Machines

21 pages, 4725 KB

Open AccessArticle

A Novel Open Circuit Fault Diagnosis for a Modular Multilevel Converter with Modal Time-Frequency Diagram and FFT-CNN-BIGRU Attention

by Ziyuan Zhai, Ning Wang, Siran Lu, Bo Zhou and Lei Guo

Machines 2025, 13(6), 533; https://doi.org/10.3390/machines13060533 - 19 Jun 2025

Viewed by 320

Abstract

Fault diagnosis is one of the most important issues for a modular multilevel converter (MMC). However, conventional solutions are deficient in two aspects. Firstly, they lack the necessary feature information. Secondly, they are incapable of performing open-circuit fault diagnosis of the modular multilevel [...] Read more.

Fault diagnosis is one of the most important issues for a modular multilevel converter (MMC). However, conventional solutions are deficient in two aspects. Firstly, they lack the necessary feature information. Secondly, they are incapable of performing open-circuit fault diagnosis of the modular multilevel converter with the requisite degree of accuracy. To solve this problem, an intelligent diagnosis method is proposed to integrate the modal time–frequency diagram and FFT-CNN-BiGRU-Attention. By selecting the phase current and bridge arm voltage as the core fault parameters, the particle swarm algorithm is used to optimize the Variational Modal Decomposition parameters, and the fault signal is decomposed and reconstructed into sensitive feature components. The reconstructed signals are further transformed into modal time–frequency diagrams via continuous wavelet transform to fully retain the time–frequency domain features. In the model construction stage, the frequency–domain features are first extracted using the fast Fourier transform (FFT), and the local patterns are captured through a combination with a convolutional neural network; subsequently, the timing correlations are analyzed using bidirectional gated loop cells, and the Attention Mechanism is introduced to strengthen the key features. Simulations show that the proposed method achieves 98.63% accuracy in locating faulty insulated gate bipolar transistors (IGBTs) in the sub-module, with second-level real-time response capability. Compared with the recently published scheme, it maintains stable performance under complex working conditions such as noise interference and data imbalances, showing stronger robustness and practical value. This study provides a new idea for the intelligent operation and maintenance of power electronic devices, which can be extended to the fault diagnosis of other power equipment in the future. Full article

(This article belongs to the Section Electromechanical Energy Conversion Systems)

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19 pages, 11712 KB

Open AccessArticle

A Data-Driven Approach for Energy Consumption Modeling and Optimization of Welding Robot Systems

by Minling Pan, Bingqi Jia, Lei Zhang, Haihong Pan and Lin Chen

Machines 2025, 13(6), 532; https://doi.org/10.3390/machines13060532 - 18 Jun 2025

Cited by 1 | Viewed by 419

Abstract

Welding robots play a crucial role in manufacturing industries, where minimizing energy consumption (EC) is increasingly important for enhancing efficiency and reducing operational costs. This study presents a data-driven approach to model and optimize EC in welding robot systems, utilizing a dataset generated [...] Read more.

Welding robots play a crucial role in manufacturing industries, where minimizing energy consumption (EC) is increasingly important for enhancing efficiency and reducing operational costs. This study presents a data-driven approach to model and optimize EC in welding robot systems, utilizing a dataset generated from real-world measurements of robot EC during various motions and integrated with trajectory data. A predictive model was developed using an extreme gradient boosting (XGBoost) regression technique focused on joint torque data, which achieved a mean absolute percentage error (MAPE) of 1.86%. Furthermore, trajectory optimization was achieved by adjusting the spatial position of the workpiece, effectively reducing EC. To solve the optimization problem, an improved whale optimization algorithm (IWOA) was employed. Experimental validations with a welding robot demonstrate that the proposed method not only accurately predicted EC with a MAPE of 2.66% but also reduced the robot system’s EC by 6.72%, outperforming the traditional method focused solely on joint motor EC, which achieved a 4.08% reduction. These results confirm the efficacy of the proposed approach, underscoring its potential for broad application in robotic systems to achieve significant energy savings. Full article

(This article belongs to the Section Advanced Manufacturing)

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23 pages, 4810 KB

Open AccessArticle

Optimization Design and Dynamic Characteristics Analysis of Self-Responsive Anti-Falling Device for Inclined Shaft TBMs

by Han Peng, Can Yang, Linjian Shangguan, Lianhui Jia, Bing Li, Chuang Xu and Wenjuan Yang

Machines 2025, 13(6), 531; https://doi.org/10.3390/machines13060531 - 18 Jun 2025

Viewed by 419

Abstract

To address the frequent failure of anti-falling devices in inclined shaft tunnel boring machines caused by cyclic loading and fatigue during construction, this study proposes an optimized self-responsive anti-falling device design. Based on the operational conditions of the “Tianyue” tunnel boring machine, a [...] Read more.

To address the frequent failure of anti-falling devices in inclined shaft tunnel boring machines caused by cyclic loading and fatigue during construction, this study proposes an optimized self-responsive anti-falling device design. Based on the operational conditions of the “Tianyue” tunnel boring machine, a three-dimensional model was constructed using SolidWorks. Finite element static analysis was employed to validate structural integrity, revealing a maximum stress of 461.19 MPa with a safety factor of 1.71. Explicit dynamic simulations further demonstrated the dynamic penetration process of propellant-driven telescopic columns through concrete lining walls, achieving a penetration depth exceeding 500 mm. The results demonstrate that the device can respond to falling signals within 12 ms and activate mechanical locking. The Q690D steel structure exhibits a deformation of 5.543 mm with favorable stress distribution, meeting engineering safety requirements. The energy release characteristics of trinitrotoluene propellant and material compatibility were systematically verified. Compared to conventional hydraulic support systems, this design offers significant improvements in response speed, maintenance cost reduction, and environmental adaptability, providing an innovative solution for fall protection in complex geological environments. Full article

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

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23 pages, 5700 KB

Open AccessArticle

Near-Zero Parasitic Shift Rectilinear Flexure Stages Based on Coupled n-RRR Planar Parallel Mechanisms

by Loïc Tissot-Daguette, Célestin Vallat, Marijn Nijenhuis, Florent Cosandier and Simon Henein

Machines 2025, 13(6), 530; https://doi.org/10.3390/machines13060530 - 18 Jun 2025

Cited by 1 | Viewed by 441

Abstract

Flexure-based linear stages have become prevalent in precision engineering; however, most designs suffer from parasitic shifts that degrade positioning accuracy. Conventional solutions to mitigate these parasitic motions often compromise support stiffness, reduce motion range, and increase structural complexity. This study presents a novel [...] Read more.

