Pub Date : 2013-10-24DOI: 10.1109/DEMPED.2013.6645743
M. Perdomo, M. Pacas, T. Eutebach, J. Immel
The automatic operation of processes requires accurate and up-to-date information about the current state of the system parameters, which frequently cannot be measured during operation. Furthermore, this parameters can change in time due to several factors such as the own dynamics of the system. For electrically powered systems a correct description of the mechanical part and its dynamics is a requirement for a good control performance. The present work describes a Kalman Filter approach to the identification of mechanical parameters. The online identification of time variable mechanical parameters is a task of prime importance for the tuning of self-adaptive controls. In this paper a method for the identification of constant and variable mechanical parameters in industrial drives, introduced in the past by other authors, is analyzed and experimentally tested.
{"title":"Identification of variable mechanical parameters using extended Kalman Filters","authors":"M. Perdomo, M. Pacas, T. Eutebach, J. Immel","doi":"10.1109/DEMPED.2013.6645743","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645743","url":null,"abstract":"The automatic operation of processes requires accurate and up-to-date information about the current state of the system parameters, which frequently cannot be measured during operation. Furthermore, this parameters can change in time due to several factors such as the own dynamics of the system. For electrically powered systems a correct description of the mechanical part and its dynamics is a requirement for a good control performance. The present work describes a Kalman Filter approach to the identification of mechanical parameters. The online identification of time variable mechanical parameters is a task of prime importance for the tuning of self-adaptive controls. In this paper a method for the identification of constant and variable mechanical parameters in industrial drives, introduced in the past by other authors, is analyzed and experimentally tested.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130515514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-24DOI: 10.1109/DEMPED.2013.6645766
F. Khelifi, B. Nadji
This work describes the operation of the fault tolerant inverter. The consequences of the switch defect in a traditional voltage inverter are analyzed. The studied failures are the short-circuit defect and the opening defect. The consequences of transistor defect leading to a final state of short-circuit or open circuit are discussed. It was proposed to implement a topology of fault-tolerant inverter with four-arms. The use of this inverter allows the increase in the availability of the converter. All simulations were done with the PSIM 7.1.2 software.
{"title":"Study of fault — Tolerant inverter","authors":"F. Khelifi, B. Nadji","doi":"10.1109/DEMPED.2013.6645766","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645766","url":null,"abstract":"This work describes the operation of the fault tolerant inverter. The consequences of the switch defect in a traditional voltage inverter are analyzed. The studied failures are the short-circuit defect and the opening defect. The consequences of transistor defect leading to a final state of short-circuit or open circuit are discussed. It was proposed to implement a topology of fault-tolerant inverter with four-arms. The use of this inverter allows the increase in the availability of the converter. All simulations were done with the PSIM 7.1.2 software.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122319903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-24DOI: 10.1109/DEMPED.2013.6645734
A. J. Fernandez Gomez, A. Dziechciarz, T. Sobczyk
The use of mathematical models of faulty induction machine has proved a useful tool for prediction of main effects due to faults. Researches develop mathematical models to use them as base of analysis of practical cases. The induction machine has become one of the most important elements in the industry, which has resulted in increased interest in controlling its operation. Among the usual faults in induction machines mechanical faults represent the 50-60% of the total failures. Those faults have associated in most cases some degree of eccentricity. In this paper a mathematical model of mixed eccentricity effects on induction machine for industrial drives applications is presented. The purpose of the paper is going one step further than previous approach of static and dynamic eccentricities showing that only one model is enough to reproduce successfully all types of eccentricities. Effects of main magneto-motive forces and steady-state performance of the motor supplied by a symmetrical sinusoidal source have been studied making it easy to understand the physical phenomena inside the machine and simplify the mathematical representation of those eccentricities. Based on this approach Matlab/Simulink models can be created for fault diagnosis purposes.
{"title":"Mathematical modeling of eccentricities in induction machines by the mono-harmonic model","authors":"A. J. Fernandez Gomez, A. Dziechciarz, T. Sobczyk","doi":"10.1109/DEMPED.2013.6645734","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645734","url":null,"abstract":"The use of mathematical models of faulty induction machine has proved a useful tool for prediction of main effects due to faults. Researches develop mathematical models to use them as base of analysis of practical cases. The induction machine has become one of the most important elements in the industry, which has resulted in increased interest in controlling its operation. Among the usual faults in induction machines mechanical faults represent the 50-60% of the total failures. Those faults have associated in most cases some degree of eccentricity. In this paper a mathematical model of mixed eccentricity effects on induction machine for industrial drives applications is presented. The purpose of the paper is going one step further than previous approach of static and dynamic eccentricities showing that only one model is enough to reproduce successfully all types of eccentricities. Effects of main magneto-motive forces and steady-state performance of the motor supplied by a symmetrical sinusoidal source have been studied making it easy to understand the physical phenomena inside the machine and simplify the mathematical representation of those eccentricities. Based on this approach Matlab/Simulink models can be created for fault diagnosis purposes.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126769206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-24DOI: 10.1109/DEMPED.2013.6645741
D. Shi
A new scheme based on the demodulation technique and interpolated fast Fourier transform (IFFT) is proposed to construct purified space vector for the purpose of sensorless speed measurement and fault diagnosis for induction motors. The phase and amplitude fluctuation associated with the eccentricity harmonics is demodulated first. Interpolated fast Fourier transform is then performed to estimate the speed of induction motors running under constant speed and transient conditions. Experimental studies have further confirmed good agreement between the estimated motor speed using the proposed scheme and the measured speed using an encoder. The effectiveness of proposed purified space vector has been further demonstrated in the detection of coupling misalignments and stator faults.
{"title":"Sensorless speed estimation and diagnosis of induction motors based on purified space vectors","authors":"D. Shi","doi":"10.1109/DEMPED.2013.6645741","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645741","url":null,"abstract":"A new scheme based on the demodulation technique and interpolated fast Fourier transform (IFFT) is proposed to construct purified space vector for the purpose of sensorless speed measurement and fault diagnosis for induction motors. The phase and amplitude fluctuation associated with the eccentricity harmonics is demodulated first. Interpolated fast Fourier transform is then performed to estimate the speed of induction motors running under constant speed and transient conditions. Experimental studies have further confirmed good agreement between the estimated motor speed using the proposed scheme and the measured speed using an encoder. The effectiveness of proposed purified space vector has been further demonstrated in the detection of coupling misalignments and stator faults.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"46 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114020979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-24DOI: 10.1109/DEMPED.2013.6645711
M. Alamyal, S. Gadoue, B. Zahawi
In this paper, an identification technique for fault detection of induction machines using Genetic Algorithm (GA) is investigated. The condition monitoring technique proposed in this paper indicates the presence of a winding fault and provides information about its nature and location. The data required for the proposed method are motor terminal voltages, stator currents and rotor speed obtained during steady state operation. The data is then processed off-line using an induction motor model in conjunction with GA to determine the effective motor parameters. The proposed technique is demonstrated using experimental data obtained from a 1.5 kW wound rotor three-phase induction machine with both stator and rotor winding faults considered. Results confirm the effectiveness of GA to properly identify the type and location of the fault without the need for knowledge of various fault signatures.
{"title":"Detection of induction machine winding faults using genetic algorithm","authors":"M. Alamyal, S. Gadoue, B. Zahawi","doi":"10.1109/DEMPED.2013.6645711","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645711","url":null,"abstract":"In this paper, an identification technique for fault detection of induction machines using Genetic Algorithm (GA) is investigated. The condition monitoring technique proposed in this paper indicates the presence of a winding fault and provides information about its nature and location. The data required for the proposed method are motor terminal voltages, stator currents and rotor speed obtained during steady state operation. The data is then processed off-line using an induction motor model in conjunction with GA to determine the effective motor parameters. The proposed technique is demonstrated using experimental data obtained from a 1.5 kW wound rotor three-phase induction machine with both stator and rotor winding faults considered. Results confirm the effectiveness of GA to properly identify the type and location of the fault without the need for knowledge of various fault signatures.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131521518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-24DOI: 10.1109/DEMPED.2013.6645726
Y. Maouche, Abdelfettah Boussaid, M. Boucherma, A. Khezzar
Most existing electrical faults in induction machines are stator turn faults; therefore the modeling of this defect appears very interesting. A number of authors have treated the modeling of this defect by completely changing the model from healthy to a defective one. This paper deals with the modeling of induction machines considering both healthy and faulty stator cases. The aim of this work is to make the electrical matrix parameters as a function of stator winding distribution. The consequence of both, fault degree and fault location are also considered. Stator faults detection are based on frequency analysis of the zero sequence for delta connected winding and on neutral voltage for wye connected winding. The simulation results show that the significant increase or decrease of certain harmonics can be used to detect short circuited turns in the machine stator.
{"title":"Modeling and simulation of stator turn faults. Detection based on stator circular current and neutral voltage","authors":"Y. Maouche, Abdelfettah Boussaid, M. Boucherma, A. Khezzar","doi":"10.1109/DEMPED.2013.6645726","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645726","url":null,"abstract":"Most existing electrical faults in induction machines are stator turn faults; therefore the modeling of this defect appears very interesting. A number of authors have treated the modeling of this defect by completely changing the model from healthy to a defective one. This paper deals with the modeling of induction machines considering both healthy and faulty stator cases. The aim of this work is to make the electrical matrix parameters as a function of stator winding distribution. The consequence of both, fault degree and fault location are also considered. Stator faults detection are based on frequency analysis of the zero sequence for delta connected winding and on neutral voltage for wye connected winding. The simulation results show that the significant increase or decrease of certain harmonics can be used to detect short circuited turns in the machine stator.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133781136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-24DOI: 10.1109/DEMPED.2013.6645775
V. Climente-Alarcón, J. Antonino-Daviu, E. Strangas, M. Riera-Guasp
In recent years several methods have been proposed in order to detect broken bars in the cage of induction motors, yielding the necessity of testing their performance in different conditions and their thresholds in assessing incipient cage damage. This paper presents the first results of a fatigue test designed to produce in the most natural way the breakage of a bar in order to determine the effectiveness of different motor current signature analysis. The high accuracy of the transient methods based on the study of the startup current, allows proposing some physical models of the breakage with the aim of establishing the remaining life of the induction motor, once the incipient defect has been detected.
