Open AccessArticle
Root Cause Identification of Machining Error Based on Statistical Process Control and Fault Diagnosis of Machine Tools
Machines 2017, 5(3), 20; doi:10.3390/machines5030020 -
Abstract
The essence of the machining process is the interaction that occurs between machine tools and a workpiece under certain conditions of cutting parameters. Root cause identification (RCI) is critical to the quality control and productivity improvement of machining processes. The geometric error caused
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The essence of the machining process is the interaction that occurs between machine tools and a workpiece under certain conditions of cutting parameters. Root cause identification (RCI) is critical to the quality control and productivity improvement of machining processes. The geometric error caused by fixture faults can be identified in most RCI methods; however, the influence of machine tool degradation on workpiece quality is usually neglected. In this paper, a novel root cause identification scheme of machining error based on statistical process control and fault diagnosis of machine tools is proposed. With the pattern recognition of control charts, quality fluctuations can be detected in a timely manner. Once the machining error occurs, the fault diagnosis of machine tools are carried out. The relationship between machine tool condition and workpiece quality is established and the root cause identification of the machining error can be achieved. A case study of the machining of a complex welded box-type workpiece is presented to illustrate the feasibility of the proposed scheme. It is found that the coaxiality error of the two holes in two sides of the box’s wall is caused by the wear of the worm gear in the rotary work table of the machine tool. Full article
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Open AccessArticle
Drilling Rig Hoisting Platform Security Monitoring System Design and Application
Machines 2017, 5(3), 19; doi:10.3390/machines5030019 -
Abstract
Drilling rig hoisting platform security monitoring system has played a very important role in oil exploration. And drilling parameters and working condition of workers are particularly important, because these parameters indicate that whether the drilling work is safe and effective directly. A security
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Drilling rig hoisting platform security monitoring system has played a very important role in oil exploration. And drilling parameters and working condition of workers are particularly important, because these parameters indicate that whether the drilling work is safe and effective directly. A security monitoring system is established to provide the real-time parameters for drilling safety is the purpose of this study. The monitoring system includes a top drive, a traveling block hook, an oil derrick and a driller room, and the controller of the system is programmable logic controller PLC. The procedure of the system is written by the RSLogix5000 software, the PC configuration is used force control monitor configuration software. According to the system, top drive, driller room and environment wind speed parameters in real-time are collected and displayed in the configuration of upper computer, the collected parameters can be used to determine the working conditions of the top drive and to send timely warnings for inspection maintenance to avoid drilling safety accidents. Work fatigue remind of driller and regularly remind of derrick check can be as much as possible to reduce safety accidents. And automatic operation of traveling block hook reached the default point faster and more smoothly than manual operation given the other uncontrollable factors in manual operation. The application of the system is successfully working in the drilling work site. Full article
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Open AccessArticle
An Ensemble-Boosting Algorithm for Classifying Partial Discharge Defects in Electrical Assets
Machines 2017, 5(3), 18; doi:10.3390/machines5030018 -
Abstract
This paper presents an ensemble-boosting algorithm (EBA) for classifying partial discharge (PD) patterns in the condition monitoring of insulation diagnosis applied for electrical assets. This approach presents an optimization technique for creating a sequence of artificial neural network (ANNs), where the training data
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This paper presents an ensemble-boosting algorithm (EBA) for classifying partial discharge (PD) patterns in the condition monitoring of insulation diagnosis applied for electrical assets. This approach presents an optimization technique for creating a sequence of artificial neural network (ANNs), where the training data for each constituent of the sequence is selected based on the performance of previous ANNs. Four different PD faults scenarios were manufactured in the high-voltage (HV) laboratory to simulate the PD faults of cylindrical voids in methacrylate, point-air-plane configuration, ceramic bushing with contaminated surface and a transformer affected by the internal PD. A PD dataset was collected, pre-processed and prepared for its use in the improved boosting algorithm using statistical techniques. In this paper, the EBA is extensively compared with the widely used single artificial neural network (SNN). Results show that the proposed approach can effectively improve the generalization capability of the PD patterns. The application of the proposed technique for both online and offline practical PD recognition is examined. Full article
