Pub Date : 2009-10-23DOI: 10.1109/DEMPED.2009.5292754
C. Bruzzese
This work reports an actual case of multiple-constraint engineering problem, risen when a suitable inverter control has been planned for Italian High-Frequentation Train drives (Treni Alta Frequentazione - TAF). GTO inverters produced harmful harmonic torques in the motor, and harmful harmonic interference with the signal-repetition system. Since switching frequencies should be moved up to solve the first problem and down to solve the second, an optimization problem rose involving mechanical and electrical systems. In this paper the on-field problems related to motor-converter interconnection are described, with particular reference to motor cage failure eventualities minimization by proper inverter control design combined with proper cage design. The case-study is described with simulations of the drive, and the optimization work is explained and discussed.
本文报告了一个多约束工程问题的实际案例，该问题是在为意大利高频列车驱动器(Treni Alta Frequentazione - TAF)规划合适的逆变器控制时出现的。GTO逆变器在电机中产生有害谐波转矩，并对信号重复系统产生有害谐波干扰。为了解决第一个问题，开关频率应该向上移动，为了解决第二个问题，开关频率应该向下移动，这就产生了一个涉及机械和电气系统的优化问题。本文描述了与电机-变换器互连相关的现场问题，特别是通过适当的变频器控制设计结合适当的保持架设计来最小化电机保持架故障的可能性。通过对传动系统的仿真，对优化工作进行了说明和讨论。
{"title":"Minimization of harmful cage torsional resonances in traction motors by a combined mechanic-electronic optimization","authors":"C. Bruzzese","doi":"10.1109/DEMPED.2009.5292754","DOIUrl":"https://doi.org/10.1109/DEMPED.2009.5292754","url":null,"abstract":"This work reports an actual case of multiple-constraint engineering problem, risen when a suitable inverter control has been planned for Italian High-Frequentation Train drives (Treni Alta Frequentazione - TAF). GTO inverters produced harmful harmonic torques in the motor, and harmful harmonic interference with the signal-repetition system. Since switching frequencies should be moved up to solve the first problem and down to solve the second, an optimization problem rose involving mechanical and electrical systems. In this paper the on-field problems related to motor-converter interconnection are described, with particular reference to motor cage failure eventualities minimization by proper inverter control design combined with proper cage design. The case-study is described with simulations of the drive, and the optimization work is explained and discussed.","PeriodicalId":405777,"journal":{"name":"2009 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116937522","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 : 2009-10-23DOI: 10.1109/DEMPED.2009.5292765
E. D. Wandekokem, Frederico Thomaz de Aquino Franzosi, T. Rauber, F. M. Varejão, R. J. Batista
We report about fault diagnosis experiments to improve the maintenance quality of motor pumps installed on oil rigs. We rely on the data-driven approach to the learning of the fault classes, i.e. supervised learning in pattern recognition. Features are extracted from the vibration signals to detect and diagnose misalignment and mechanical looseness problems. We show the results of automatic pattern recognition methods to define and select features that describe the faults of the provided examples. The support vector machine is chosen as the classification architecture.
{"title":"Data-driven fault diagnosis of oil rig motor pumps applying automatic definition and selection of features","authors":"E. D. Wandekokem, Frederico Thomaz de Aquino Franzosi, T. Rauber, F. M. Varejão, R. J. Batista","doi":"10.1109/DEMPED.2009.5292765","DOIUrl":"https://doi.org/10.1109/DEMPED.2009.5292765","url":null,"abstract":"We report about fault diagnosis experiments to improve the maintenance quality of motor pumps installed on oil rigs. We rely on the data-driven approach to the learning of the fault classes, i.e. supervised learning in pattern recognition. Features are extracted from the vibration signals to detect and diagnose misalignment and mechanical looseness problems. We show the results of automatic pattern recognition methods to define and select features that describe the faults of the provided examples. The support vector machine is chosen as the classification architecture.","PeriodicalId":405777,"journal":{"name":"2009 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122923056","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 : 2009-10-23DOI: 10.1109/DEMPED.2009.5292795
F. Waldhart, J. Bacher
There are various methods to determine the efficiency of three phase induction machines. But all of them have in common that they are too inaccurate or they are impracticable. In this paper the machine efficiency will be derived from start up data. For that purpose the time dependence of all stator currents and all stator voltages have to be measured. Normally it isn't possible to mount a speed sensor on the machine. Therefore, only the speed at the end of the start up can be determined. Practical results with standard three phase induction machines with different power ranges from 3 kW up to 500 kW are presented.
