-date fashion. This two-part paper presents an overview concerning fault tolerance in multiphase drives. Hundreds of citations are classified and critically discussed. Although the emphasis is put on fault tolerance, fault detection/diagnosis is also considered to some extent, because of its importance in fault-tolerant drives. The most important recent advances, emerging trends and open challenges are also identified. Part 1 provides a comprehensive survey considering numerous kinds of faults, whereas Part 2 is focused on phase/switch open-circuit failures. Full article

(This article belongs to the Special Issue Feature Papers to Celebrate the First Impact Factor of Machines)

► Show Figures

Figure 1

19 pages, 6920 KiB

Open AccessEditor’s ChoiceArticle

Vision-Based Robotic Object Grasping—A Deep Reinforcement Learning Approach

by Ya-Ling Chen, Yan-Rou Cai and Ming-Yang Cheng

Machines 2023, 11(2), 275; https://doi.org/10.3390/machines11020275 - 12 Feb 2023

Cited by 21 | Viewed by 10046

Abstract

This paper focuses on developing a robotic object grasping approach that possesses the ability of self-learning, is suitable for small-volume large variety production, and has a high success rate in object grasping/pick-and-place tasks. The proposed approach consists of a computer vision-based object detection [...] Read more.

This paper focuses on developing a robotic object grasping approach that possesses the ability of self-learning, is suitable for small-volume large variety production, and has a high success rate in object grasping/pick-and-place tasks. The proposed approach consists of a computer vision-based object detection algorithm and a deep reinforcement learning algorithm with self-learning capability. In particular, the You Only Look Once (YOLO) algorithm is employed to detect and classify all objects of interest within the field of view of a camera. Based on the detection/localization and classification results provided by YOLO, the Soft Actor-Critic deep reinforcement learning algorithm is employed to provide a desired grasp pose for the robot manipulator (i.e., learning agent) to perform object grasping. In order to speed up the training process and reduce the cost of training data collection, this paper employs the Sim-to-Real technique so as to reduce the likelihood of damaging the robot manipulator due to improper actions during the training process. The V-REP platform is used to construct a simulation environment for training the deep reinforcement learning neural network. Several experiments have been conducted and experimental results indicate that the 6-DOF industrial manipulator successfully performs object grasping with the proposed approach, even for the case of previously unseen objects. Full article

(This article belongs to the Special Issue Recent Trends and Interdisciplinary Applications of AI & Robotics)

► Show Figures

Figure 1

20 pages, 13342 KiB

Open AccessEditor’s ChoiceArticle

Integration of Deep Learning for Automatic Recognition of 2D Engineering Drawings

by Yi-Hsin Lin, Yu-Hung Ting, Yi-Cyun Huang, Kai-Lun Cheng and Wen-Ren Jong

Machines 2023, 11(8), 802; https://doi.org/10.3390/machines11080802 - 4 Aug 2023

Cited by 22 | Viewed by 10038

Abstract

In an environment where manufacturing precision requirements are increasing, complete project plans can consist of hundreds of engineering drawings. The presentation of these drawings often varies based on personal preferences, leading to inconsistencies in format and symbols. The lack of standardization in these [...] Read more.

In an environment where manufacturing precision requirements are increasing, complete project plans can consist of hundreds of engineering drawings. The presentation of these drawings often varies based on personal preferences, leading to inconsistencies in format and symbols. The lack of standardization in these aspects can result in inconsistent interpretations during subsequent analysis. Therefore, proper annotation of engineering drawings is crucial as it determines product quality, subsequent inspections, and processing costs. To reduce the time and cost associated with interpreting and analyzing drawings, as well as to minimize human errors in judgment, we developed an engineering drawing recognition system. This study employs geometric dimensioning and tolerancing (GD&T) in accordance with the ASME (American Society of Mechanical Engineers) Y14.5 2018 specification to describe the language of engineering drawings. Additionally, PyTorch, OpenCV, and You Only Look Once (YOLO) are utilized for training. Existing 2D engineering drawings serve as the training data, and image segmentation is performed to identify objects such as dimensions, tolerances, functional frames, and geometric symbols in the drawings using the network model. By reading the coordinates corresponding to each object, the correct values are displayed. Real-world cases are utilized to train the model with multiple engineering drawings containing mixed features, resulting in recognition capabilities surpassing those of single-feature identification. This approach improves the recognition accuracy of deep learning models and makes engineering drawing and image recognition more practical. The recognition results are directly stored in a database, reducing product verification time and preventing errors that may occur due to manual data entry, thereby avoiding subsequent quality control issues. The accuracy rates achieved are as follows: 85% accuracy in detecting views in 2D engineering drawings, 70% accuracy in detecting annotation groups and annotations, and 80% accuracy in text and symbol recognition. Full article

(This article belongs to the Special Issue Smart Manufacturing and Industrial Automation)

► Show Figures

Figure 1

14 pages, 5204 KiB

Open AccessEditor’s ChoiceArticle

Optimization Design and Performance Analysis of a Reverse-Salient Permanent Magnet Synchronous Motor

by Xiaokun Zhao, Baoquan Kou, Changchuang Huang and Lu Zhang

Machines 2022, 10(3), 204; https://doi.org/10.3390/machines10030204 - 11 Mar 2022

Cited by 14 | Viewed by 9768

Abstract

The reverse-salient permanent magnet synchronous motor (RSPMSM) is a competitive candidate for electric vehicles due to its high torque density and high efficiency. This paper proposes an optimized RSPMSM by adopting a segmented permanent magnet structure. First, the structure, electromagnetic torque, and current [...] Read more.

The reverse-salient permanent magnet synchronous motor (RSPMSM) is a competitive candidate for electric vehicles due to its high torque density and high efficiency. This paper proposes an optimized RSPMSM by adopting a segmented permanent magnet structure. First, the structure, electromagnetic torque, and current control laws of the RSPMSM are introduced in detail. Second, the optimization design method of the RSPMSM is proposed by taking the torque and constant-power speed range as optimized objectives, with the saliency ratio as a constraint. The optimized model of the RSPMSM is determined using the genetic algorithm (GA). Further performance analysis and comparisons are made between the initial motor and the optimized motor. Finally, a prototype is manufactured, and the performance of the RSPMSM is verified through the finite element method (FEM) and experiments. Full article

(This article belongs to the Section Electrical Machines and Drives)

► Show Figures

Figure 1

54 pages, 1710 KiB

Open AccessEditor’s ChoiceReview

A Systematic Literature Review of Cutting Tool Wear Monitoring in Turning by Using Artificial Intelligence Techniques

by Lorenzo Colantonio, Lucas Equeter, Pierre Dehombreux and François Ducobu

Machines 2021, 9(12), 351; https://doi.org/10.3390/machines9120351 - 10 Dec 2021

Cited by 54 | Viewed by 9627

Abstract

In turning operations, the wear of cutting tools is inevitable. As workpieces produced with worn tools may fail to meet specifications, the machining industries focus on replacement policies that mitigate the risk of losses due to scrap. Several strategies, from empiric laws to [...] Read more.