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Open AccessArticle
Survivability Analysis on a Cyber-Physical System
Machines 2017, 5(3), 17; doi:10.3390/machines5030017 -
Abstract
A cyber-physical system (CPS) is composed of interdependent physical-resource and cyber-resource networks that are tightly coupled. The malfunction of nodes in a network may trigger failures to the other network and further cause cascading failures, which would potentially lead to the complete collapse
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A cyber-physical system (CPS) is composed of interdependent physical-resource and cyber-resource networks that are tightly coupled. The malfunction of nodes in a network may trigger failures to the other network and further cause cascading failures, which would potentially lead to the complete collapse of the entire system. The number and communication of operating nodes at stable state are closely related to the initial failure nodes and the topology of the network system. To address this issue, this paper studies the survivability of CPS in the presence of initial failure nodes, proposes (m, k)—survivability, which is defined as the probability that at least k nodes are still working in CPS after m nodes are attacked, and discusses the problem of cascading failure based on reliability (CFR). Further, we propose an algorithm to calculate (m, k)—survivability and find that the minimum survivability of system with regular allocation strategy decreases with k for a fixed m, and the proportion of initial failure node groups that cause the system to completely fragment increases with m. The simulation shows the properties and the result of CFR of the system with 12 nodes. Full article
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Open AccessArticle
Do We Understand the Relationship between Affective Computing, Emotion and Context-Awareness?
Machines 2017, 5(3), 16; doi:10.3390/machines5030016 -
Abstract
Historically, the utilization of context, the range and scope of context-aware systems, and the levels of computational intelligence in such systems have been very limited. While the inherent complexity is a significant factor, a principal reason for these limitations lies in the failure
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Historically, the utilization of context, the range and scope of context-aware systems, and the levels of computational intelligence in such systems have been very limited. While the inherent complexity is a significant factor, a principal reason for these limitations lies in the failure to incorporate the emotional component. Affective computing technologies are designed to implement innate emotional capabilities and the capability to simulate emotions and empathy; thus, intelligent context-aware systems with affective computing provide a basis upon which we may effectively enable the emotional component. Moreover, machine cognition relies upon affective computing technologies to provide a basis upon which the emotional component may be incorporated. This paper poses the question: do we understand the relationship between affective computing, emotion and context-awareness? The conclusion drawn is that while affective computing and the need for the incorporation of the emotional component is generally understood and domain-specific strategies to enable implementation have been proposed, there remain important challenges and open research questions in relation to the cognitive modelling and the effective incorporation of affective computing and the emotional component in intelligent context-aware systems. Full article
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Open AccessArticle
A Reliable Turning Process by the Early Use of a Deep Simulation Model at Several Manufacturing Stages
Machines 2017, 5(2), 15; doi:10.3390/machines5020015 -
Abstract
The future of machine tools will be dominated by highly flexible and interconnected systems, in order to achieve the required productivity, accuracy, and reliability. Nowadays, distortion and vibration problems are easily solved in labs for the most common machining operations by using models
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The future of machine tools will be dominated by highly flexible and interconnected systems, in order to achieve the required productivity, accuracy, and reliability. Nowadays, distortion and vibration problems are easily solved in labs for the most common machining operations by using models based on the equations describing the physical laws of the machining processes; however, additional efforts are needed to overcome the gap between scientific research and real manufacturing problems. In fact, there is an increasing interest in developing simulation packages based on “deep-knowledge and models” that aid machine designers, production engineers, or machinists to get the most out of the machine-tools. This article proposes a methodology to reduce problems in machining by means of a simulation utility, which uses the main variables of the system and process as input data, and generates results that help in the proper decision-making and machining plan. Direct benefits can be found in (a) the fixture/clamping optimal design; (b) the machine tool configuration; (c) the definition of chatter-free optimum cutting conditions and (d) the right programming of cutting toolpaths at the Computer Aided Manufacturing (CAM) stage. The information and knowledge-based approach showed successful results in several local manufacturing companies and are explained in the paper. Full article