{"title":"Online efficiency determination of three phase asynchronous machines by start-up data","authors":"F. Waldhart, J. Bacher","doi":"10.1109/DEMPED.2009.5292795","DOIUrl":"https://doi.org/10.1109/DEMPED.2009.5292795","url":null,"abstract":"There are various methods to determine the efficiency of three phase induction machines. But all of them have in common that they are too inaccurate or they are impracticable. In this paper the machine efficiency will be derived from start up data. For that purpose the time dependence of all stator currents and all stator voltages have to be measured. Normally it isn't possible to mount a speed sensor on the machine. Therefore, only the speed at the end of the start up can be determined. Practical results with standard three phase induction machines with different power ranges from 3 kW up to 500 kW are presented.","PeriodicalId":405777,"journal":{"name":"2009 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128387341","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 : 2009-10-23DOI: 10.1109/DEMPED.2009.5292759
T. G. Arora, M. Aware, D. Tutakne
Thyristor based, phase angle controlled, speed regulators are widely used for energy efficient control of single-phase induction motors. This leads to power saving but adversely affects the life of insulation in the motors due to distortions in the applied voltage and current waveforms. The accelerated insulation ageing is due to increased voltage peaks, voltage transients and increased thermal stress. Voltage harmonics increase dielectric and core losses. Current peaks increase the thermal stress in the insulation. This paper presents the application of fuzzy logic system to life estimation of the insulation of phase angle controlled single-phase induction motors. Three basic insulation degradation parameters; voltage peaks, rate of rise of voltage and thermal stress are used for life estimation. The results obtained with the fuzzy expert system for the set of experiments show a performance approaching that attainable for the life model based on the inverse power law.
{"title":"Fuzzy logic application to life estimation of phase angle controlled induction motors","authors":"T. G. Arora, M. Aware, D. Tutakne","doi":"10.1109/DEMPED.2009.5292759","DOIUrl":"https://doi.org/10.1109/DEMPED.2009.5292759","url":null,"abstract":"Thyristor based, phase angle controlled, speed regulators are widely used for energy efficient control of single-phase induction motors. This leads to power saving but adversely affects the life of insulation in the motors due to distortions in the applied voltage and current waveforms. The accelerated insulation ageing is due to increased voltage peaks, voltage transients and increased thermal stress. Voltage harmonics increase dielectric and core losses. Current peaks increase the thermal stress in the insulation. This paper presents the application of fuzzy logic system to life estimation of the insulation of phase angle controlled single-phase induction motors. Three basic insulation degradation parameters; voltage peaks, rate of rise of voltage and thermal stress are used for life estimation. The results obtained with the fuzzy expert system for the set of experiments show a performance approaching that attainable for the life model based on the inverse power law.","PeriodicalId":405777,"journal":{"name":"2009 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives","volume":"244 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130694185","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 : 2009-10-23DOI: 10.1109/DEMPED.2009.5292800
I. Jaksch, P. Fuchs
Demodulation techniques extract modulating currents induced by induction motors rotor faults and directly evaluate these fault currents in time and frequency domain. Vector representation of amplitude and phase modulation is analyzed with the investigation, how both modulations change with changing parameters. It is proved that fault indicators of amplitude modulation do not change with motor changing parameters and they are the base of rotor faults detection. Two demodulation methods based on complex analytical signal are presented. Experiments were focused to IM energized from line and inverters.