In turning operations, the wear of cutting tools is inevitable. As workpieces produced with worn tools may fail to meet specifications, the machining industries focus on replacement policies that mitigate the risk of losses due to scrap. Several strategies, from empiric laws to more advanced statistical models, have been proposed in the literature. More recently, many monitoring systems based on Artificial Intelligence (AI) techniques have been developed. Due to the scope of different artificial intelligence approaches, having a holistic view of the state of the art on this subject is complex, in part due to a lack of recent comprehensive reviews. This literature review therefore presents 20 years of literature on this subject obtained following a Systematic Literature Review (SLR) methodology. This SLR aims to answer the following research question: “How is the AI used in the framework of monitoring/predicting the condition of tools in stable turning condition?” To answer this research question, the “Scopus” database was consulted in order to gather relevant publications published between 1 January 2000 and 1 January 2021. The systematic approach yielded 8426 articles among which 102 correspond to the inclusion and exclusion criteria which limit the application of AI to stable turning operation and online prediction. A bibliometric analysis performed on these articles highlighted the growing interest of this subject in the recent years. A more in-depth analysis of the articles is also presented, mainly focusing on six AI techniques that are highly represented in the literature: Artificial Neural Network (ANN), fuzzy logic, Support Vector Machine (SVM), Self-Organizing Map (SOM), Hidden Markov Model (HMM), and Convolutional Neural Network (CNN). For each technique, the trends in the inputs, pre-processing techniques, and outputs of the AI are presented. The trends highlight the early and continuous importance of ANN, and the emerging interest of CNN for tool condition monitoring. The lack of common benchmark database for evaluating models performance does not allow clear comparisons of technique performance. Full article

(This article belongs to the Special Issue Advances in Tool Life Prediction in Machining)

► Show Figures

Figure 1

29 pages, 4758 KiB

Open AccessEditor’s ChoiceReview

Planet Load-Sharing and Phasing

by Moslem Molaie, Samira Deylaghian, Giovanni Iarriccio, Farhad S. Samani, Antonio Zippo and Francesco Pellicano

Machines 2022, 10(8), 634; https://doi.org/10.3390/machines10080634 - 30 Jul 2022

Cited by 8 | Viewed by 9495

Abstract

This paper presents an analysis of the scientific literature devoted to the problem of load sharing and phasing in planetary gearboxes. The wide range of research topics demonstrates the technical challenges of understanding planetary load-sharing and planet phasing. This review includes studies having [...] Read more.

This paper presents an analysis of the scientific literature devoted to the problem of load sharing and phasing in planetary gearboxes. The wide range of research topics demonstrates the technical challenges of understanding planetary load-sharing and planet phasing. This review includes studies having the goal of developing models for load sharing and exploring the positive or negative effects of different parameters such as phasing on the load distribution among planets. Practical aspects are also considered, for example, the effects of some errors that are unavoidable during manufacturing or working conditions, e.g., misalignments or position errors. Methods for improving the load-sharing characteristics, e.g., flexible ring or floating components, are discussed as well. Full article

(This article belongs to the Section Machine Design and Theory)

► Show Figures

Figure 1

16 pages, 5771 KiB

Open AccessEditor’s ChoiceArticle

Dual-Motor Planetary Transmission to Improve Efficiency in Electric Vehicles

by Giacomo Mantriota and Giulio Reina

Machines 2021, 9(3), 58; https://doi.org/10.3390/machines9030058 - 11 Mar 2021

Cited by 38 | Viewed by 8789

Abstract

Electric cars are typically subject to highly variable operational conditions, especially when they drive in urban environments. Consequently, the efficiency of the electric motors may degrade significantly, possibly leading to lower autonomy and higher running costs. Latest advances in power electronics and motion [...] Read more.

Electric cars are typically subject to highly variable operational conditions, especially when they drive in urban environments. Consequently, the efficiency of the electric motors may degrade significantly, possibly leading to lower autonomy and higher running costs. Latest advances in power electronics and motion control have paved the way to the development of novel architectures of full electric power transmissions. In this paper, a dual-motor solution is proposed where two smaller motors are coupled via a planetary gear, in contrast to the standard configuration that uses one larger motor directly connected to the drive wheels with a fixed ratio reducer. The dual-motor architecture guarantees that both motors operate in the vicinity of their optimal working range, resulting in a higher overall energy efficiency. The technical requirements and the control strategy of the dual-motor system are selected through a parametric optimization process. Results included were obtained from extensive simulations performed over different standard driving cycles, showing that the dual-motor power transmission generally outperforms the single-motor counterpart with an average efficiency improvement of about 9% that is reached in both the power delivery and regeneration stage. Full article

(This article belongs to the Special Issue Italian Advances on MMS)

► Show Figures

Figure 1

13 pages, 4208 KiB

Open AccessEditor’s ChoiceArticle

Application of IoT-Aided Simulation to Manufacturing Systems in Cyber-Physical System

by Yifei Tan, Wenhe Yang, Kohtaroh Yoshida and Soemon Takakuwa

Machines 2019, 7(1), 2; https://doi.org/10.3390/machines7010002 - 3 Jan 2019

Cited by 65 | Viewed by 8667

Abstract

With the rapid development of mobile and wireless networking technologies, data has become more ubiquitous and the IoT (Internet of Things) is attracting much attention due to high expectations for enabling innovative service, efficiency, and productivity improvement. In next-generation manufacturing, the digital twin [...] Read more.

With the rapid development of mobile and wireless networking technologies, data has become more ubiquitous and the IoT (Internet of Things) is attracting much attention due to high expectations for enabling innovative service, efficiency, and productivity improvement. In next-generation manufacturing, the digital twin (DT) has been proposed as a new concept and simulation tool for collecting and synchronizing real-world information in real time in cyber space to cope with the challenges of smart factories. Although the DT is considered a challenging technology, it is still at the conceptual stage and only a few studies have specifically discussed methods for its construction and implementation. In this study, we first explain the concept of DT and important issues involved in developing it within an IoT-aided manufacturing environment. Then, we propose a DT construction framework and scheme for inputting data derived from the IoT into a simulation model. Finally, we describe how we verify the effectiveness of the proposed framework and scheme, by constructing a DT-oriented simulation model for an IoT-aided manufacturing system. Full article

(This article belongs to the Special Issue Smart Manufacturing)

► Show Figures

Figure 1

23 pages, 8318 KiB

Open AccessEditor’s ChoiceArticle

Design and Optimization of a Centrifugal Pump for Slurry Transport Using the Response Surface Method

by Khaled Alawadhi, Bashar Alzuwayer, Tareq Ali Mohammad and Mohammad H. Buhemdi

Machines 2021, 9(3), 60; https://doi.org/10.3390/machines9030060 - 13 Mar 2021

Cited by 24 | Viewed by 8547

Abstract

Since centrifugal pumps consume a mammoth amount of energy in various industrial applications, their design and optimization are highly relevant to saving maximum energy and increasing the system’s efficiency. In the current investigation, a centrifugal pump has been designed and optimized. The study [...] Read more.