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Open AccessFeature PaperArticle
Automated Cable Preparation for Robotized Stator Cable Winding
Machines 2017, 5(2), 14; doi:10.3390/machines5020014 -
Abstract
A method for robotized cable winding of the Uppsala University Wave Energy Converter generator stator has previously been presented and validated. The purpose of this study is to present and validate further developments to the method: automated stand-alone equipment for the preparation of
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A method for robotized cable winding of the Uppsala University Wave Energy Converter generator stator has previously been presented and validated. The purpose of this study is to present and validate further developments to the method: automated stand-alone equipment for the preparation of the winding cables. The cable preparation consists of three parts: feeding the cable from a drum, forming the cable end and cutting the cable. Forming and cutting the cable was previously done manually and only small cable drums could be handled. Therefore the robot cell needed to be stopped frequently. The new equipment was tested in an experimental robot stator cable winding setup. Through the experiments, the equipment was validated to be able to perform fully automated and robust cable preparation. Suggestions are also given on how to further develop the equipment with regards to performance, robustness and quality. Hence, this work represents another important step towards demonstrating completely automated robotized stator cable winding. Full article
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Open AccessArticle
Dynamic Simulation of the Harvester Boom Cylinder
Machines 2017, 5(2), 13; doi:10.3390/machines5020013 -
Abstract
Based on the complete dynamic calculation method, the layout, force, and strength of harvester boom cylinders were designed and calculated. Closed simulations for the determination of the dynamic responses of the harvester boom during luffing motion considering the cylinder drive system and luffing
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Based on the complete dynamic calculation method, the layout, force, and strength of harvester boom cylinders were designed and calculated. Closed simulations for the determination of the dynamic responses of the harvester boom during luffing motion considering the cylinder drive system and luffing angle position control have been realized. Using the ADAMS mechanical system dynamics analysis software, six different arm poses were selected and simulated based on the cylinder as the analysis object. A flexible model of the harvester boom luffing motion has been established. The movement of the oil cylinder under different conditions were analyzed, and the main operation dimensions of the harvester boom and the force condition of the oil cylinder were obtained. The calculation results show that the dynamic responses of the boom are more sensitive to the luffing acceleration, in comparison with the luffing velocity. It is seen that this method is very effective and convenient for boom luffing simulation. It is also reasonable to see that the extension of the distance of the bottom of the boom is shortened by adjusting the initial state of the boom in the working process, which can also effectively reduce the workload of the boom—thus improving the mechanical efficiency. Full article
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Open AccessArticle
Concepts for 3D Printing-Based Self-Replicating Robot Command and Coordination Techniques
Machines 2017, 5(2), 12; doi:10.3390/machines5020012 -
Abstract
Self-replicating robots represent a new area for prospective advancement in robotics. A self-replicating robot can identify when additional robots are needed to solve a problem or meet user needs, and create them in response to this identified need. This allows robotic systems to
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Self-replicating robots represent a new area for prospective advancement in robotics. A self-replicating robot can identify when additional robots are needed to solve a problem or meet user needs, and create them in response to this identified need. This allows robotic systems to respond to changing (or non-predicted) mission needs. Being able to modify the physical system component provides an additional tool for optimizing robotic system performance. This paper begins the process of developing a command and coordination system that makes decisions with the consideration of replication, repair, and retooling capabilities. A high-level algorithm is proposed and qualitatively assessed. Full article
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Open AccessArticle
Integrated Condition Monitoring and Prognosis Method for Incipient Defect Detection and Remaining Life Prediction of Low Speed Slew Bearings
Machines 2017, 5(2), 11; doi:10.3390/machines5020011 -
Abstract
This paper presents an application of multivariate state estimation technique (MSET), sequential probability ratio test (SPRT) and kernel regression for low speed slew bearing condition monitoring and prognosis. The method is applied in two steps. Step (1) is the detection of the incipient