Flexure-based linear stages have become prevalent in precision engineering; however, most designs suffer from parasitic shifts that degrade positioning accuracy. Conventional solutions to mitigate these parasitic motions often compromise support stiffness, reduce motion range, and increase structural complexity. This study presents a novel family of flexure-based rectilinear-motion stages using coupled n-RRR planar parallel mechanisms, achieving extremely low parasitic shifts while addressing the forementioned limitations. Four design variants are selected and analyzed via Finite Element Method (FEM) simulations, evaluating parasitic shifts, stroke, and support stiffness. The most precise configuration, a 4-RRR rectilinear stage having kinematic chains coupled via two Watt linkages, exhibits a lateral shift smaller than 0.258 µm and an in-plane parasitic rotation smaller than 12.6 µrad over a 12 mm stroke. Experimental validation using a POM prototype confirms the high positioning precision and support stiffness properties. In addition, a silicon prototype incorporating thermally preloaded buckling beams is investigated to reduce its translational stiffness. Experimental results show a translational stiffness reduction of 98% in the monostable configuration and 112% in the bistable configuration (i.e., negative stiffness), without support stiffness reduction. These results highlight the potential of the proposed mechanisms for a wide range of precision applications, offering a scalable and high-accuracy solution for micro- and nano-positioning systems. Full article

(This article belongs to the Special Issue Recent Developments in Machine Design, Automation and Robotics)

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16 pages, 4443 KB

Open AccessArticle

Factors Affecting Mechanical Properties of Impulse Friction Stir Welded AA2024-T351 Under Static and Cyclic Loads

by Iuliia Morozova, Aleksei Obrosov, Anton Naumov, Vesselin Michailov and Nikolay Doynov

Machines 2025, 13(6), 529; https://doi.org/10.3390/machines13060529 - 17 Jun 2025

Viewed by 289

Abstract

This study investigates the factors affecting the mechanical performance of conventional and impulse friction stir welded (FSW and IFSW) AA2024-T351 joints under static and cyclic loading. Emphasis is placed on the influence of fracture-inducing features such as oxide inclusions, constituent particle distributions, crystallographic [...] Read more.

This study investigates the factors affecting the mechanical performance of conventional and impulse friction stir welded (FSW and IFSW) AA2024-T351 joints under static and cyclic loading. Emphasis is placed on the influence of fracture-inducing features such as oxide inclusions, constituent particle distributions, crystallographic texture, and precipitation state. A series of IFSW welds produced at varying impulse parameters were compared to conventional FSW welds in terms of microhardness, tensile strength, fatigue life, and Taylor factor distribution. IFSW joints demonstrated a significant improvement in tensile strength and elongation, particularly at higher impulse frequencies. Enhanced material mixing due to the reciprocating tool motion in IFSW resulted in finer particle distribution, more favorable crystallographic texture, and reduced weld pitch, all contributing to increased ductility and strength. Fractographic analyses revealed that fatigue failures primarily initiated in the stir zone, typically at unplasticized metallic inclusions. However, IFSW joints displayed longer fatigue lives, particularly when impulse parameters were optimized. These findings underline the complex interplay of microstructural and textural factors in determining weld performance, highlighting IFSW as a promising technique for enhancing the durability of high-strength aluminum welds. Full article

(This article belongs to the Section Advanced Manufacturing)

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24 pages, 3638 KB

Open AccessArticle

Digital Control of an Inverted Pendulum Using a Velocity-Controlled Robot

by Marco Costanzo, Raffaele Mazza and Ciro Natale

Machines 2025, 13(6), 528; https://doi.org/10.3390/machines13060528 - 17 Jun 2025

Viewed by 511

Abstract

This research article tackles the control problem of an inverted pendulum, also known as the Furuta pendulum, mounted on a velocity-controlled robot manipulator in two configurations: the rotary pendulum and the translational pendulum. Differently from most of the existing control architectures where the [...] Read more.

This research article tackles the control problem of an inverted pendulum, also known as the Furuta pendulum, mounted on a velocity-controlled robot manipulator in two configurations: the rotary pendulum and the translational pendulum. Differently from most of the existing control architectures where the motor actuating the pendulum motion is torque-controlled, the proposed control architecture exploits the inner velocity loop usually available on industrial robots, thus easing the implementation of an inverted pendulum. Another aspect investigated in this paper and mostly overlooked in the literature is the digital implementation of the control and, specifically, the latency introduced by the digital controller. The proposed control solution explicitly models such effects in the control design phase, improving the closed-loop performance. The additional novelty introduced by this paper is the friction compensation that is essential in the swing-up phase of the inverted pendulum, whereas classical control strategies for the nonlinear swing-up usually neglect this effect, and their solutions lead to control failures in practical systems. This paper presents detailed modeling and experimental identification phases followed by the control design of both the nonlinear swing-up algorithm and the linear stabilization controller, both experimentally validated on a Meca500 robotic arm controlled via an EtherCAT communication protocol by a mini PC featuring a Xenomai real-time operating system. The overall system showcases the potential of high-performance digital control systems in industrial robotic applications. Full article

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

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21 pages, 3178 KB

Open AccessArticle

The Prediction of Sound Insulation for the Front Wall of Pure Electric Vehicles Based on AFWL-CNN

by Yan Ma, Jie Yan, Jianjiao Deng, Xiaona Liu, Dianlong Pan, Jingjing Wang and Ping Liu

Machines 2025, 13(6), 527; https://doi.org/10.3390/machines13060527 - 17 Jun 2025

Viewed by 295

Abstract

The front wall acoustic package system plays a crucial role in automotive design, and its performance directly affects the quality and comfort of the interior noise. In response to the limitations of traditional experimental and simulation methods in terms of accuracy and efficiency, [...] Read more.

The front wall acoustic package system plays a crucial role in automotive design, and its performance directly affects the quality and comfort of the interior noise. In response to the limitations of traditional experimental and simulation methods in terms of accuracy and efficiency, this paper proposes a convolutional neural network (AFWL-CNN) based on adaptive weighted feature learning. Using a data-driven method, the sound insulation performance of the entire vehicle’s front wall acoustic package system was predicted and analyzed based on the original parameters of the front wall acoustic package components, thereby effectively avoiding the shortcomings of traditional TPA and CAE methods. Compared to the traditional CNN model (RMSE = 0.042, MAE = 3.89 dB, I-TIME = 13.67 s), the RMSE of the proposed AFWL-CNN model was optimized to 0.031 (approximately 26.19% improvement), the mean absolute error (MAE) was reduced to 2.84 dB (approximately 26.99% improvement), and the inference time (I-TIME) increased to 17.16 s (approximately 25.53% increase). Although the inference time of the AFWL-CNN model increased by 25.53% compared to the CNN model, it achieved a more significant improvement in prediction accuracy, demonstrating a reasonable trade-off between efficiency and accuracy. Compared to AFWL-LSTM (RMSE = 0.039, MAE = 3.35 dB, I-TIME = 19.81 s), LSTM (RMSE = 0.044, MAE = 4.07 dB, I-TIME = 16.71 s), and CNN–Transformer (RMSE = 0.040, MAE = 3.74 dB, I-TIME = 19.55 s) models, the AFWL-CNN model demonstrated the highest prediction accuracy among the five models. Furthermore, the proposed method was verified using the front wall acoustic package data of a new car model, and the results showed the effectiveness and reliability of this method in predicting the acoustic package performance of the front wall system. This study provides a powerful tool for fast and accurate performance prediction of automotive front acoustic packages, significantly improving design efficiency and providing a data-driven framework that can be used to solve other vehicle noise problems. Full article

(This article belongs to the Special Issue Intelligent Applications in Mechanical Engineering)

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26 pages, 1863 KB

Open AccessArticle

Robotic Positioning Accuracy Enhancement via Memory Red Billed Blue Magpie Optimizer and Adaptive Momentum PSO Tuned Graph Neural Network

by Jian Liu, Xiaona Huang, Yonghong Deng, Canjun Xiao and Zhibin Li

Machines 2025, 13(6), 526; https://doi.org/10.3390/machines13060526 - 16 Jun 2025

Viewed by 366

Abstract

Robotic positioning accuracy is critically affected by both geometric and non-geometric errors. To address this dual error issue comprehensively, this paper proposes a novel two-stage compensation framework. First, a Memory based red billed blue magpie optimizer (MRBMO) is employed to identify and compensate [...] Read more.