Since centrifugal pumps consume a mammoth amount of energy in various industrial applications, their design and optimization are highly relevant to saving maximum energy and increasing the system’s efficiency. In the current investigation, a centrifugal pump has been designed and optimized. The study has been carried out for the specific application of transportation of slurry at a flow rate of 120 m³/hr to a head of 20 m. For the optimization process, a multi-objective genetic algorithm (MOGA) and response surface methodology (RSM) have been employed. The process is based on the mean line design of the pump. It utilizes six geometric parameters as design variables, i.e., number of vanes, inlet beta shroud, exit beta shroud, hub inlet blade draft, Rake angle, and the impeller’s rotational speed. The objective functions employed are pump power, hydraulic efficiency, volumetric efficiency, and pump efficiency. In this reference, five different software packages, i.e., ANSYS Vista, ANSYS DesignModeler, response surface optimization software, and ANSYS CFX, were coupled to achieve the optimized design of the pump geometry. Characteristic maps were generated using simulations conducted for 45 points. Additionally, erosion rate was predicted using 3-D numerical simulations under various conditions. Finally, the transient behavior of the pump, being the highlight of the study, was evaluated. Results suggest that the maximum fluctuation in the local pressure and stresses on the cases correspond to a phase angle of 0°–30° of the casing that in turn corresponds to the maximum erosion rates in the region. Full article

(This article belongs to the Section Machine Design and Theory)

► Show Figures

Figure 1

17 pages, 4950 KiB

Open AccessEditor’s ChoiceArticle

The Setup Design for Selective Laser Sintering of High-Temperature Polymer Materials with the Alignment Control System of Layer Deposition

by Alexey Nazarov, Innokentiy Skornyakov and Igor Shishkovsky

Machines 2018, 6(1), 11; https://doi.org/10.3390/machines6010011 - 5 Mar 2018

Cited by 10 | Viewed by 8505

Abstract

This paper presents the design of an additive setup for the selective laser sintering (SLS) of high-temperature polymeric materials, which is distinguished by an original control system for aligning the device for depositing layers of polyether ether ketone (PEEK) powder. The kinematic and [...] Read more.

This paper presents the design of an additive setup for the selective laser sintering (SLS) of high-temperature polymeric materials, which is distinguished by an original control system for aligning the device for depositing layers of polyether ether ketone (PEEK) powder. The kinematic and laser-optical schemes are given. The main cooling circuits are described. The proposed technical and design solutions enable conducting the SLS process in different types of high-temperature polymer powders. The principles of the device adjustment for depositing powder layers based on an integral thermal analysis are disclosed. The PEEK sinterability was shown on the designed installation. The physic-mechanical properties of the tested 3D parts were evaluated in comparison with the known data and showed an acceptable quality. Full article

(This article belongs to the Special Issue Process Innovation in Digital Manufacturing)

► Show Figures

Graphical abstract

20 pages, 3534 KiB

Open AccessEditor’s ChoiceArticle

YOLO-GD: A Deep Learning-Based Object Detection Algorithm for Empty-Dish Recycling Robots

by Xuebin Yue, Hengyi Li, Masao Shimizu, Sadao Kawamura and Lin Meng

Machines 2022, 10(5), 294; https://doi.org/10.3390/machines10050294 - 22 Apr 2022

Cited by 61 | Viewed by 8322

Abstract

Due to the workforce shortage caused by the declining birth rate and aging population, robotics is one of the solutions to replace humans and overcome this urgent problem. This paper introduces a deep learning-based object detection algorithm for empty-dish recycling robots to automatically [...] Read more.

Due to the workforce shortage caused by the declining birth rate and aging population, robotics is one of the solutions to replace humans and overcome this urgent problem. This paper introduces a deep learning-based object detection algorithm for empty-dish recycling robots to automatically recycle dishes in restaurants and canteens, etc. In detail, a lightweight object detection model YOLO-GD (Ghost Net and Depthwise convolution) is proposed for detecting dishes in images such as cups, chopsticks, bowls, towels, etc., and an image processing-based catch point calculation is designed for extracting the catch point coordinates of the different-type dishes. The coordinates are used to recycle the target dishes by controlling the robot arm. Jetson Nano is equipped on the robot as a computer module, and the YOLO-GD model is also quantized by TensorRT for improving the performance. The experimental results demonstrate that the YOLO-GD model is only 1/5 size of the state-of-the-art model YOLOv4, and the

m A P

of YOLO-GD achieves 97.38%, 3.41% higher than YOLOv4. After quantization, the YOLO-GD model decreases the inference time per image from 207.92 ms to 32.75 ms, and the

m A P

is 97.42%, which is slightly higher than the model without quantization. Through the proposed image processing method, the catch points of various types of dishes are effectively extracted. The functions of empty-dish recycling are realized and will lead to further development toward practical use. Full article

(This article belongs to the Special Issue Selected Papers from The 11th International Conference on Advanced Mechatronic Systems (ICAMechS 2021))

► Show Figures

Figure 1

23 pages, 8684 KiB

Open AccessEditor’s ChoiceArticle

Analytical Study on the Cornering Behavior of an Articulated Tracked Vehicle

by Antonio Tota, Enrico Galvagno and Mauro Velardocchia

Machines 2021, 9(2), 38; https://doi.org/10.3390/machines9020038 - 9 Feb 2021

Cited by 19 | Viewed by 8244

Abstract

Articulated tracked vehicles have been traditionally studied and appreciated for the extreme maneuverability and mobility flexibility in terms of grade and side slope capabilities. The articulation joint represents an attractive and advantageous solution, if compared to the traditional skid steering operation, by avoiding [...] Read more.

Articulated tracked vehicles have been traditionally studied and appreciated for the extreme maneuverability and mobility flexibility in terms of grade and side slope capabilities. The articulation joint represents an attractive and advantageous solution, if compared to the traditional skid steering operation, by avoiding any trust adjustment between the outside and inside tracks. This paper focuses on the analysis and control of an articulated tracked vehicle characterized by two units connected through a mechanical multiaxial joint that is hydraulically actuated to allow the articulated steering operation. A realistic eight degrees of freedom mathematical model is introduced to include the main nonlinearities involved in the articulated steering behavior. A linearized vehicle model is further proposed to analytically characterize the cornering steady-state and transient behaviors for small lateral accelerations. Finally, a hitch angle controller is designed by proposing a torque-based and a speed-based Proportional Integral Derivative (PID) logics. The controller is also verified by simulating maneuvers typically adopted for handling analysis. Full article

(This article belongs to the Special Issue Italian Advances on MMS)

► Show Figures

Figure 1

14 pages, 3752 KiB

Open AccessEditor’s ChoiceArticle

Deep Learning-Based Landmark Detection for Mobile Robot Outdoor Localization

by Sivapong Nilwong, Delowar Hossain, Shin-ichiro Kaneko and Genci Capi

Machines 2019, 7(2), 25; https://doi.org/10.3390/machines7020025 - 18 Apr 2019

Cited by 45 | Viewed by 8174

Abstract

Outdoor mobile robot applications generally implement Global Positioning Systems (GPS) for localization tasks. However, GPS accuracy in outdoor localization has less accuracy in different environmental conditions. This paper presents two outdoor localization methods based on deep learning and landmark detection. The first localization [...] Read more.