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This paper presents an application of multivariate state estimation technique (MSET), sequential probability ratio test (SPRT) and kernel regression for low speed slew bearing condition monitoring and prognosis. The method is applied in two steps. Step (1) is the detection of the incipient slew bearing defect. In this step, combined MSET and SPRT is used with circular-domain kurtosis, time-domain kurtosis, wavelet decomposition (WD) kurtosis, empirical mode decomposition (EMD) kurtosis and the largest Lyapunov exponent (LLE) feature. Step (2) is the prediction of the selected features’ trends and the estimation of the remaining useful life (RUL) of the slew bearing. In this step, kernel regression is used with time-domain kurtosis, WD kurtosis and the LLE feature. The application of the method is demonstrated with laboratory slew bearing acceleration data. Full article
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Open AccessArticle
Automated Mounting of Pole-Shoe Wedges in Linear Wave Power Generators—Using Industrial Robotics and Proximity Sensors
Machines 2017, 5(1), 10; doi:10.3390/machines5010010 -
Abstract
A system for automatic mounting of high tolerance wedges inside a wave power linear generator is proposed. As for any renewable energy concept utilising numerous smaller generation units, minimising the production cost per unit is vital for commercialization. The linear generator in question
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A system for automatic mounting of high tolerance wedges inside a wave power linear generator is proposed. As for any renewable energy concept utilising numerous smaller generation units, minimising the production cost per unit is vital for commercialization. The linear generator in question uses self-locking wedges, which are challenging to mount using industrial robots due to the high tolerances used, and because of the fact that any angular error remaining after calibration risks damaging the equipment. Using two types of probes, mechanical touch probes and inductive proximity sensors, combined with a flexible robot tool and iterative calibration routines, an automatic mounting system that overcomes the challenges of high tolerance wedge mounting is presented. The system is experimentally verified to work at mounting speeds of up to 50mm/s, and calibration accuracies of 0.25mmand 0.1 ∘ are achieved. The use of a flexible robot tool, able to move freely in one Cartesian plane, was found to be essential for making the system work. Full article
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Open AccessArticle
Direct Uncertainty Minimization Framework for System Performance Improvement in Model Reference Adaptive Control
Machines 2017, 5(1), 9; doi:10.3390/machines5010009 -
Abstract
Inthispaper, adirectuncertaintyminimizationframeworkisdevelopedanddemonstrated for model reference adaptive control laws. The proposed framework consists of a novel architecture involvingmodificationtermsintheadaptivecontrollawandtheupdatelaw. Inparticular,theseterms areconstructedthroughagradientminimizationprocedureinordertoachieveimprovedclosed-loop system performance with adaptive control laws. The proposed framework is first developed for adaptive control laws with linear reference models and then generalized to
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Inthispaper, adirectuncertaintyminimizationframeworkisdevelopedanddemonstrated for model reference adaptive control laws. The proposed framework consists of a novel architecture involvingmodificationtermsintheadaptivecontrollawandtheupdatelaw. Inparticular,theseterms areconstructedthroughagradientminimizationprocedureinordertoachieveimprovedclosed-loop system performance with adaptive control laws. The proposed framework is first developed for adaptive control laws with linear reference models and then generalized to adaptive control laws with nonlinear reference models. Two illustrative numerical examples are included to demonstrate the efficacy of the proposed framework. Full article
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Open AccessArticle
Life Cycle Analysis of Double-Arm Type Robotic Tools for LCD Panel Handling
Machines 2017, 5(1), 8; doi:10.3390/machines5010008 -
Abstract
This study includes a life cycle assessment of double-arm type robotic tools made with three different materials. The robotic arms are used for Liquid Crystal Display (LCD) panel handling. The environmental impacts generated during all the life stages of the robots have been
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This study includes a life cycle assessment of double-arm type robotic tools made with three different materials. The robotic arms are used for Liquid Crystal Display (LCD) panel handling. The environmental impacts generated during all the life stages of the robots have been investigated. The study shows that composite materials have less environmental impact compared with metallic materials. It is also found that the most significant impact category generated by the robotic tools is carcinogen, while the use stage of the robotic tool’s life cycle has the greatest environmental impact. Full article
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Open AccessReview
The Insulation for Machines Having a High Lifespan Expectancy, Design, Tests and Acceptance Criteria Issues
Machines 2017, 5(1), 7; doi:10.3390/machines5010007 -
Abstract
