Open AccessArticle
Utilizing Sequential Action Control Method in GaN-Based High-Speed Drive for BLDC Motor
Machines 2017, 5(4), 28; doi:10.3390/machines5040028 -
Abstract
This paper presents a hybrid model–based control algorithm that combines Model Predictive Control (MPC) and Sequential Action Control (SAC) deployed in a high-speed drive for Brushless DC (BLDC) motor by using a DC-DC converter with Gallium Nitride (GaN) switches. GaN FETs are selected
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This paper presents a hybrid model–based control algorithm that combines Model Predictive Control (MPC) and Sequential Action Control (SAC) deployed in a high-speed drive for Brushless DC (BLDC) motor by using a DC-DC converter with Gallium Nitride (GaN) switches. GaN FETs are selected because of their higher speed and lower power loss as compared with traditional Si switches. In the proposed framework, SAC processes the initial values of the control variables as well as their time of application and their duration in MPC loop. After receiving the underlying estimation of future contribution from SAC, MPC consolidates it with current input and predicts future control values by using the system state space model. This hybrid control conserves control effort and reduces sensitivity to initial conditions. In this way, converter’s output voltage is controlled to produce the reference speed at the motor output. National Instrument PXIe-6356 module is utilized as the interface between software and hardware that is a multi-function, LabVIEW-compatible data acquisition device. The viability of the proposed hybrid optimization for the high-speed drive is confirmed numerically by utilizing MATLAB/Simulink and approved experimentally using a Gallium Nitride (GaN) half-bridge DC-DC converter. Full article
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Open AccessArticle
The Decision making System for Condition Monitoring of Induction Motors Based on Vector Control Model
Machines 2017, 5(4), 27; doi:10.3390/machines5040027 -
Abstract
Induction motors are mainly used for variable load applications and it is vital to have a condition monitoring system with capabilities to diagnose motor faults in variable load conditions. The environment noise varies has non-linear relation with motor load and it challenges the
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Induction motors are mainly used for variable load applications and it is vital to have a condition monitoring system with capabilities to diagnose motor faults in variable load conditions. The environment noise varies has non-linear relation with motor load and it challenges the decision making capability of the condition monitoring system. This paper addresses the issue of reliable decision making on the existence of bearing faults in variable load conditions. Two type of threshold schemes have been proposed to reliably diagnose bearing faults in Park vector modulus spectrum. The performance of the developed threshold based condition monitoring system has been analyzed theoretically and experimentally. Full article
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Open AccessArticle
Modeling, Analysis, and Realization of Permanent Magnet Synchronous Motor Current Vector Control by MATLAB/Simulink and FPGA
Machines 2017, 5(4), 26; doi:10.3390/machines5040026 -
Abstract
In this paper, we present the modeling, analysis, and realization of current vector control for a permanent magnet synchronous motor (PMSM) drive using MATLAB/Simulink and a field programmable gate array (FPGA). In AC motor drive systems, most of the current vector controls are
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In this paper, we present the modeling, analysis, and realization of current vector control for a permanent magnet synchronous motor (PMSM) drive using MATLAB/Simulink and a field programmable gate array (FPGA). In AC motor drive systems, most of the current vector controls are realized by digital signal processors (DSPs) because of their complete and compact hardware functions. However, the performances of drive systems realized by low-cost DSP are limited by the hardware structure and computation capacity, which may lead to the difficulty of reaching a fast enough response, above all, for those motors with a small electrical time constant. Therefore, we use FPGA to speed up the calculation about the current vector control to attain a fast response. Simulations and practical experimental results are used to verify the correctness and performance of the designed full hardware system. Full article
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Open AccessFeature PaperArticle
Virtual Reference Feedback Tuning of Model-Free Control Algorithms for Servo Systems
Machines 2017, 5(4), 25; doi:10.3390/machines5040025 -
Abstract
This paper proposes the combination of two data-driven techniques, namely virtual reference feedback tuning (VRFT) and model-Free Control (MFC) in terms of the VRFT of MFC algorithms dedicated to servo systems. VRFT ensures the automatic optimal computation of the parameters of three MFC
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This paper proposes the combination of two data-driven techniques, namely virtual reference feedback tuning (VRFT) and model-Free Control (MFC) in terms of the VRFT of MFC algorithms dedicated to servo systems. VRFT ensures the automatic optimal computation of the parameters of three MFC algorithms represented by intelligent proportional (iP), intelligent proportional-integral (iPI), and intelligent proportional-integral-derivative (iPID) controllers. The combination of MFC and VRFT leads to a novel mixed MFC-VRFT approach. The approach is validated by experimental results related to the angular speed control of modular servo system laboratory equipment. The performance of the control systems with the MFC algorithms (iP, iPI, and iPID controllers) tuned by the mixed MFC-VRFT approach is compared with that of control systems with MFC algorithms tuned by a metaheuristics gravitational search algorithm (GSA) optimizer, and of control systems with I, PI and PID controllers optimally tuned by VRFT and GSA in the same optimization problem. Full article
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Open AccessReview
Rotating Electrical Machine Condition Monitoring Automation—A Review
Machines 2017, 5(4), 24; doi:10.3390/machines5040024 -
Abstract
We review existing machine condition monitoring techniques and industrial automation for plant-wide condition monitoring of rotating electrical machines. Cost and complexity of a condition monitoring system increase with the number of measurements, so extensive condition monitoring is currently mainly restricted to the situations
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We review existing machine condition monitoring techniques and industrial automation for plant-wide condition monitoring of rotating electrical machines. Cost and complexity of a condition monitoring system increase with the number of measurements, so extensive condition monitoring is currently mainly restricted to the situations where the consequences of poor availability, yield or quality are so severe that they clearly justify the investment in monitoring. There are challenges to obtaining plant-wide monitoring that includes even small machines and non-critical applications. One of the major inhibiting factors is the ratio of condition monitoring cost to equipment cost, which is crucial to the acceptance of using monitoring to guide maintenance for a large fleet of electrical machinery. Ongoing developments in sensing, communication and computation for industrial automation may greatly extend the set of machines for which extensive monitoring is viable. Full article
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Open AccessArticle
Toilet Assistive System Designed for the Reduction of Accidental Falls in the Bathroom Using Admittance Controller
Machines 2017, 5(4), 23; doi:10.3390/machines5040023 -
Abstract
This paper suggests an assistive system for the toilet with the objective of measuring human activities and to provide intelligent mechanical assistance to help seating and standing. The project intends to develop a seating assistance as a technical aid in order to reduce
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This paper suggests an assistive system for the toilet with the objective of measuring human activities and to provide intelligent mechanical assistance to help seating and standing. The project intends to develop a seating assistance as a technical aid in order to reduce accidents and falls in the bathroom. The preferred technique is human-robot physical interaction algorithms known in collaborative robotics (cobot) and adapting it to a personalized assistance technology installed on a smart toilet. First, the design of the mechanical assistance is presented. Then, an admittance controller is designed and implemented in order to help the user in a similar way as a cobot could be used. This technique could be used to assist the user and improve balance with adequate training and an adequate configuration of the admittance controller. Full article
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Open AccessArticle
Quantification of a Low-Cost Stretchable Conductive Sensor Using an Expansion/Contraction Simulator Machine: A Step towards Validation of a Noninvasive Cardiac and Respiration Monitoring Prototype
Machines 2017, 5(4), 22; doi:10.3390/machines5040022 -
Abstract
The use of wearable sensors in health monitoring is increasing dramatically, largely due to their convenience and low-cost. Understanding the accuracy of any given sensor is paramount to avoid potential misdiagnosis. Commercially available electro-resistive band (ERB) sensors have been integrated into several newly
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The use of wearable sensors in health monitoring is increasing dramatically, largely due to their convenience and low-cost. Understanding the accuracy of any given sensor is paramount to avoid potential misdiagnosis. Commercially available electro-resistive band (ERB) sensors have been integrated into several newly developed wearable devices with a view to using these sensors to monitor a range of respiratory and cardiovascular metrics. Quantification of the ERBs is a necessary to step towards validation of these prototypes, as it provides valuable information, which could be exploited for compensation and ultimately, for improvement of their performance. Here, we present an analysis of the ERB sensors using an expansion/contraction simulator machine. Using the developed rig, the characteristics of four ERBs were compared with a linear displacement sensor (string potentiometer) during continuous use over the course of four-and-a-half days to investigate the error and nonlinearity of the ERBs. The analysis of the recorded data includes calculation and comparison of the total harmonic distortions of the two sensors to quantify ERB nonlinearity. Moreover, comparisons between the peak-to-peak voltages and signal-to-noise ratios of the ERB and string potentiometer demonstrate the effect nonlinearity on these factors. This paper demonstrates the nonlinearity of ERBs and highlights the implications for their use in practice. Full article
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Open AccessReview
A Review of Feature Extraction Methods in Vibration-Based Condition Monitoring and Its Application for Degradation Trend Estimation of Low-Speed Slew Bearing
Machines 2017, 5(4), 21; doi:10.3390/machines5040021 -
Abstract
This paper presents an empirical study of feature extraction methods for the application of low-speed slew bearing condition monitoring. The aim of the study is to find the proper features that represent the degradation condition of slew bearing rotating at very low speed
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This paper presents an empirical study of feature extraction methods for the application of low-speed slew bearing condition monitoring. The aim of the study is to find the proper features that represent the degradation condition of slew bearing rotating at very low speed (≈ 1 r/min) with naturally defect. The literature study of existing research, related to feature extraction methods or algorithms in a wide range of applications such as vibration analysis, time series analysis and bio-medical signal processing, is discussed. Some features are applied in vibration slew bearing data acquired from laboratory tests. The selected features such as impulse factor, margin factor, approximate entropy and largest Lyapunov exponent (LLE) show obvious changes in bearing condition from normal condition to final failure. Full article
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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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