Outdoor mobile robot applications generally implement Global Positioning Systems (GPS) for localization tasks. However, GPS accuracy in outdoor localization has less accuracy in different environmental conditions. This paper presents two outdoor localization methods based on deep learning and landmark detection. The first localization method is based on the Faster Regional-Convolutional Neural Network (Faster R-CNN) landmark detection in the captured image. Then, a feedforward neural network (FFNN) is trained to determine robot location coordinates and compass orientation from detected landmarks. The second localization employs a single convolutional neural network (CNN) to determine location and compass orientation from the whole image. The dataset consists of images, geolocation data and labeled bounding boxes to train and test two proposed localization methods. Results are illustrated with absolute errors from the comparisons between localization results and reference geolocation data in the dataset. The experimental results pointed both presented localization methods to be promising alternatives to GPS for outdoor localization. Full article

(This article belongs to the Special Issue Selected Papers from Conference on Control, Mechatronics and Automation (ICCMA))

► Show Figures

Figure 1

27 pages, 3938 KiB

Open AccessEditor’s ChoiceArticle

Electrically Driven Lower Limb Exoskeleton Rehabilitation Robot Based on Anthropomorphic Design

by Moyao Gao, Zhanli Wang, Zaixiang Pang, Jianwei Sun, Jing Li, Shuang Li and Hansi Zhang

Machines 2022, 10(4), 266; https://doi.org/10.3390/machines10040266 - 7 Apr 2022

Cited by 37 | Viewed by 8140

Abstract

To help people with impairment of lower extremity movement regain the ability to stand and walk, and to enhance limb function, this study proposes an anthropomorphic design of an electrically driven, lower-limb exoskeleton rehabilitation robot. The angular range of the robot’s motion was [...] Read more.

To help people with impairment of lower extremity movement regain the ability to stand and walk, and to enhance limb function, this study proposes an anthropomorphic design of an electrically driven, lower-limb exoskeleton rehabilitation robot. The angular range of the robot’s motion was determined according to the characteristics of the targeted lower-limb joints; the robot was given an active–passive anthropomorphic design with 12 degrees of freedom. The multi-degree-of-freedom hip exoskeleton, bionic artificial knee exoskeleton and passive rigid-flexible coupling ankle exoskeleton can assist patients in rehabilitation exercises with better wear comfort and exercise flexibility. A kinetic model of the seven-rod lower-limb exoskeleton rehabilitation robot was built, and data analysis of the dynamically captured motion trajectory was conducted. These provided a theoretical basis for gait planning and the control system of the lower-limb exoskeleton rehabilitation robot. The results show that the lower-limb exoskeleton rehabilitation robot system possesses sound wearing comfort and movement flexibility, and the degree of freedom of movement of the exoskeleton robot matches well with that of human movement. The robot can thus provide effective assistance to patients’ standing and walking rehabilitation training. Full article

(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)

► Show Figures

Figure 1

14 pages, 2177 KiB

Open AccessEditor’s ChoiceArticle

A Compatible Design of a Passive Exoskeleton to Reduce the Body–Exoskeleton Interaction Force

by Nengbing Zhou, Yali Liu, Qiuzhi Song and Dehao Wu

Machines 2022, 10(5), 371; https://doi.org/10.3390/machines10050371 - 13 May 2022

Cited by 10 | Viewed by 8000

Abstract

In the research and development of a passive exoskeleton, the body–exoskeleton coupling mode is a key point to reduce the interaction force and realize the efficient assistance of the exoskeleton. The purpose of this paper was to explore a cooperative movement mode between [...] Read more.

In the research and development of a passive exoskeleton, the body–exoskeleton coupling mode is a key point to reduce the interaction force and realize the efficient assistance of the exoskeleton. The purpose of this paper was to explore a cooperative movement mode between human and passive exoskeleton for reducing the body–exoskeleton interaction force. Firstly, through the research of the body–exoskeleton interactive mode, we analyzed the kinematic and dynamic constraint of the exoskeleton and established a dynamic model of the body–exoskeleton system. On this basis, the characteristic of the body–exoskeleton interaction force was analyzed; then, we put forward a mode that uses human gravity and load weight to maintain the stability of the exoskeleton’s movement to achieve the goal of reducing the interaction force. Based on the human–exoskeleton integrated mode, we constructed a mechanical model and simulated the change in interaction force in this mode; the simulation results showed that the interaction force at the lower leg was 98.5% less than that of the pure mechanical exoskeleton. Finally, we developed a prototype that was made of plastic parts and finished the experiment by walking with a load of 30 kg. The experimental results showed that this mode reduced the body–exoskeleton interaction force by 65.1%, which verified the effectiveness of the body–exoskeleton coupling mode preliminarily. The research results provided a new analytical approach for the design of a passive exoskeleton, and its improvement effect could be extended from the lower leg of the body–exoskeleton to the thigh or trunk, and guide the design of a passive exoskeleton. Full article

(This article belongs to the Section Automation and Control Systems)

► Show Figures

Figure 1

14 pages, 2012 KiB

Open AccessEditor’s ChoiceArticle

Developing a Combined Method for Detection of Buried Metal Objects

by Ivan V. Bryakin, Igor V. Bochkarev, Vadim R. Khramshin and Ekaterina A. Khramshina

Machines 2021, 9(5), 92; https://doi.org/10.3390/machines9050092 - 2 May 2021

Cited by 6 | Viewed by 7994

Abstract

This paper discusses the author-developed novel method for the detection of buried metal objects that combines two basic subsurface sensing methods: one based on changes in the electromagnetic field parameters as induced by the inner or surficial impedance of the medium when affected [...] Read more.