The windings insulation of electrical machines will remain a topic that is updated frequently. The criteria severity requested by the electrical machine applications increases continuously. Manufacturers and designers are always confronted with new requirements or new criteria with enhanced performances. The most problematic
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The windings insulation of electrical machines will remain a topic that is updated frequently. The criteria severity requested by the electrical machine applications increases continuously. Manufacturers and designers are always confronted with new requirements or new criteria with enhanced performances. The most problematic requirements that will be investigated here are the extremely long lifespan coupled to critical operating conditions (overload, supply grid instabilities, and critical operating environments). Increasing lifespan does not have a considerable benefit because the purchasing price of usual machines has to be compared to the purchasing price and maintenance price of long lifespan machines. A machine having a 40-year lifespan will cost more than twice the usual price of a 20-year lifetime machine. Systems which need a long lifetime are systems which are crucial for a country, and those for which outage costs are exorbitant. Nuclear power stations are such systems. It is certain that the used technologies have evolved since the first nuclear power plant, but they cannot evolve as quickly as in other sectors of activities. No-one wants to use an immature technology in such power plants. Even if the electrical machines have exceeded 100 years of age, their improvements are linked to a patient and continuous work. Nowadays, the windings insulation systems have a well-established structure, especially high voltage windings. Unfortunately, a high life span is not only linked to this result. Several manufacturers’ improvements induced by many years of experiment have led to the writing of standards that help the customers and the manufacturers to regularly enhance the insulation specifications or qualifications. Hence, in this publication, the authors will give a step by step exhaustive review of one insulation layout and will take time to give a detailed report on the standards that are linked to insulation systems. No standard can provide insurance about lifespan, nor do any insulation tests incorporate all of the operating conditions: thermal, mechanical, moisture and chemical. Even if one manufacturer uses the standards compliance to demonstrate the quality of its realization; in the end, the successful use in operation remains an objective test. Thereafter, both customer and manufacturers will use the standards while knowing that such documents cannot fully satisfy their wishes. In one 20-year historical review, the authors will highlight the duration in insulation improvements and small breakthroughs in standards writing. High lifespan machines are not the main interest of standards. A large part of this publication is dedicated to the improvements of the insulation wall to achieve the lifespan. Even if the choice of raw materials is fundamental, the understanding of ageing phenomena also leads to improvements. Full article
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Open AccessArticle
Perception, Planning, Control, and Coordination for Autonomous Vehicles
Machines 2017, 5(1), 6; doi:10.3390/machines5010006 -
Abstract
Autonomous vehicles are expected to play a key role in the future of urban transportation systems, as they offer potential for additional safety, increased productivity, greater accessibility, better road efficiency, and positive impact on the environment. Research in autonomous systems has seen dramatic
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Autonomous vehicles are expected to play a key role in the future of urban transportation systems, as they offer potential for additional safety, increased productivity, greater accessibility, better road efficiency, and positive impact on the environment. Research in autonomous systems has seen dramatic advances in recent years, due to the increases in available computing power and reduced cost in sensing and computing technologies, resulting in maturing technological readiness level of fully autonomous vehicles. The objective of this paper is to provide a general overview of the recent developments in the realm of autonomous vehicle software systems. Fundamental components of autonomous vehicle software are reviewed, and recent developments in each area are discussed. Full article
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Open AccessArticle
A Method for Design of Modular Reconfigurable Machine Tools
Machines 2017, 5(1), 5; doi:10.3390/machines5010005 -
Abstract
Presented in this paper is a method for the design of modular reconfigurable machine tools (MRMTs). An MRMT is capable of using a minimal number of modules through reconfiguration to perform the required machining tasks for a family of parts. The proposed method
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Presented in this paper is a method for the design of modular reconfigurable machine tools (MRMTs). An MRMT is capable of using a minimal number of modules through reconfiguration to perform the required machining tasks for a family of parts. The proposed method consists of three steps: module identification, module determination, and layout synthesis. In the first step, the module components are collected from a family of general-purpose machines to establish a module library. In the second step, for a given family of parts to be machined, a set of needed modules are selected from the module library to construct a desired reconfigurable machine tool. In the third step, a final machine layout is decided though evaluation by considering a number of performance indices. Based on this method, a software package has been developed that can design an MRMT for a given part family. Full article