{"title":"Bar breakage mechanism and prognosis in an induction motor","authors":"V. Climente-Alarcón, J. Antonino-Daviu, E. Strangas, M. Riera-Guasp","doi":"10.1109/DEMPED.2013.6645775","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645775","url":null,"abstract":"In recent years several methods have been proposed in order to detect broken bars in the cage of induction motors, yielding the necessity of testing their performance in different conditions and their thresholds in assessing incipient cage damage. This paper presents the first results of a fatigue test designed to produce in the most natural way the breakage of a bar in order to determine the effectiveness of different motor current signature analysis. The high accuracy of the transient methods based on the study of the startup current, allows proposing some physical models of the breakage with the aim of establishing the remaining life of the induction motor, once the incipient defect has been detected.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115756740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-24DOI: 10.1109/DEMPED.2013.6645772
D. Sawitri, D. A. Asfani, M. Purnomo, I. Purnama, M. Ashari
Unbalance voltage supply in induction motor is a crucial problem. This paper proposes an original system to detect an unbalance voltage condition in induction motor using Support Vector Machine (SVM). Induction motor current, as a signal due to the unbalance voltage supply in three-phase induction motor, is recorded in lab bench. The features of recorded signals are extracted by wavelet transform and Principal Component Analysis algorithm. Then, the quality of detection is classified by SVM, and the average result of detection is 86%.
{"title":"Early detection of unbalance voltage in three phase induction motor based on SVM","authors":"D. Sawitri, D. A. Asfani, M. Purnomo, I. Purnama, M. Ashari","doi":"10.1109/DEMPED.2013.6645772","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645772","url":null,"abstract":"Unbalance voltage supply in induction motor is a crucial problem. This paper proposes an original system to detect an unbalance voltage condition in induction motor using Support Vector Machine (SVM). Induction motor current, as a signal due to the unbalance voltage supply in three-phase induction motor, is recorded in lab bench. The features of recorded signals are extracted by wavelet transform and Principal Component Analysis algorithm. Then, the quality of detection is classified by SVM, and the average result of detection is 86%.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124842360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-24DOI: 10.1109/DEMPED.2013.6645752
A. Andreičiks, I. Steiks, O. Krievs, F. Blaabjerg
In order to use hydrogen fuel cell in domestic applications either as main power supply or backup power source, the low DC output voltage of the fuel cell has to be matched to the voltage level and frequency of the utility grid AC voltage. The interfacing power converter systems usually consist of a DC/DC converter and an inverter. In this paper a detailed simulation study of such interfacing converter system comprising a double inductor push-pull step-up DC/DC converter and a cascaded H-bridge inverter has been carried out and further confirmed with experimental results. The power converter system is designed for interfacing a 2kW proton exchange membrane (PEM) fuel cell.
{"title":"Design of current source DC/DC converter and inverter for 2kW fuel cell application","authors":"A. Andreičiks, I. Steiks, O. Krievs, F. Blaabjerg","doi":"10.1109/DEMPED.2013.6645752","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645752","url":null,"abstract":"In order to use hydrogen fuel cell in domestic applications either as main power supply or backup power source, the low DC output voltage of the fuel cell has to be matched to the voltage level and frequency of the utility grid AC voltage. The interfacing power converter systems usually consist of a DC/DC converter and an inverter. In this paper a detailed simulation study of such interfacing converter system comprising a double inductor push-pull step-up DC/DC converter and a cascaded H-bridge inverter has been carried out and further confirmed with experimental results. The power converter system is designed for interfacing a 2kW proton exchange membrane (PEM) fuel cell.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125919828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-24DOI: 10.1109/DEMPED.2013.6645771
W. S. Gongora, H. V. D. Silva, A. Goedtel, W. Godoy, S. D. Silva
The induction motor has been widely used in various industrial applications. Thus, several studies have presented strategies for the diagnosis and prediction of failures in these motor. One strategy used recently is based on intelligent systems, in particular, artificial neural networks. The purpose of this paper is to present an alternative tool to traditional methods for detection of bearing failures using on a perceptron network with signal analysis in time domain. Experimental results are presented to validate the proposal.
{"title":"Neural approach for bearing fault detection in three phase induction motors","authors":"W. S. Gongora, H. V. D. Silva, A. Goedtel, W. Godoy, S. D. Silva","doi":"10.1109/DEMPED.2013.6645771","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645771","url":null,"abstract":"The induction motor has been widely used in various industrial applications. Thus, several studies have presented strategies for the diagnosis and prediction of failures in these motor. One strategy used recently is based on intelligent systems, in particular, artificial neural networks. The purpose of this paper is to present an alternative tool to traditional methods for detection of bearing failures using on a perceptron network with signal analysis in time domain. Experimental results are presented to validate the proposal.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128643596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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