This paper discusses the author-developed novel method for the detection of buried metal objects that combines two basic subsurface sensing methods: one based on changes in the electromagnetic field parameters as induced by the inner or surficial impedance of the medium when affected by a propagating magnetic field; and one based on changes in the input impedance of the receiver as induced by the electromagnetic properties of the probed medium. The proposed method utilizes three instrumentation channels: two primary channels come from the ferrite magnetic antenna (the receiver), where the first channel is used to measure the current voltage amplitude of the active input signal component, while the second channel measures the current voltage amplitude of the reactive input signal component; an additional (secondary) channel comes from the emitting frame antenna (the transmitter) to measure the current amplitude of the exciting current. This data redundancy proves to significantly improve the reliability and accuracy of detecting buried metal objects. Implementation of the computational procedures for the proposed method helped to detect and identify buried objects by their specific electrical conductance and magnetic permeability, while also locating them depth-wise. The research team has designed an induction probe that contains two mutually orthogonal antennas (a frame transmitter and ferrite receiver); the authors herein propose a metal detector design that implements the proposed induction sensing method. Experimental research proved the developed combined method for searching for buried metal objects efficient and well-performing. Full article

(This article belongs to the Section Automation and Control Systems)

► Show Figures

Figure 1

21 pages, 6926 KiB

Open AccessEditor’s ChoiceReview

Utilization of Additive Manufacturing in the Thermal Design of Electrical Machines: A Review

by Martin Sarap, Ants Kallaste, Payam Shams Ghahfarokhi, Hans Tiismus and Toomas Vaimann

Machines 2022, 10(4), 251; https://doi.org/10.3390/machines10040251 - 31 Mar 2022

Cited by 22 | Viewed by 7870

Abstract

Additive manufacturing (AM) is a key technology for advancing many fields, including electrical machines. It offers unparalleled design freedom together with low material waste and fast prototyping, which is why it has become to focus of many researchers. For electrical machines, AM allows [...] Read more.

Additive manufacturing (AM) is a key technology for advancing many fields, including electrical machines. It offers unparalleled design freedom together with low material waste and fast prototyping, which is why it has become to focus of many researchers. For electrical machines, AM allows the production of designs with optimized mechanical, electromagnetic and thermal parameters. This paper attempts to give the reader an overview of the existing research and thermal solutions which have been realized with the use of AM. These include novel heat sink and heat exchanger designs, solutions for cooling the machine windings directly, and additively manufactured hollow windings. Some solutions such as heat pipes, which have been produced with AM but not used to cool electrical machines, are also discussed, as these are used in conventional designs and will certainly be used for additively manufactured electrical machines in the future. Full article

(This article belongs to the Special Issue Future Trends in Advanced Design of Electrical Machines, Drives and Electric Vehicles Using Additive Manufacturing Approaches)

► Show Figures

Figure 1

18 pages, 2747 KiB

Open AccessEditor’s ChoiceArticle

Design of Nonlinear Control of Gas Turbine Engine Based on Constant Eigenvectors

by Sagit Valeev and Natalya Kondratyeva

Machines 2021, 9(3), 49; https://doi.org/10.3390/machines9030049 - 25 Feb 2021

Cited by 7 | Viewed by 7706

Abstract

A gas turbine engine represents a complex dynamic control object. Its characteristics change depending on the state of the environment and the regimes of its operation. This paper discusses an algorithmic approach to the design of a nonlinear controller, based on the concept [...] Read more.

A gas turbine engine represents a complex dynamic control object. Its characteristics change depending on the state of the environment and the regimes of its operation. This paper discusses an algorithmic approach to the design of a nonlinear controller, based on the concept of constant eigenvectors and analytical design of the control system. The proposed design method makes it possible to ensure the stability and the required quality of transient processes at different acceleration modes. In this case, the constancy of the matrix of the canonical basis of the closed-loop control system is assumed, which guarantees stability. The design of a neural network dynamic model of a gas turbine engine based on a neural network approximator with one input and multiple outputs is considered. An example of the design of a nonlinear controller for a gas turbine engine is considered, the neural network model of which is given in the state space. The application of neural network approximation of controller coefficients is presented. Full article

(This article belongs to the Special Issue Mechatronic System for Automatic Control)

► Show Figures

Figure 1

10 pages, 2965 KiB

Open AccessEditor’s ChoiceCommunication

Optimal Design of Double-Pole Magnetization BLDC Motor and Comparison with Single-Pole Magnetization BLDC Motor in Terms of Electromagnetic Performance

by Hyo-Seob Shin, Gang-Hyeon Jang, Kyung-Hun Jung, Seong-Kook Cho, Jang-Young Choi and Hyeon-Jae Shin

Machines 2021, 9(1), 18; https://doi.org/10.3390/machines9010018 - 17 Jan 2021

Cited by 1 | Viewed by 7667

Abstract

This study presents an optimal double-pole magnetization brushless DC (BLDC) motor design, compared to a single-pole magnetization BLDC motor in terms of electromagnetic performance. Initially, a double-pole model is selected based on the permanent magnet (PM) of the single-pole model. The pole separation [...] Read more.

This study presents an optimal double-pole magnetization brushless DC (BLDC) motor design, compared to a single-pole magnetization BLDC motor in terms of electromagnetic performance. Initially, a double-pole model is selected based on the permanent magnet (PM) of the single-pole model. The pole separation space, which is generated in the magnetization process of the double-pole PM, is selected based on the pole space of the single-pole model. Moreover, the PM offset is selected considering the PM volume of the single-pole model. Further, an optimal model is selected using the multiple response optimal method, which is a type of response surface methodology (RSM). The objective of the optimal design is to maintain the back EMF and decrease the cogging torque; the design variables include the pole separation space and PM offset. The experimental points of the initial model are designed using the central composite method (CCD). Finally, the optimization is verified by comparing the experimental and analysis results of the single-pole model with the analysis results of the optimal model. Full article

► Show Figures

Figure 1

18 pages, 3300 KiB

Open AccessEditor’s ChoiceArticle

Tailor-Made Hand Exoskeletons at the University of Florence: From Kinematics to Mechatronic Design

by Nicola Secciani, Matteo Bianchi, Alessandro Ridolfi, Federica Vannetti, Yary Volpe, Lapo Governi, Massimo Bianchini and Benedetto Allotta

Machines 2019, 7(2), 22; https://doi.org/10.3390/machines7020022 - 3 Apr 2019

Cited by 23 | Viewed by 7593

Abstract

Recently, robotics has increasingly become a companion for the human being and assisting physically impaired people with robotic devices is showing encouraging signs regarding the application of this largely investigated technology to the clinical field. As of today, however, exoskeleton design can still [...] Read more.