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Open AccessArticle
Automatic Motion Generation for Robotic Milling Optimizing Stiffness with Sample-Based Planning
Machines 2017, 5(1), 3; doi:10.3390/machines5010003 -
Abstract
Optimal and intuitive robotic machining is still a challenge. One of the main reasons for this is the lack of robot stiffness, which is also dependent on the robot positioning in the Cartesian space. To make up for this deficiency and with the
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Optimal and intuitive robotic machining is still a challenge. One of the main reasons for this is the lack of robot stiffness, which is also dependent on the robot positioning in the Cartesian space. To make up for this deficiency and with the aim of increasing robot machining accuracy, this contribution describes a solution approach for optimizing the stiffness over a desired milling path using the free degree of freedom of the machining process. The optimal motion is computed based on the semantic and mathematical interpretation of the manufacturing process modeled on its components: product, process and resource; and by configuring automatically a sample-based motion problem and the transition-based rapid-random tree algorithm for computing an optimal motion. The approach is simulated on a CAM software for a machining path revealing its functionality and outlining future potentials for the optimal motion generation for robotic machining processes. Full article
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Open AccessArticle
Physics-Embedded Machine Learning: Case Study with Electrochemical Micro-Machining
Machines 2017, 5(1), 4; doi:10.3390/machines5010004 -
Abstract
Although intelligent machine learning techniques have been used for input-output modeling of many different manufacturing processes, these techniques map directly from the input process parameters to the outputs and do not take into consideration any partial knowledge available about the mechanisms and physics
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Although intelligent machine learning techniques have been used for input-output modeling of many different manufacturing processes, these techniques map directly from the input process parameters to the outputs and do not take into consideration any partial knowledge available about the mechanisms and physics of the process. In this paper, a new approach is presented for taking advantage of the partial knowledge available about the mechanisms of the process and embedding it into the neural network structure. To validate the proposed approach, it is used to create a forward prediction model for the process of electrochemical micro-machining (μ-ECM). The prediction accuracy of the proposed approach is compared to the prediction accuracy of pure neural structure models with different structures and the results show that the Neural Network (NN) models with embedded knowledge have better prediction accuracy over pure NN models. Full article
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Open AccessEditorial
Acknowledgement to Reviewers of Machines in 2016
Machines 2017, 5(1), 2; doi:10.3390/machines5010002 -
Abstract
The editors of Machines would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2016.[...] Full article
Open AccessArticle
Online Estimation and Correction of Systematic Encoder Line Errors
Machines 2017, 5(1), 1; doi:10.3390/machines5010001 -
Abstract
This paper addresses the identification and correction of amplitude and offset errors in the sinusoidal outputs from incremental position encoders. Precise angular position measurement is of high importance in many position control applications. Manufacturing tolerances and noise from thermal and electromagnetic interference sources
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This paper addresses the identification and correction of amplitude and offset errors in the sinusoidal outputs from incremental position encoders. Precise angular position measurement is of high importance in many position control applications. Manufacturing tolerances and noise from thermal and electromagnetic interference sources introduce systematic and random errors in the orthogonal sine cosine output line signals. Evaluation of these signals reproduces deviations in the measured angular position. This paper proposes two methods to identify and compensate for the influence of the systematic errors online without the necessity of a reference measurement during identification. The key component of the methods is a nonlinear estimator that exploits the orthogonality property of harmonic functions. The first method explains the basic idea with a scalar error model and operates continuously but exhibits an angular shift in direction of rotation during transients of the parameters, whereas the second method assumes an error model with error parameters as a function over one full revolution of the encoder. The latter updates the error function iteratively in subsequent revolutions. Full article
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