Robotic positioning accuracy is critically affected by both geometric and non-geometric errors. To address this dual error issue comprehensively, this paper proposes a novel two-stage compensation framework. First, a Memory based red billed blue magpie optimizer (MRBMO) is employed to identify and compensate for geometric errors by optimizing the geometric parameters based on end-effector observations. This memory-guided evolutionary mechanism effectively enhances the convergence accuracy and stability of the geometric calibration process. Second, a tuned graph neural network (AMPSO-GNN) is developed to model and compensate for non-geometric errors, such as cable deformation, thermal drift, and control imperfections. The GNN architecture captures the topological structure of the robotic system, while the adaptive momentum PSO dynamically optimizes the network’s hyperparameters for improved generalization. Experimental results on a six-axis industrial robot demonstrate that the proposed method significantly reduces residual positioning errors, achieving higher accuracy compared to conventional calibration and compensation strategies. This dual-compensation approach offers a scalable and robust solution for precision-critical robotic applications. Full article

(This article belongs to the Special Issue Robotic Intelligence Development of AI in Robot Perception, Learning, and Decision)

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20 pages, 1649 KB

Open AccessArticle

Direct Force Control Technology for Longitudinal Trajectory of Receiver Aircraft Based on Incremental Nonlinear Dynamic Inversion and Active Disturbance Rejection Controller

by Xin Bao, Yan Li and Zhong Wang

Machines 2025, 13(6), 525; https://doi.org/10.3390/machines13060525 - 16 Jun 2025

Viewed by 355

Abstract

Aiming at the requirements of rapidity, high precision, and robustness for the longitudinal trajectory control of the receiver aircraft in autonomous aerial refueling, a direct lift control (DLC) strategy that integrates incremental nonlinear dynamic inversion (INDI) and nonlinear extended state observer (NESO) is [...] Read more.

Aiming at the requirements of rapidity, high precision, and robustness for the longitudinal trajectory control of the receiver aircraft in autonomous aerial refueling, a direct lift control (DLC) strategy that integrates incremental nonlinear dynamic inversion (INDI) and nonlinear extended state observer (NESO) is proposed. First, a control strategy for generating direct lift through the coordinated action of the flaperons and elevators is presented, and a longitudinal dynamics model is established. Secondly, based on the INDI and DLC methods, the rapid tracking and control of altitude are achieved. Finally, an NESO is designed. The observer gains are designed through the pole placement method and the robust optimization method to achieve the estimation of states such as airspeed, angle of attack, pitch rate, and pitch angle, as well as unknown force and moment disturbances. The estimated force and moment disturbances are used to implement the active disturbance rejection control. Simulation results show that the strategy has no altitude tracking error under normal operating conditions, and the altitude tracking error is less than 0.2 m under typical disturbance conditions, indicating high control accuracy. Under disturbance conditions, the estimation errors of true airspeed, angle of attack, pitch angle, and pitch angular velocity are less than 0.3 m/s, 0.12°, 0.1°, and 0.2°/s, respectively, demonstrating the high-precision estimation capability of the observer. The NESO exhibits high accuracy in state estimation, the rudder deflection is smooth, and the anti-disturbance capability is significantly better than traditional methods, providing an engineered solution for the longitudinal control of the receiver aircraft. Full article

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

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23 pages, 2753 KB

Open AccessArticle

Three-Dimensional Stability Lobe Construction for Face Milling of Thin-Wall Components with Position-Dependent Dynamics and Process Damping

by Jinjie Jia, Lixue Chen, Wenyuan Song and Mingcong Huang

Machines 2025, 13(6), 524; https://doi.org/10.3390/machines13060524 - 16 Jun 2025

Viewed by 350

Abstract

Titanium alloy thin-walled components are extensively used in aerospace engineering, yet their milling stability remains a persistent challenge due to vibration-induced surface anomalies. This study develops an advanced dynamic model for the face milling of titanium alloy thin-walled structures, systematically integrating axial cutting [...] Read more.

Titanium alloy thin-walled components are extensively used in aerospace engineering, yet their milling stability remains a persistent challenge due to vibration-induced surface anomalies. This study develops an advanced dynamic model for the face milling of titanium alloy thin-walled structures, systematically integrating axial cutting dynamics with regenerative chatter mechanisms and nonlinear process damping phenomena. The proposed framework crucially accounts for time-varying tool–workpiece interactions and damping characteristics, enabling precise characterization of stability transitions under dynamically varying axial immersion conditions. A novel extension of the semi-discretization method is implemented to resolve multi-parameter stability solutions, establishing a computational paradigm for generating three-dimensional stability lobe diagrams (3D SLDs) that concurrently evaluate spindle speed, cutting position, and the axial depth of a cut. Comprehensive experimental validation through time-domain chatter tests demonstrates remarkable consistency between theoretical predictions and empirical chatter thresholds. The results reveal that process damping significantly suppresses chatter at low spindle speeds, while regenerative effects dominate instability at higher speeds. This work provides a systematic framework for optimizing machining parameters in thin-walled component manufacturing, offering improved accuracy in stability prediction compared to traditional two-dimensional SLD methods. The proposed methodology bridges the gap between theoretical dynamics and industrial applications, facilitating efficient high-precision machining of titanium alloys. Full article

(This article belongs to the Special Issue Machine Tools for Precision Machining: Design, Control and Prospects)

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24 pages, 4703 KB

Open AccessArticle

Deep Reinforcement Learning-Based Active Disturbance Rejection Control for Trajectory Tracking of Autonomous Ground Electric Vehicles

by Xianjian Jin, Huaizhen Lv, Yinchen Tao, Jianning Lu, Jianbo Lv and Nonsly Valerienne Opinat Ikiela

Machines 2025, 13(6), 523; https://doi.org/10.3390/machines13060523 - 16 Jun 2025

Viewed by 604

Abstract

This paper proposes an integrated control framework for improving the trajectory tracking performance of autonomous ground electric vehicles (AGEVs) under complex disturbances, including parameter uncertainties, and environmental changes. The framework integrates active disturbance rejection control (ADRC) for real-time disturbance estimation and compensation with [...] Read more.