Recently, robotics has increasingly become a companion for the human being and assisting physically impaired people with robotic devices is showing encouraging signs regarding the application of this largely investigated technology to the clinical field. As of today, however, exoskeleton design can still be considered a hurdle task and, even in modern robotics, aiding those patients who have lost or injured their limbs is surely one of the most challenging goal. In this framework, the research activity carried out by the Department of Industrial Engineering of the University of Florence concentrated on the development of portable, wearable and highly customizable hand exoskeletons to aid patients suffering from hand disabilities, and on the definition of patient-centered design strategies to tailor-made devices specifically developed on the different users’ needs. Three hand exoskeletons versions will be presented in this paper proving the major taken steps in mechanical designing and controlling a compact and lightweight solution. The performance of the resulting systems has been tested in a real-use scenario. The obtained results have been satisfying, indicating that the derived solutions may constitute a valid alternative to existing hand exoskeletons so far studied in the rehabilitation and assistance fields. Full article

(This article belongs to the Special Issue Advances of Italian Machine Design)

► Show Figures

Figure 1

26 pages, 7851 KiB

Open AccessEditor’s ChoiceArticle

Modeling, Design, and Implementation of an Underactuated Gripper with Capability of Grasping Thin Objects

by Long Kang, Sang-Hwa Kim and Byung-Ju Yi

Machines 2021, 9(12), 347; https://doi.org/10.3390/machines9120347 - 9 Dec 2021

Cited by 9 | Viewed by 7515

Abstract

Underactuated robotic grippers have the advantage of lower cost, simpler control, and higher safety over the fully actuated grippers. In this study, an underactuated robotic finger is presented. The design issues that should be considered for stable grasping are discussed in detail. This [...] Read more.

Underactuated robotic grippers have the advantage of lower cost, simpler control, and higher safety over the fully actuated grippers. In this study, an underactuated robotic finger is presented. The design issues that should be considered for stable grasping are discussed in detail. This robotic finger is applied to design a two-fingered underactuated gripper. Firstly, a new three-DOF linkage-driven robotic finger that combines a five-bar mechanism and a double parallelogram is presented. This special architecture allows us to put all of the required actuators into the palm. By adding a torsion spring and a mechanical stopper at a passive joint, this underactuated finger mechanism can be used to perform parallel grasping, shape-adaptive grasping, and environmental contact-based grasp. Secondly, the dynamic model of this robotic finger is developed to investigate how to select an appropriate torsion spring. The dynamic simulation is performed with a multi-body dynamic simulator to verify our proposed approach. Moreover, static grasp models of both two-point and three-point contact grasps are investigated. Finally, different types of grasping modes are verified experimentally with a two-fingered underactuated robotic gripper. Full article

(This article belongs to the Section Automation and Control Systems)

► Show Figures

Figure 1

20 pages, 13069 KiB

Open AccessEditor’s ChoiceArticle

Tracking and Counting of Tomato at Different Growth Period Using an Improving YOLO-Deepsort Network for Inspection Robot

by Yuhao Ge, Sen Lin, Yunhe Zhang, Zuolin Li, Hongtai Cheng, Jing Dong, Shanshan Shao, Jin Zhang, Xiangyu Qi and Zedong Wu

Machines 2022, 10(6), 489; https://doi.org/10.3390/machines10060489 - 17 Jun 2022

Cited by 67 | Viewed by 7365

Abstract

To realize tomato growth period monitoring and yield prediction of tomato cultivation, our study proposes a visual object tracking network called YOLO-deepsort to identify and count tomatoes in different growth periods. Based on the YOLOv5s model, our model uses shufflenetv2, combined with the [...] Read more.

To realize tomato growth period monitoring and yield prediction of tomato cultivation, our study proposes a visual object tracking network called YOLO-deepsort to identify and count tomatoes in different growth periods. Based on the YOLOv5s model, our model uses shufflenetv2, combined with the CBAM attention mechanism, to compress the model size from the algorithm level. In the neck part of the network, the BiFPN multi-scale fusion structure is used to improve the prediction accuracy of the network. When the target detection network completes the bounding box prediction of the target, the Kalman filter algorithm is used to predict the target’s location in the next frame, which is called the tracker in this paper. Finally, calculate the bounding box error between the predicted bounding box and the bounding box output by the object detection network to update the parameters of the Kalman filter and repeat the above steps to achieve the target tracking of tomato fruits and flowers. After getting the tracking results, we use OpenCV to create a virtual count line to count the targets. Our algorithm achieved a competitive result based on the above methods: The mean average precision of flower, green tomato, and red tomato was 93.1%, 96.4%, and 97.9%. Moreover, we demonstrate the tracking ability of the model and the counting process by counting tomato flowers. Overall, the YOLO-deepsort model could fulfill the actual requirements of tomato yield forecast in the greenhouse scene, which provide theoretical support for crop growth status detection and yield forecast. Full article

(This article belongs to the Special Issue Recent Advances in Computer Vision Technology and Its Agricultural Application)

► Show Figures

Figure 1

16 pages, 5882 KiB

Open AccessEditor’s ChoiceArticle

Fatigue Analysis of Dozer Push Arms under Tilt Bulldozing Conditions

by Longye Pan, Xianglong Guan, Xingwei Luan, Yajun Huang, Ruwei Zhang, Jin-Hwan Choi and Xiangqian Zhu

Machines 2022, 10(1), 38; https://doi.org/10.3390/machines10010038 - 4 Jan 2022

Cited by 4 | Viewed by 7289

Abstract

Tilt bulldozing generates unbalanced loads on two push arms, which leads to the service lives of the two push arms being different. Because the push arms rotate in triaxial directions during tilt bulldozing, it is difficult to accurately analyze the fatigue life of [...] Read more.

Tilt bulldozing generates unbalanced loads on two push arms, which leads to the service lives of the two push arms being different. Because the push arms rotate in triaxial directions during tilt bulldozing, it is difficult to accurately analyze the fatigue life of the push arm with one specific boundary condition and loading history. Therefore, a fatigue analysis of the push arms under tilt bulldozing conditions is proposed based on co-simulation of RecurDyn-EDEM-AMESim in this paper. The control of tilt bulldozing conditions is realized automatically according to the tilt angle and blade depth. The dynamic loads of the push arms are accurately calculated in this virtual model. Subsequently, the stress–time histories are obtained to investigate the fatigue lives of push arms. Both the overall damage and the initiation positions of the cracks are predicted herein. It is determined that the fatigue lives of the right and left push arms are 7,317.84 h and 39,381.89 h, respectively. Thus, the life of the push arm on the blade’s tilted side is reduced by 81.42% compared to the other side. Additionally, experimental tests are conducted to verify the accuracy of the virtual model. Analysis results indicate that the strains of the push arms according to the virtual simulation are close to those measured in the experiments. Full article

(This article belongs to the Special Issue Dynamics and Diagnostics of Heavy-Duty Industrial Machines)

► Show Figures

Figure 1

15 pages, 2069 KiB

Open AccessEditor’s ChoiceReview

Systematic Literature Review Predictive Maintenance Solutions for SMEs from the Last Decade

by Sepideh Hassankhani Dolatabadi and Ivana Budinska

Machines 2021, 9(9), 191; https://doi.org/10.3390/machines9090191 - 7 Sep 2021

Cited by 19 | Viewed by 7249

Abstract

Today, small- and medium-sized enterprises (SMEs) play an important role in the economy of societies. Although environmental factors, such as COVID-19, as well as non-environmental factors, such as equipment failure, make these industries more vulnerable, they can be minimized by better understanding the [...] Read more.