{"title":"Demodulation analysis for exact rotor faults detection under changing parameters","authors":"I. Jaksch, P. Fuchs","doi":"10.1109/DEMPED.2009.5292800","DOIUrl":"https://doi.org/10.1109/DEMPED.2009.5292800","url":null,"abstract":"Demodulation techniques extract modulating currents induced by induction motors rotor faults and directly evaluate these fault currents in time and frequency domain. Vector representation of amplitude and phase modulation is analyzed with the investigation, how both modulations change with changing parameters. It is proved that fault indicators of amplitude modulation do not change with motor changing parameters and they are the base of rotor faults detection. Two demodulation methods based on complex analytical signal are presented. Experiments were focused to IM energized from line and inverters.","PeriodicalId":405777,"journal":{"name":"2009 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133229312","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 : 2009-10-23DOI: 10.1109/DEMPED.2009.5292752
K. Rothenhagen, F. Fuchs
Fault tolerance is gaining interest as a means to increase the reliability and availability of distributed energy systems. In this paper, a voltage-oriented Doubly-Fed Induction Generator is examined. This work applies formerly developped model based sensor fault tolerant control methods to gain and offset faults. For that reason, saturation is modelled. Fault detection is triggered by residuals. Fault isolation determines the faulty sensor. Replacement signals from observers are used to reconfigure the drive and re-enter closed loop control. While model based FDI for these faults is generally possible, it requires the fault to be large enough to be detectable.
{"title":"Model-based fault detection of gain and offset faults in Doubly Fed Induction Generators","authors":"K. Rothenhagen, F. Fuchs","doi":"10.1109/DEMPED.2009.5292752","DOIUrl":"https://doi.org/10.1109/DEMPED.2009.5292752","url":null,"abstract":"Fault tolerance is gaining interest as a means to increase the reliability and availability of distributed energy systems. In this paper, a voltage-oriented Doubly-Fed Induction Generator is examined. This work applies formerly developped model based sensor fault tolerant control methods to gain and offset faults. For that reason, saturation is modelled. Fault detection is triggered by residuals. Fault isolation determines the faulty sensor. Replacement signals from observers are used to reconfigure the drive and re-enter closed loop control. While model based FDI for these faults is generally possible, it requires the fault to be large enough to be detectable.","PeriodicalId":405777,"journal":{"name":"2009 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127860396","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 : 2009-10-23DOI: 10.1109/DEMPED.2009.5292768
Y. Aksenov, I. Yaroshenko, G. Noe, A. V. Andreev
This paper contains summary information on Diacs technology principles comprising the following subjects: power transformers on-line testing and defects location procedure; on-line diagnostic technology and data analysis; examples of test results. Possible failure scenarios are observed here, as well as general tools available for power transformer life assessment. Specific technology of Diagnostic Methods Synergy for transformer insulation analysis is described in the paper, one the most important components of which are methods of Double-Coordinate Location and n(Q) distribution analysis, on-line PD location, gas-in-oil analysis, thermovision.