This paper proposes an integrated control framework for improving the trajectory tracking performance of autonomous ground electric vehicles (AGEVs) under complex disturbances, including parameter uncertainties, and environmental changes. The framework integrates active disturbance rejection control (ADRC) for real-time disturbance estimation and compensation with a deep deterministic policy gradient (DDPG)-based deep reinforcement learning (DRL) algorithm for dynamic optimization of controller parameters to improve tracking accuracy and robustness. More specifically, it combines the Line of Sight (LOS) guidance rate with ADRC, proves the stability of LOS through the Lyapunov law, and designs a yaw angle controller, using the extended state observer to reduce the impact of disturbances on tracking accuracy. And the approach also addresses the nonlinear vehicle dynamic characteristics of AGEVs while mitigating internal and external disturbances by leveraging the inherent decoupling capability of ADRC and the data-driven parameter adaptation capability of DDPG. Simulations via CarSim/Simulink are carried out to validate the controller performance in serpentine and double-lane-change maneuvers. The simulation results show that the proposed framework outperforms traditional control strategies with significant improvements in lateral tracking accuracy, yaw stability, and sideslip angle suppression. Full article

(This article belongs to the Special Issue Intelligent Sensing, Planning and Control for Autonomous Ground Vehicles)

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21 pages, 4416 KB

Open AccessArticle

A Generic Modeling Method of Multi-Modal/Multi-Layer Digital Twins for the Remote Monitoring and Intelligent Maintenance of Industrial Equipment

by Maolin Yang, Yifan Cao, Siwei Shangguan, Xin Chen and Pingyu Jiang

Machines 2025, 13(6), 522; https://doi.org/10.3390/machines13060522 - 16 Jun 2025

Viewed by 494

Abstract

Digital twin (DT) is a useful tool for the remote monitoring, analyzing, controlling, etc. of industrial equipment in a harsh working environment unfriendly to human workers. Although much research has been devoted to DT modeling methods, there are still limitations. For example, (1) [...] Read more.

Digital twin (DT) is a useful tool for the remote monitoring, analyzing, controlling, etc. of industrial equipment in a harsh working environment unfriendly to human workers. Although much research has been devoted to DT modeling methods, there are still limitations. For example, (1) existing DT modeling methods are usually focused on specific types of equipment rather than being generally applicable to different types of equipment and requirements. (2) Existing DT models usually emphasize working condition monitoring and have relatively limited capability for modeling the operation and maintenance mechanism of the equipment for further decision making. (3) How to integrate artificial intelligence algorithms into DT models still requires further exploration. In this regard, a systematic and general DT modeling method is proposed for the remote monitoring and intelligent maintenance of industrial equipment. The DT model contains a multi-modal digital model, a multi-layer status model, and an intelligent interaction model driven by a kind of human-readable/computer-deployable event-state knowledge graph. Using the model, the dynamic workflows, working mechanisms, working status, workpiece logistics, monitoring data, and intelligent functions, etc., during the remote monitoring and maintenance of industrial equipment can be realized. The model was verified through three different DT modeling scenarios of a robot-based carbon block polishing processing line. Full article

(This article belongs to the Special Issue Intelligent Fault Detection and Diagnosis in Condition-Based Maintenance)

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51 pages, 13105 KB

Open AccessEditor’s ChoiceReview

Current Status and Trends of Wall-Climbing Robots Research

by Shengjie Lou, Zhong Wei, Jinlin Guo, Yu Ding, Jia Liu and Aiguo Song

Machines 2025, 13(6), 521; https://doi.org/10.3390/machines13060521 - 15 Jun 2025

Viewed by 1725

Abstract

A wall-climbing robot is an electromechanical device capable of autonomous or semi-autonomous movement on intricate vertical surfaces (e.g., walls, glass facades, pipelines, ceilings, etc.), typically incorporating sensing and adaptive control systems to enhance task performance. It is designed to perform tasks such as [...] Read more.

A wall-climbing robot is an electromechanical device capable of autonomous or semi-autonomous movement on intricate vertical surfaces (e.g., walls, glass facades, pipelines, ceilings, etc.), typically incorporating sensing and adaptive control systems to enhance task performance. It is designed to perform tasks such as inspection, cleaning, maintenance, and rescue while maintaining stable adhesion to the surface. Its applications span various sectors, including industrial maintenance, marine engineering, and aerospace manufacturing. This paper provides a systematic review of the physical principles and scalability of various attachment methods used in wall-climbing robots, with a focus on the applicability and limitations of different attachment mechanisms in relation to robot size and structural design. For specific attachment methods, the design and compatibility of motion and attachment mechanisms are analyzed to offer design guidance for wall-climbing robots tailored to different operational tasks. Additionally, this paper reviews localization and path planning methods for wall-climbing robots, comparing graph search, sampling-based, and feedback-based algorithms to guide strategy selection across varying environments and tasks. Finally, this paper outlines future development trends in wall-climbing robots, including the diversification of locomotion mechanisms, hybridization of attachment systems, and advancements in intelligent localization and path planning. This work provides a comprehensive theoretical foundation and practical reference for the design and application of wall-climbing robots. Full article

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

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24 pages, 2289 KB

Open AccessArticle

Advanced Control Strategy for Induction Motors Using Dual SVM-PWM Inverters and MVT-Based Observer

by Omar Allag, Abdellah Kouzou, Meriem Allag, Ahmed Hafaifa, Jose Rodriguez and Mohamed Abdelrahem

Machines 2025, 13(6), 520; https://doi.org/10.3390/machines13060520 - 14 Jun 2025

Viewed by 502

Abstract

This paper introduces a novel field-oriented control (FOC) strategy for an open-end stator three-phase winding induction motor (OEW-TP-IM) using dual space vector modulation-pulse width modulation (SVM-PWM) inverters. This configuration reduces common mode voltage at the motor’s terminals, enhancing efficiency and reliability. The study [...] Read more.

This paper introduces a novel field-oriented control (FOC) strategy for an open-end stator three-phase winding induction motor (OEW-TP-IM) using dual space vector modulation-pulse width modulation (SVM-PWM) inverters. This configuration reduces common mode voltage at the motor’s terminals, enhancing efficiency and reliability. The study presents a backstepping control approach combined with a mean value theorem (MVT)-based observer to improve control accuracy and stability. Stability analysis of the backstepping controller for key control loops, including flux, speed, and currents, is conducted, achieving asymptotic stability as confirmed through Lyapunov’s methods. An advanced observer using sector nonlinearity (SNL) and time-varying parameters from convex theory is developed to manage state observer error dynamics effectively. Stability conditions, defined as linear matrix inequalities (LMIs), are solved using MATLAB R2016b to optimize the observer’s estimator gains. This approach simplifies system complexity by measuring only two line currents, enhancing responsiveness. Comprehensive simulations validate the system’s performance under various conditions, confirming its robustness and effectiveness. This strategy improves the operational dynamics of OEW-TP-IM machine and offers potential for broad industrial applications requiring precise and reliable motor control. Full article

(This article belongs to the Section Electromechanical Energy Conversion Systems)

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22 pages, 329 KB

Open AccessArticle

Comprehensive MILP Formulation and Solution for Simultaneous Scheduling of Machines and AGVs in a Partitioned Flexible Manufacturing System

by Cheng Zhuang, Jingbo Qu, Tianyu Wang, Liyong Lin, Youyi Bi and Mian Li

Machines 2025, 13(6), 519; https://doi.org/10.3390/machines13060519 - 13 Jun 2025

Viewed by 687

Abstract

This paper proposes a comprehensive Mixed-Integer Linear Programming (MILP) formulation for the simultaneous scheduling of machines and Automated Guided Vehicles (AGVs) within a partitioned Flexible Manufacturing System (FMS). The main objective is to numerically optimize the simultaneous scheduling of machines and AGVs while [...] Read more.