Today, small- and medium-sized enterprises (SMEs) play an important role in the economy of societies. Although environmental factors, such as COVID-19, as well as non-environmental factors, such as equipment failure, make these industries more vulnerable, they can be minimized by better understanding the concerns and threats these industries face. Only a few SMEs have the capacity to implement the innovative manufacturing technologies of Industry 4.0. The system must be highly adaptable to any equipment, have low costs, avoid the need of doing complex integrations and setups, and have future reliability due to the rapid growth of technology. The goal of this study was to provide an overview of past articles (2010–2020), highlighting the major expectations, requirements, and challenges for SMEs regarding the implementation of predictive maintenance (PdM). The proposed solutions to meet these expectations, requirements, and challenges are discussed. In general, in this study, we attempted to overcome the challenges and limitations of using smart manufacturing—PdM, in particular—in small- and medium-sized enterprises by summarizing the solutions offered in different industries and with various conditions. Moreover, this literature review enables managers and stakeholders of organizations to find solutions from previous studies for a specific category, with consideration for their expectations and needs. This can be significantly helpful for small- and medium-sized organizations to save time due to time-consuming maintenance processes. Full article

(This article belongs to the Section Machines Testing and Maintenance)

► Show Figures

Figure 1

19 pages, 1186 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Development of a Methodology for Condition-Based Maintenance in a Large-Scale Application Field

by Marco Cocconcelli, Luca Capelli, Jacopo Cavalaglio Camargo Molano and Davide Borghi

Machines 2018, 6(2), 17; https://doi.org/10.3390/machines6020017 - 16 Apr 2018

Cited by 18 | Viewed by 7125

Abstract

This paper describes a methodology, developed by the authors, for condition monitoring and diagnostics of several critical components in the large-scale applications with machines. For industry, the main target of condition monitoring is to prevent the machine stopping suddenly and thus avoid economic [...] Read more.

This paper describes a methodology, developed by the authors, for condition monitoring and diagnostics of several critical components in the large-scale applications with machines. For industry, the main target of condition monitoring is to prevent the machine stopping suddenly and thus avoid economic losses due to lack of production. Once the target is reached at a local level, usually through an R&D project, the extension to a large-scale market gives rise to new goals, such as low computational costs for analysis, easily interpretable results by local technicians, collection of data from worldwide machine installations, and the development of historical datasets to improve methodology, etc. This paper details an approach to condition monitoring, developed together with a multinational corporation, that covers all the critical points mentioned above. Full article

(This article belongs to the Special Issue Machinery Condition Monitoring and Industrial Analytics)

► Show Figures

Figure 1

23 pages, 1232 KiB

Open AccessEditor’s ChoiceArticle

Optimal Design of Axial Flux Permanent Magnet Motors for Ship RIM-Driven Thruster

by Hichem Ouldhamrane, Jean-Frédéric Charpentier, Farid Khoucha, Abdelhalim Zaoui, Yahia Achour and Mohamed Benbouzid

Machines 2022, 10(10), 932; https://doi.org/10.3390/machines10100932 - 13 Oct 2022

Cited by 8 | Viewed by 6982

Abstract

This paper deals with the design and optimization of a 2.1 MW rim-driven electric thruster for ship propulsion. For this purpose, a double stator ironless rotor axial flux permanent magnet (AFPM) motor is considered as the propulsion motor. The analytical model of the [...] Read more.

This paper deals with the design and optimization of a 2.1 MW rim-driven electric thruster for ship propulsion. For this purpose, a double stator ironless rotor axial flux permanent magnet (AFPM) motor is considered as the propulsion motor. The analytical model of the selected AFPM motor is presented. The magnetic field in the AFPM machine is calculated using the 3D magnetic charge concept in combination with image theory and permeance functions to take into account the stator slotting effects, and a simple thermal model is used to evaluate the heat dissipation capabilities of the machine and the thermal dependence of the main electromagnetic losses. To optimally design the AFPM, an optimization process based on genetic algorithms is applied to minimize the cost of the active motor materials. An appropriate objective function has been constructed, and different constraints related to the main electrical, geometrical, and mechanical parameters have been taken into account. The achieved results are compared with the performance of a podded radial flux permanent magnet (RFPM) motor, which is considered a reference propulsion motor. The obtained results show a fairly satisfactory improvement in the cost and masses of the active motor materials. Finally, the accuracy of the obtained optimum solution is validated by performing 3D finite element analysis (3D-FEA) simulations. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Electrical Machines and Drives)

► Show Figures

Figure 1

27 pages, 8982 KiB

Open AccessEditor’s ChoiceArticle

Probabilistic Condition Monitoring of Azimuth Thrusters Based on Acceleration Measurements

by Riku-Pekka Nikula, Mika Ruusunen, Joni Keski-Rahkonen, Lars Saarinen and Fredrik Fagerholm

Machines 2021, 9(2), 39; https://doi.org/10.3390/machines9020039 - 10 Feb 2021

Cited by 7 | Viewed by 6953

Abstract

Drill ships and offshore rigs use azimuth thrusters for propulsion, maneuvering and steering, attitude control and dynamic positioning activities. The versatile operating modes and the challenging marine environment create demand for flexible and practical condition monitoring solutions onboard. This study introduces a condition [...] Read more.

Drill ships and offshore rigs use azimuth thrusters for propulsion, maneuvering and steering, attitude control and dynamic positioning activities. The versatile operating modes and the challenging marine environment create demand for flexible and practical condition monitoring solutions onboard. This study introduces a condition monitoring algorithm using acceleration and shaft speed data to detect anomalies that give information on the defects in the driveline components of the thrusters. Statistical features of vibration are predicted with linear regression models and the residuals are then monitored relative to multivariate normal distributions. The method includes an automated shaft speed selection approach that identifies the normal distributed operational areas from the training data based on the residuals. During monitoring, the squared Mahalanobis distance to the identified distributions is calculated in the defined shaft speed ranges, providing information on the thruster condition. The performance of the method was validated based on data from two operating thrusters and compared with reference classifiers. The results suggest that the method could detect changes in the condition of the thrusters during online monitoring. Moreover, it had high accuracy in the bearing condition related binary classification tests. In conclusion, the algorithm has practical properties that exhibit suitability for online application. Full article

► Show Figures

Figure 1

22 pages, 4464 KiB

Open AccessEditor’s ChoiceArticle

AI-Based Posture Control Algorithm for a 7-DOF Robot Manipulator

by Cheonghwa Lee and Dawn An

Machines 2022, 10(8), 651; https://doi.org/10.3390/machines10080651 - 4 Aug 2022

Cited by 10 | Viewed by 6729

Abstract

With the rapid development of artificial intelligence (AI) technology and an increasing demand for redundant robotic systems, robot control systems are becoming increasingly complex. Although forward kinematics (FK) and inverse kinematics (IK) equations have been used as basic and perfect solutions for robot [...] Read more.