{"title":"Diagnostic technology for transformers: Methods synergy and Double-Coordinate Location","authors":"Y. Aksenov, I. Yaroshenko, G. Noe, A. V. Andreev","doi":"10.1109/DEMPED.2009.5292768","DOIUrl":"https://doi.org/10.1109/DEMPED.2009.5292768","url":null,"abstract":"This paper contains summary information on Diacs technology principles comprising the following subjects: power transformers on-line testing and defects location procedure; on-line diagnostic technology and data analysis; examples of test results. Possible failure scenarios are observed here, as well as general tools available for power transformer life assessment. Specific technology of Diagnostic Methods Synergy for transformer insulation analysis is described in the paper, one the most important components of which are methods of Double-Coordinate Location and n(Q) distribution analysis, on-line PD location, gas-in-oil analysis, thermovision.","PeriodicalId":405777,"journal":{"name":"2009 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130603219","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 : 2009-10-23DOI: 10.1109/DEMPED.2009.5292788
F. Charfi, S. Lesecq, F. Sellami
This paper presents a new methodology for fault detection and identification in power system drives. The stationary wavelet transform is the tool used through the analysis of the three phase stator current signals measured at the stator of an induction machine fed by a three phase voltage inverter. Fault scenarios with one open-switch are considered because they are the most likely to occur. Several signals are analysed simultaneously in order to perform the diagnosis. The currents signals are filtered using the SWT performed with the DB4 wavelet to extract the detail and approximation coefficients up to level 6. Then, the approximation at level 6 is examined to detect changes in the mean. This is achieved with statistical hypothesis techniques. In this work, a Neyman Pearson change in the mean detection test is used. Finally, a signature table is deduced to isolate the faulty switch. The whole diagnostic procedure can perform on line because of its low computational cost. Real data recorded from a benchmark feed the proposed diagnostic tool. Presented results confirm the effectiveness of the proposed methodology.
{"title":"Fault diagnosis using SWT and Neyman Pearson detection tests","authors":"F. Charfi, S. Lesecq, F. Sellami","doi":"10.1109/DEMPED.2009.5292788","DOIUrl":"https://doi.org/10.1109/DEMPED.2009.5292788","url":null,"abstract":"This paper presents a new methodology for fault detection and identification in power system drives. The stationary wavelet transform is the tool used through the analysis of the three phase stator current signals measured at the stator of an induction machine fed by a three phase voltage inverter. Fault scenarios with one open-switch are considered because they are the most likely to occur. Several signals are analysed simultaneously in order to perform the diagnosis. The currents signals are filtered using the SWT performed with the DB4 wavelet to extract the detail and approximation coefficients up to level 6. Then, the approximation at level 6 is examined to detect changes in the mean. This is achieved with statistical hypothesis techniques. In this work, a Neyman Pearson change in the mean detection test is used. Finally, a signature table is deduced to isolate the faulty switch. The whole diagnostic procedure can perform on line because of its low computational cost. Real data recorded from a benchmark feed the proposed diagnostic tool. Presented results confirm the effectiveness of the proposed methodology.","PeriodicalId":405777,"journal":{"name":"2009 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130670586","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 : 2009-10-23DOI: 10.1109/DEMPED.2009.5292798
Guillermo R. Bossio, C. D. de Angelo, C. Pezzani, J. Bossio, G. García
Effects of rotor faults on stator currents in induction motors are studied in the present work. Particularly, the effects of such faults on the sidebands at fundamental and harmonics current components are analyzed. A multiple-coupled circuit model determines the variation of amplitude of these sidebands as a function of the number of broken bars, load and motor-load inertia. The results obtained from this analysis allow improving the rotor fault diagnosis techniques and identifying and separating rotor faults from others. Simulation and experimental results are presented to validate the proposal.
{"title":"Evaluation of harmonic current sidebands for broken bar diagnosis in induction motors","authors":"Guillermo R. Bossio, C. D. de Angelo, C. Pezzani, J. Bossio, G. García","doi":"10.1109/DEMPED.2009.5292798","DOIUrl":"https://doi.org/10.1109/DEMPED.2009.5292798","url":null,"abstract":"Effects of rotor faults on stator currents in induction motors are studied in the present work. Particularly, the effects of such faults on the sidebands at fundamental and harmonics current components are analyzed. A multiple-coupled circuit model determines the variation of amplitude of these sidebands as a function of the number of broken bars, load and motor-load inertia. The results obtained from this analysis allow improving the rotor fault diagnosis techniques and identifying and separating rotor faults from others. Simulation and experimental results are presented to validate the proposal.","PeriodicalId":405777,"journal":{"name":"2009 IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives","volume":"70 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131490420","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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