This paper proposes a comprehensive Mixed-Integer Linear Programming (MILP) formulation for the simultaneous scheduling of machines and Automated Guided Vehicles (AGVs) within a partitioned Flexible Manufacturing System (FMS). The main objective is to numerically optimize the simultaneous scheduling of machines and AGVs while considering various workshop layouts and operational constraints. Three different workshop layouts are analyzed, with varying numbers of machines in partitioned workshop areas A and B, to evaluate the performance and effectiveness of the proposed model. The model is tested in multiple scenarios that combine different layouts with varying numbers of workpieces, followed by an extension to consider dynamic initial conditions in a more generalized MILP framework. Results demonstrate that the proposed MILP formulation efficiently generates globally optimal solutions and consistently outperforms a greedy algorithm enhanced by A*-inspired heuristics. Although computationally intensive for large scenarios, the MILP’s optimal results serve as an exact benchmark for evaluating faster heuristic methods. In addition, the study provides practical insight into the integration of AGVs in modern manufacturing systems, paving the way for more flexible and efficient production planning. The findings of this research are expected to contribute to the development of advanced scheduling strategies in automated manufacturing systems. Full article

(This article belongs to the Special Issue Intelligent Sensing, Planning and Control for Autonomous Ground Vehicles)

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18 pages, 6386 KB

Open AccessArticle

Study on Steam Excitation Forces Induced by Tip Seal Leakage Flow in Steam Turbines

by Pan Li, Huan Wang, Haichao Peng, Heyong Si and Tieliu Jiang

Machines 2025, 13(6), 518; https://doi.org/10.3390/machines13060518 - 13 Jun 2025

Viewed by 384

Abstract

This study aims to elucidate the mechanisms by which tip seal leakage flow induces steam excitation, thereby enhancing the operational safety of steam turbines. Using numerical simulations, it investigates the detailed characteristics of the flow field in the turbine tip seal cavity. By [...] Read more.

This study aims to elucidate the mechanisms by which tip seal leakage flow induces steam excitation, thereby enhancing the operational safety of steam turbines. Using numerical simulations, it investigates the detailed characteristics of the flow field in the turbine tip seal cavity. By introducing Boundary Vorticity Flux (BVF) into the tip seal flow field, this research explores the relationship between leakage vortex structures in non-uniform flow fields at the blade tip and the resulting steam excitation forces. The results demonstrate that, during eccentric rotor operation, the extent and intensity of vortices within the seal cavity vary, lead to changes in the BVF distribution along the shroud surface, which in turn alter the tangential forces and induce variations in lateral excitation force at the blade tip. Additionally, the non-uniform flow in the tip seal clearance induces circumferential pressure variations across the shroud, leading to adjustments in radial excitation force at the blade tip. Full article

(This article belongs to the Section Turbomachinery)

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12 pages, 1700 KB

Open AccessArticle

Analysis of the Influence of Drill Tip Geometry on the Dry Drilling Process in CFRP Thermoset Laminate

by Francisco de A. Toti, Amilton J. C. de Freitas, José J. de Oliveira and Rita de Cássia M. Sales-Contini

Machines 2025, 13(6), 517; https://doi.org/10.3390/machines13060517 - 13 Jun 2025

Viewed by 430

Abstract

Carbon fibre reinforced composite (CFRP) laminates are widely used in high-tech industries. However, their assembly often requires a drilling process that can create defects. Therefore, studies on the drill tip angle have sought to minimize the surface area affected by these defects and [...] Read more.

Carbon fibre reinforced composite (CFRP) laminates are widely used in high-tech industries. However, their assembly often requires a drilling process that can create defects. Therefore, studies on the drill tip angle have sought to minimize the surface area affected by these defects and improve the internal hole quality. In this work, drilling was carried out under dry conditions at a constant cutting speed for four different feed rates in the epoxy–carbon-based thermosetting laminate (EPX-C). Two carbide drills with point angles of 118° and 140° were used. The results showed the occurrence of chipping-type delaminations on both the hole entry and exit surfaces, with the latter being more severely affected. The delamination factor values obtained indicated that the 118° drill performed better than the 140° drill. The results were also compared with those obtained in a previous study using drills with angles of 60° and 130°. Although the values were higher, they followed the same trend of reduction with increasing feed. In terms of surface finish, the average roughness (Ra) values obtained with the 140° drill were better at the lowest feed rate. Full article

(This article belongs to the Section Advanced Manufacturing)

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14 pages, 3831 KB

Open AccessArticle

Research on Online Non-Contact Test Device and Test Method for Bearing Stiffness of Electric Spindle

by Chuanhai Chen, Liang Zhang, Chunlei Hua, Zhifeng Liu, Qingyu Meng and Junze Shi

Machines 2025, 13(6), 516; https://doi.org/10.3390/machines13060516 - 13 Jun 2025

Viewed by 471

Abstract

To enable experimental research on the dynamic support stiffness of electric spindle bearings, the authors designed a magnetic non-contact excitation and test device that can test the support stiffness of electric spindle bearings under a rotating state. The device includes load excitation and [...] Read more.

To enable experimental research on the dynamic support stiffness of electric spindle bearings, the authors designed a magnetic non-contact excitation and test device that can test the support stiffness of electric spindle bearings under a rotating state. The device includes load excitation and displacement detection components, which can collect the load loading and displacement data of electric spindle bearings under machine state in real time. The radial and axial loads can be applied at the same time, and the displacement detection component adopts a high-precision displacement sensor, which can measure the displacement data generated by the electric spindle bearing under the action of the excitation component in real time. A magnetic loading method was proposed for testing the supporting stiffness of the front and rear bearings in electric spindles along the three orthogonal directions of radial X/Y and axial Z. According to the designed device and test method, the dynamic support stiffness of an electric spindle bearing in a vertical machining center is tested, and the variation trend of the bearing support stiffness under the combined action of axial load, radial load and rotational speed is analyzed. Full article

(This article belongs to the Section Advanced Manufacturing)

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18 pages, 2053 KB

Open AccessArticle

Optimization of Hybrid Machining of Nomex Honeycomb Structures: Effect of the CZ10 Tool and Ultrasonic Vibrations on the Cutting Process

by Oussama Beldi, Tarik Zarrouk, Ahmed Abbadi, Mohammed Nouari, Jamal-Eddine Salhi, Mohammed Abbadi and Mohamed Barboucha

Machines 2025, 13(6), 515; https://doi.org/10.3390/machines13060515 - 13 Jun 2025

Viewed by 448

Abstract

Machining Nomex honeycomb composite structures is crucial for manufacturing components that meet stringent industry requirements. However, the complex characteristics of this material require specialized machining techniques to avoid defects, ensure optimal surface quality, and preserve the integrity of the cutting tool. Thus, hybrid [...] Read more.

Machining Nomex honeycomb composite structures is crucial for manufacturing components that meet stringent industry requirements. However, the complex characteristics of this material require specialized machining techniques to avoid defects, ensure optimal surface quality, and preserve the integrity of the cutting tool. Thus, hybrid ultrasonic-vibration-assisted machining (HUSVAM) technology, using a CZ10 combined cutting tool, was introduced to overcome these limitations. To this end, a 3D numerical model based on the finite element method, developed using Abaqus/Explicit 2017 software, allows us to simulate the interaction between the cutting tool and the thin walls of the structure to be machined. The objective of this study was to validate a numerical model through experimental tests while quantifying the impact of critical machining parameters, including the rotation speed and tilt angle, on process performance, in terms of surface finish, tool wear, cutting force components and chip size. The numerical results demonstrated that HUSVAM technology allows for a significant reduction in the cutting force components, with a decrease of between 12% and 35%. Furthermore, this technology improves cutting quality by limiting the deformation and tearing of cell walls, while extending tool life through a significant reduction in wear. These improvements thus contribute to a substantial optimization of the overall efficiency of the machining process. Full article

(This article belongs to the Special Issue Mastering Vibrations: The Latest Breakthroughs in Control for Mechanical Systems)

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36 pages, 25977 KB

Open AccessArticle

How to Win Bosch Future Mobility Challenge: Design and Implementation of the VROOM Autonomous Scaled Vehicle

by Theodoros Papafotiou, Emmanouil Tsardoulias, Alexandros Nikolaou, Aikaterini Papagiannitsi, Despoina Christodoulou, Ioannis Gkountras and Andreas L. Symeonidis

Machines 2025, 13(6), 514; https://doi.org/10.3390/machines13060514 - 12 Jun 2025

Viewed by 1852

Abstract

Over the last decade, a transformation in the automotive industry has been witnessed, as advancements in artificial intelligence and sensor technology have continued to accelerate the development of driverless vehicles. These systems are expected to significantly reduce traffic accidents and associated costs, making [...] Read more.

Over the last decade, a transformation in the automotive industry has been witnessed, as advancements in artificial intelligence and sensor technology have continued to accelerate the development of driverless vehicles. These systems are expected to significantly reduce traffic accidents and associated costs, making their integration into future transportation systems highly impactful. To explore this field in a controlled and flexible manner, scaled autonomous vehicle platforms are increasingly adopted for experimentation. In this work, we propose a set of methodologies to perform autonomous driving tasks through a software–hardware co-design approach. The developed system focuses on deploying a modular and reconfigurable software stack tailored to run efficiently on constrained embedded hardware, demonstrating a balance between real-time capability and computational resource usage. The proposed platform was implemented on a 1:10 scale vehicle that participated in the Bosch Future Mobility Challenge (BFMC) 2024. It integrates a high-performance embedded computing unit and a heterogeneous sensor suite to achieve reliable perception, decision-making, and control. The architecture is structured across four interconnected layers—Input, Perception, Control, and Output—allowing flexible module integration and reusability. The effectiveness of the system was validated throughout the competition scenarios, leading the team to secure first place. Although the platform was evaluated on a scaled vehicle, its underlying software–hardware principles are broadly applicable and scalable to larger autonomous systems. Full article

(This article belongs to the Special Issue Emerging Approaches to Intelligent and Autonomous Systems)

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24 pages, 4655 KB

Open AccessArticle

Effect of Bearing Support Parameters on the Radial and Angular Deformation of Rotor Shaft Gear Based on CRDRS Support Configuration with Intermediate Bearing Support

by Xiaojie Yuan, Xiaoyu Che, Rupeng Zhu and Weifang Chen

Machines 2025, 13(6), 513; https://doi.org/10.3390/machines13060513 - 12 Jun 2025

Viewed by 1251

Abstract

The rotor shaft is a critical component responsible for transmitting engine power to the helicopter’s rotor. Deformation of the rotor shaft can affect the meshing performance of the output stage gears in the main gearbox, thereby affecting load transfer efficiency. By adjusting the [...] Read more.

The rotor shaft is a critical component responsible for transmitting engine power to the helicopter’s rotor. Deformation of the rotor shaft can affect the meshing performance of the output stage gears in the main gearbox, thereby affecting load transfer efficiency. By adjusting the support parameters of the rotor shaft, deformation at critical positions can be minimized, and the meshing performance of the output stage gears can be improved. Therefore, it is imperative to investigate the influence of rotor shaft support parameters on the deformation of the rotor shaft. This paper takes coaxial reversing dual rotor shaft (CRDRS) support configuration with intermediate bearing support as object. Utilizing Timoshenko beam theory, a rotor shaft model is developed, and static equations are derived based on the Lagrange equations. The relaxation iteration method is employed for a two-level iterative solution, and the effects of bearing support positions and support stiffness on the radial and angular deformations of rotor shaft gears under two support configurations, simply supported outer rotor shaft–cantilever-supported inner rotor shaft, and simply supported outer rotor shaft–simply supported inner rotor shaft, are analyzed. The findings indicate that the radial and angular deformations of gear s₁ are consistently smaller than those of gear s₂ in the CRDRS system. This difference is particularly pronounced in the selection of support configuration. The bearing support position plays a dominant role in gear deformation, exhibiting a monotonic linear relationship. In contrast, although adjustments in bearing support stiffness also follow a linear pattern in influencing deformation, their impact is relatively limited. Overall, optimal design should prioritize the adjustment of bearing positions, particularly the layout of b₃ relative to s₂, while complementing it with coordinated modifications to the stiffness of bearings b₂, b₃, and b₄ to effectively enhance the static characteristics of the dual-rotor shaft gears. Full article

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

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15 pages, 1153 KB

Open AccessArticle

Avoiding Lyapunov-Krasovskii Functionals: Simple Nonlinear Sampled–Data Control of a Semi-Active Suspension with Magnetorheological Dampers

by Fernando Viadero-Monasterio, Miguel Meléndez-Useros, Manuel Jiménez-Salas and María Jesús López Boada

Machines 2025, 13(6), 512; https://doi.org/10.3390/machines13060512 - 12 Jun 2025

Viewed by 621

Abstract

This paper presents a novel control design methodology for a magnetorheological (MR) damper-based semi-active suspension system operating under communication-induced time delays, which introduce nonlinear sampled-data dynamics. To address these challenges, a linear matrix inequality (LMI) framework is developed for synthesizing the current controller, [...] Read more.

This paper presents a novel control design methodology for a magnetorheological (MR) damper-based semi-active suspension system operating under communication-induced time delays, which introduce nonlinear sampled-data dynamics. To address these challenges, a linear matrix inequality (LMI) framework is developed for synthesizing the current controller, with the dual goals of enhancing ride comfort and safety while ensuring system stability and robustness against road disturbances. The proposed approach deliberately avoids the use of Lyapunov-Krasovskii functionals, offering a more practical and computationally efficient alternative. Experimental results confirm that the proposed MR damper model outperforms traditional Lyapunov-Krasovskii-based methods. Additionally, two simulated road profiles are used to evaluate the suspension system’s behavior, further demonstrating the effectiveness of the proposed control strategy. Full article

(This article belongs to the Special Issue Adaptive Control Using Magnetorheological Technology)

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22 pages, 3848 KB

Open AccessArticle

A Multi-Category Defect Detection Model for Rail Fastener Based on Optimized YOLOv8n

by Mei Chen, Maolin Zhang, Jun Peng, Jiabin Huang and Haitao Li

Machines 2025, 13(6), 511; https://doi.org/10.3390/machines13060511 - 12 Jun 2025

Cited by 1 | Viewed by 1202

Abstract

Currently, object detection-based rail fastener defect detection methods still face challenges such as limited detection categories, insufficient accuracy, and high computational complexity. To this end, the YOLOv8n-FDD, an advanced multi-category fastener defect detection model designed upon the YOLOv8n with comprehensive optimizations is developed [...] Read more.

Currently, object detection-based rail fastener defect detection methods still face challenges such as limited detection categories, insufficient accuracy, and high computational complexity. To this end, the YOLOv8n-FDD, an advanced multi-category fastener defect detection model designed upon the YOLOv8n with comprehensive optimizations is developed in this paper. Concretely, by introducing the CUT-based style transfer model to generate diverse defect samples, the concern due to imbalanced distribution of sample categories is effectively alleviated. The CA mechanism is incorporated to enhance the feature extraction capability, and the bounding box loss function is further upgraded to improve the model’s generalization performance. With respect to efficiency, the Conv and c2f modules of the YOLOv8n model are, respectively, replaced with the GSConv and VoVGSPCP modules, accordingly achieving a lightweight design. Comparative experimental results demonstrate that the presented YOLOv8n-FDD model outperforms several classic object detection models in terms of detection accuracy, detection speed, model size, and computational complexity. Full article

(This article belongs to the Special Issue Intelligent Vibration Control and Condition Monitoring in Smart Structures and Electromechanical Systems)

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13 pages, 1400 KB

Open AccessCommunication

Human and Humanoid-in-the-Loop (HHitL) Ecosystem: An Industry 5.0 Perspective

by Mahdi Sadeqi Bajestani, Mohammad Mahruf Mahdi, Duhwan Mun and Duck Bong Kim

Machines 2025, 13(6), 510; https://doi.org/10.3390/machines13060510 - 12 Jun 2025

Viewed by 845

Abstract

As manufacturing transitions into the era of Industry 5.0, the demand for systems that are not only intelligent but also human-centric, resilient, and sustainable is becoming increasingly critical. This paper introduces the Human and Humanoid-in-the-Loop (HHitL) ecosystem, a novel framework that integrates both [...] Read more.

As manufacturing transitions into the era of Industry 5.0, the demand for systems that are not only intelligent but also human-centric, resilient, and sustainable is becoming increasingly critical. This paper introduces the Human and Humanoid-in-the-Loop (HHitL) ecosystem, a novel framework that integrates both humans and humanoid robots as collaborative agents within cyber–physical manufacturing environments. Building on the foundational principles of Industry 5.0, the paper presents a 6P architecture that includes participation, purpose, preservation, physical assets, persistence, and projection. The core features of this ecosystem, including anthropomorphism, perceptual intelligence, cognitive adaptability, and dexterity/locomotion, are identified, and their enablers are also introduced. This work presents a forward-looking vision for next-generation manufacturing ecosystems where human values and robotic capabilities converge to form adaptive, ethical, and high-performance systems. Full article

(This article belongs to the Section Advanced Manufacturing)

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22 pages, 5111 KB

Open AccessArticle

Multibody Simulation of 1U CubeSat Passive Attitude Stabilisation Using a Robotic Arm

by Filippo Foiani, Giulia Morettini, Massimiliano Palmieri, Stefano Carletta, Filippo Cianetti and Marco Dionigi

Machines 2025, 13(6), 509; https://doi.org/10.3390/machines13060509 - 11 Jun 2025

Cited by 1 | Viewed by 1043

Abstract

Robotics plays a pivotal role in contemporary space missions, particularly in the development of robotic manipulators for operations in environments that are inaccessible to humans. In accordance with the trend of integrating multiple functionalities into a single system, this study evaluates the feasibility [...] Read more.

Robotics plays a pivotal role in contemporary space missions, particularly in the development of robotic manipulators for operations in environments that are inaccessible to humans. In accordance with the trend of integrating multiple functionalities into a single system, this study evaluates the feasibility of using a robotic manipulator, termed a C-arm, for passive attitude control of a 1U CubeSat. A simplified multibody model of the CubeSat system was employed to assess the robotic arm’s functionality as a gravity gradient boom and subsequently as a passive magnetic control mechanism by utilising a permanent magnet at its extremity. The effectiveness of the C-arm as a gravitational boom is constrained by size and weight, as evidenced by the simulations; the pitch angle oscillated around ±40°, while roll and yaw angles varied up to 30° and 35°, respectively. Subsequent evaluations sought to enhance pointing accuracy through the utilisation of permanent magnets. However, the absence of dissipative forces resulted in attitude instabilities. In conclusion, the integration of a robotic arm into a 1U CubeSat for passive attitude control shows potential, especially for missions where pointing accuracy can tolerate a certain range, as is typical of CubeSat nanosatellite missions. Full article

(This article belongs to the Special Issue Recent Developments in Machine Design, Automation and Robotics)

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15 pages, 3254 KB

Open AccessArticle

MHSAEO Index for Fault Diagnosis of Rolling Bearings in Electric Hoists

by Xinhui Wang, Yan Wang and Yutian He

Machines 2025, 13(6), 508; https://doi.org/10.3390/machines13060508 - 11 Jun 2025

Viewed by 732

Abstract

Rolling bearing fault diagnosis in electric hoists faces significant challenges due to heavy noise and complex vibration interferences, which obscure fault signatures and hinder conventional demodulation methods. While existing techniques like the Teager–Kaiser energy operator (TKEO) and its variants (e.g., HO-AEO, SD-AEO) offer [...] Read more.

Rolling bearing fault diagnosis in electric hoists faces significant challenges due to heavy noise and complex vibration interferences, which obscure fault signatures and hinder conventional demodulation methods. While existing techniques like the Teager–Kaiser energy operator (TKEO) and its variants (e.g., HO-AEO, SD-AEO) offer filterless demodulation, their susceptibility to noise and dependency on preprocessing limit diagnostic accuracy. This study proposes a Multi-resolution Higher-order Symmetric Analytic Energy Operator (MHSAEO) to address these limitations. The MHSAEO integrates three innovations: (1) dynamic non-adjacent sampling to suppress stochastic errors, (2) AM-FM dual demodulation via symmetric energy orthogonality, and (3) adaptive spectral mining for full-band feature extraction. Experimental validation on a 10-ton electric hoist bearing system demonstrates that the MHSAEO achieves signal-to-noise ratio improvements (SNRIs) of −3.83 dB (outer race faults) and −2.12 dB (inner race faults), successfully identifying the characteristic fault frequencies of both inner (145.9 Hz) and outer races in electric hoist bearings with 2nd–5th harmonics. Compared to traditional methods, the MHSAEO reduces computational time by 30.1 × (0.0328 s vs. 0.9872 s) without requiring preprocessing. The results confirm its superior anti-interference capability and real-time performance over the TKEO, HO-AEO, and hybrid denoising–TKEO approaches. Full article

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

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26 pages, 2560 KB

Open AccessArticle

Clustered Correlation Health Scan Anomaly Detection Algorithm Applied for Fault Diagnosis in the Cylinders of a Marine Dual-Fuel Engine

by Hassan Dabaja, Ayah Youssef, Hassan Noura and Mustapha Ouladsine

Machines 2025, 13(6), 507; https://doi.org/10.3390/machines13060507 - 11 Jun 2025

Viewed by 537

Abstract

A novel anomaly detection algorithm is presented to analyze a group of signals that must be correlated under normal conditions. The method is called Clustered Correlation Health Scan (CCH-Scan). It detects abnormal signals, the durations corresponding to abnormalities, and the degree of abnormality. [...] Read more.

A novel anomaly detection algorithm is presented to analyze a group of signals that must be correlated under normal conditions. The method is called Clustered Correlation Health Scan (CCH-Scan). It detects abnormal signals, the durations corresponding to abnormalities, and the degree of abnormality. This algorithm is applied to a case study on fault diagnosis in the cylinders of a 12-cylinder marine dual-fuel engine. In particular, 12 Exhaust Valve Closing Dead Time (ECDT) signals are analyzed to detect abnormalities. Although these signals are critical and any abnormality in them requires urgent intervention, this is the first time they have been discussed in the literature. The details of the algorithm are elaborated, its parameters are studied, and the effects of these parameters on the results are measured and analyzed using a quality score. In addition, a metric to measure the degree of abnormality of the signal is introduced. The method detects abnormal signals, the durations of abnormalities, and the degrees of abnormalities. The results align with ground-truth data from an available technical industrial maintenance report. The approach demonstrates promising potential for application in various other contexts. Full article

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

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25 pages, 9103 KB

Open AccessArticle

Evaluation of Load-Bearing Performance and Cost Efficiency in Steel-Welded and Modular Aluminum Rack Structures

by Lenka Jakubovičová, Milan Vaško and František Synák

Machines 2025, 13(6), 506; https://doi.org/10.3390/machines13060506 - 10 Jun 2025

Viewed by 635

Abstract

The profile modular system offers variability, flexibility, ease of assembly, and corrosion resistance as well as non-time-consuming assembly while meeting the required conditions of the customer. It has a broad spectrum of usability. This article compares the results of a stress analysis solution [...] Read more.

The profile modular system offers variability, flexibility, ease of assembly, and corrosion resistance as well as non-time-consuming assembly while meeting the required conditions of the customer. It has a broad spectrum of usability. This article compares the results of a stress analysis solution for two variants of a rack structure, namely the original variant made by welding Jäkl profiles and the newly proposed design variant created with aluminum Bosch profiles. The finite element method (FEM) is used in computational analyses. FEM models are created using shell elements. Particular attention is given to the use of shell elements in the FEM and their suitability for finite element analyses of the selected structures. Finally, the advantages and disadvantages of both approaches are evaluated, including a safety assessment and an economic comparison of the variants. Full article

(This article belongs to the Section Material Processing Technology)

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23 pages, 29181 KB

Open AccessEditor’s ChoiceArticle

Design and Implementation of a Bionic Marine Iguana Robot for Military Micro-Sensor Deployment

by Gang Chen, Xin Tang, Baohang Guo, Guoqi Li, Zhengrui Wu, Weizhe Huang, Yidong Xu, Ming Lu, Jianfei Liang and Zhen Liu

Machines 2025, 13(6), 505; https://doi.org/10.3390/machines13060505 - 9 Jun 2025

Viewed by 1257

Abstract

Underwater sensor deployment in military applications requires high precision, yet existing robotic solutions often lack the maneuverability and adaptability required for complex aquatic environments. To address this gap, this study proposes a bio-inspired underwater robot modeled after the marine iguana, which exhibits effective [...] Read more.

Underwater sensor deployment in military applications requires high precision, yet existing robotic solutions often lack the maneuverability and adaptability required for complex aquatic environments. To address this gap, this study proposes a bio-inspired underwater robot modeled after the marine iguana, which exhibits effective crawling and swimming capabilities. The research aims to develop a compact, multi-functional robot capable of precise sensor deployment and environmental detection. The methodology integrates a biomimetic mechanical design—featuring leg-based crawling, tail-driven swimming, a deployable head mechanism, and buoyancy control—with a multi-sensor control system for navigation and data acquisition. Gait and trajectory planning are optimized using kinematic modeling for both terrestrial and aquatic locomotion. Experimental results demonstrate the robot’s ability to perform accurate underwater sensor deployment, validating its potential for military applications. This work provides a novel approach to underwater deployment robotics, bridging the gap between biological inspiration and functional engineering. Full article

(This article belongs to the Special Issue Design and Application of Bionic Robots)

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28 pages, 2380 KB

Open AccessArticle

A Unified Framework for Automated Testing of Robotic Process Automation Workflows Using Symbolic and Concolic Analysis

by Ciprian Paduraru, Marina Cernat and Adelina-Nicoleta Staicu

Machines 2025, 13(6), 504; https://doi.org/10.3390/machines13060504 - 9 Jun 2025

Cited by 1 | Viewed by 942

Abstract

Robotic Process Automation is a technology that replicates human interactions with user interfaces across various applications. However, testing Robotic Process Automation implementations remains challenging due to the dynamic nature of workflows. This paper presents a novel testing framework that first integrates symbolic execution [...] Read more.

Robotic Process Automation is a technology that replicates human interactions with user interfaces across various applications. However, testing Robotic Process Automation implementations remains challenging due to the dynamic nature of workflows. This paper presents a novel testing framework that first integrates symbolic execution and concolic testing strategies to enhance Robotic Process Automation workflow validation. Building on insights from these methods, we introduce a hybrid approach that optimizes test coverage and efficiency in specific cases. Our open-source implementation demonstrates that automated testing in the Robotic Process Automation domain significantly improves coverage, reduces manual effort, and enhances reliability. Furthermore, the proposed solution supports multiple Robotic Process Automation platforms and aligns with industry best practices for user interface automation testing. Experimental evaluation, conducted in collaboration with industry, validates the effectiveness of our approach. Full article

(This article belongs to the Special Issue Recent Developments in Machine Design, Automation and Robotics)

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