With the rapid development of artificial intelligence (AI) technology and an increasing demand for redundant robotic systems, robot control systems are becoming increasingly complex. Although forward kinematics (FK) and inverse kinematics (IK) equations have been used as basic and perfect solutions for robot posture control, both equations have a significant drawback. When a robotic system is highly nonlinear, it is difficult or impossible to derive both the equations. In this paper, we propose a new method that can replace both the FK and IK equations of a seven-degrees-of-freedom (7-DOF) robot manipulator. This method is based on reinforcement learning (RL) and artificial neural networks (ANN) for supervised learning (SL). RL was used to acquire training datasets consisting of six posture data in Cartesian space and seven motor angle data in joint space. The ANN is used to make the discrete training data continuous, which implies that the trained ANN infers any new data. Qualitative and quantitative evaluations of the proposed method were performed through computer simulation. The results show that the proposed method is sufficient to control the robot manipulator as efficiently as the IK equation. Full article

(This article belongs to the Special Issue Advanced Control Theory with Applications in Intelligent Machines)

► Show Figures

Figure 1

18 pages, 6540 KiB

Open AccessEditor’s ChoiceArticle

Designing a Low-Cost Mechatronic Device for Semi-Automatic Saffron Harvesting

by Alessandro Rocco Denarda, Andrea Manuello Bertetto and Giuseppe Carbone

Machines 2021, 9(5), 94; https://doi.org/10.3390/machines9050094 - 9 May 2021

Cited by 5 | Viewed by 6684

Abstract

This paper addresses the design of a novel mechatronic device for saffron harvesting. The main proposed challenge consists of proposing a new paradigm for semi-automatic harvesting of saffron flowers. The proposed novel solution is designed for being easily portable with user-friendly and cost-oriented [...] Read more.

This paper addresses the design of a novel mechatronic device for saffron harvesting. The main proposed challenge consists of proposing a new paradigm for semi-automatic harvesting of saffron flowers. The proposed novel solution is designed for being easily portable with user-friendly and cost-oriented features and with a fully electric battery-powered actuation. A preliminary concept design has been proposed as based on a specific novel cam mechanism in combination with an elastic spring for fulfilling the detachment of the flowers from their stems. Numerical calculations and simulations have been carried out to complete the full design of a proof-of-concept prototype. Preliminary experimental tests have been carried out to demonstrate the engineering feasibility and effectiveness of the proposed design solutions, whose concept has been submitted for patenting. Full article

(This article belongs to the Special Issue Intelligent Machines and Control Systems)

► Show Figures

Figure 1

19 pages, 8970 KiB

Open AccessEditor’s ChoiceArticle

Motion Planning and Control of Redundant Manipulators for Dynamical Obstacle Avoidance

by Giacomo Palmieri and Cecilia Scoccia

Machines 2021, 9(6), 121; https://doi.org/10.3390/machines9060121 - 18 Jun 2021

Cited by 49 | Viewed by 6652

Abstract

This paper presents a framework for the motion planning and control of redundant manipulators with the added task of collision avoidance. The algorithms that were previously studied and tested by the authors for planar cases are here extended to full mobility redundant manipulators [...] Read more.

This paper presents a framework for the motion planning and control of redundant manipulators with the added task of collision avoidance. The algorithms that were previously studied and tested by the authors for planar cases are here extended to full mobility redundant manipulators operating in a three-dimensional workspace. The control strategy consists of a combination of off-line path planning algorithms with on-line motion control. The path planning algorithm is used to generate trajectories able to avoid fixed obstacles detected before the robot starts to move; this is based on the potential fields method combined with a smoothing interpolation that exploits Bézier curves. The on-line motion control is designed to compensate for the motion of the obstacles and to avoid collisions along the kinematic chain of the manipulator; this is realized using a velocity control law based on the null space method for redundancy control. Furthermore, an additional term of the control law is introduced which takes into account the speed of the obstacles, as well as their position. In order to test the algorithms, a set of simulations are presented: the redundant collaborative robot KUKA LBR iiwa is controlled in different cases, where fixed or dynamic obstacles interfere with its motion. The simulated data show that the proposed method for the smoothing of the trajectory can give a reduction of the angular accelerations of the motors of the order of

90 %

, with an increase of less than

15 %

of the calculation time. Furthermore, the dependence of the on-line control law on the speed of the obstacle can lead to reductions in the maximum speed and acceleration of the joints of approximately

50 %

and

80 %

, respectively, without significantly increasing the computational effort that is compatible for transferability to a real system. Full article

(This article belongs to the Special Issue Advances of Japanese Machine Design)

► Show Figures

Figure 1

36 pages, 16046 KiB

Open AccessEditor’s ChoiceReview

Vibration Image Representations for Fault Diagnosis of Rotating Machines: A Review

by Hosameldin Osman Abdallah Ahmed and Asoke Kumar Nandi

Machines 2022, 10(12), 1113; https://doi.org/10.3390/machines10121113 - 23 Nov 2022

Cited by 23 | Viewed by 6472

Abstract

Rotating machine vibration signals typically represent a large collection of responses from various sources in a machine, along with some background noise. This makes it challenging to precisely utilise the collected vibration signals for machine fault diagnosis. Much of the research in this [...] Read more.

Rotating machine vibration signals typically represent a large collection of responses from various sources in a machine, along with some background noise. This makes it challenging to precisely utilise the collected vibration signals for machine fault diagnosis. Much of the research in this area has focused on computing certain features of the original vibration signal in the time domain, frequency domain, and time–frequency domain, which can sufficiently describe the signal in essence. Yet, computing useful features from noisy fault signals, including measurement errors, needs expert prior knowledge and human labour. The past two decades have seen rapid developments in the application of feature-learning or representation-learning techniques that can automatically learn representations of time series vibration datasets to address this problem. These include supervised learning techniques with known data classes and unsupervised learning or clustering techniques with data classes or class boundaries that are not obtainable. More recent developments in the field of computer vision have led to a renewed interest in transforming the 1D time series vibration signal into a 2D image, which can often offer discriminative descriptions of vibration signals. Several forms of features can be learned from the vibration images, including shape, colour, texture, pixel intensity, etc. Given its high performance in fault diagnosis, the image representation of vibration signals is receiving growing attention from researchers. In this paper, we review the works associated with vibration image representation-based fault detection and diagnosis for rotating machines in order to chart the progress in this field. We present the first comprehensive survey of this topic by summarising and categorising existing vibration image representation techniques based on their characteristics and the processing domain of the vibration signal. In addition, we also analyse the application of these techniques in rotating machine fault detection and classification. Finally, we briefly outline future research directions based on the reviewed works. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Fault Diagnosis and Prognosis)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Editor’s Choice Articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI