Pub Date : 2013-10-24DOI: 10.1109/DEMPED.2013.6645689
Jason M. Anderson, R. Cox, Paul O'Connor
The early detection of incipient faults is desirable in mission-critical applications such as shipboard propulsion drives. This paper presents an online condition-monitoring approach for detecting early stage faults in IGBTs. The proposed algorithm extracts important device features (i.e. on-state resistance, gate charge, etc.) and compares them to healthy values recorded over a range of operating conditions. The algorithm is based on principal-components analysis (PCA). An experimental implementation in an IGBT-based drive is described, and results recorded with two different faults over a range of operating conditions are presented. The scheme integrates well with new FPGA-based gate drives and provides a powerful alternative to rules-based fault detection.
{"title":"Online algorithm for early stage fault detection in IGBT switches","authors":"Jason M. Anderson, R. Cox, Paul O'Connor","doi":"10.1109/DEMPED.2013.6645689","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645689","url":null,"abstract":"The early detection of incipient faults is desirable in mission-critical applications such as shipboard propulsion drives. This paper presents an online condition-monitoring approach for detecting early stage faults in IGBTs. The proposed algorithm extracts important device features (i.e. on-state resistance, gate charge, etc.) and compares them to healthy values recorded over a range of operating conditions. The algorithm is based on principal-components analysis (PCA). An experimental implementation in an IGBT-based drive is described, and results recorded with two different faults over a range of operating conditions are presented. The scheme integrates well with new FPGA-based gate drives and provides a powerful alternative to rules-based fault detection.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"97 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":"121461740","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.2013.6645710
Á. Sapena-Bañó, M. Pineda-Sánchez, R. Puche-Panadero, J. Roger-Folch, J. Pérez-Cruz, M. Riera-Guasp
The use of advanced diagnosis techniques for induction motor (IM) faults relies on the use of automated classifiers, such as those based on support vector machines (SVMs), which are able to assess the condition of the machine using a set of relevant features extracted either from the time domain or from the frequency domain machines signals. But the performance of such systems depends on two main factors: the quantity that is used to obtain the machine's condition, and the signal processing tool used for extract the features set. In this paper, a combination of the most used quantities and signal processing tools is used for diagnosis a set of machines with broken bars, fed from the mains and from variable speed drives, using the same SVM. In this way, the most efficient combination can be chosen, from the point of view of the performance of the automatic classifier system.
{"title":"Support vector machine for diagnosis of inductioi motors: A comparative analysis in terms of the quantity and the signal processing tool used to build the feature space","authors":"Á. Sapena-Bañó, M. Pineda-Sánchez, R. Puche-Panadero, J. Roger-Folch, J. Pérez-Cruz, M. Riera-Guasp","doi":"10.1109/DEMPED.2013.6645710","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645710","url":null,"abstract":"The use of advanced diagnosis techniques for induction motor (IM) faults relies on the use of automated classifiers, such as those based on support vector machines (SVMs), which are able to assess the condition of the machine using a set of relevant features extracted either from the time domain or from the frequency domain machines signals. But the performance of such systems depends on two main factors: the quantity that is used to obtain the machine's condition, and the signal processing tool used for extract the features set. In this paper, a combination of the most used quantities and signal processing tools is used for diagnosis a set of machines with broken bars, fed from the mains and from variable speed drives, using the same SVM. In this way, the most efficient combination can be chosen, from the point of view of the performance of the automatic classifier system.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"150 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":"115104083","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.2013.6645740
S. H. Kia, H. Henao, G. Capolino
The aim of the present work is the diagnosis of tooth surface damage fault in gears using the induction machine electrical signature analysis. The condition monitoring of gears is a crucial task due to its importance in the mechanical power transmission in industrial, aerospace and automotive applications. The vibration analysis has been commonly used as an effective tool for gear fault diagnosis in several studies. The gear torsional vibration effect in the stator current and the estimated electromagnetic torque has been previously studied based on the observation of gear mechanical characteristic frequencies in the spectrum of the load torque. This paper investigates the profile generated by a gear tooth surface damage fault in the load torque. It will be shown that the periodic behavior of this particular profile produces fault-related frequencies in the stator current and hence harmonics namely integer multiple of rotation frequency in the instantaneous frequency of the stator current space vector and the estimated electromagnetic torque. The obtained results show a possible non-invasive gear tooth surface damage fault detection with a fault sensitivity comparable to the one obtained with invasive methods. A set-up based on a 250W three-phase squirrel-cage induction machine shaft-connected to a single-stage gear has been used for this purpose.
{"title":"Gear tooth surface damage fault detection using induction machine electrical signature analysis","authors":"S. H. Kia, H. Henao, G. Capolino","doi":"10.1109/DEMPED.2013.6645740","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645740","url":null,"abstract":"The aim of the present work is the diagnosis of tooth surface damage fault in gears using the induction machine electrical signature analysis. The condition monitoring of gears is a crucial task due to its importance in the mechanical power transmission in industrial, aerospace and automotive applications. The vibration analysis has been commonly used as an effective tool for gear fault diagnosis in several studies. The gear torsional vibration effect in the stator current and the estimated electromagnetic torque has been previously studied based on the observation of gear mechanical characteristic frequencies in the spectrum of the load torque. This paper investigates the profile generated by a gear tooth surface damage fault in the load torque. It will be shown that the periodic behavior of this particular profile produces fault-related frequencies in the stator current and hence harmonics namely integer multiple of rotation frequency in the instantaneous frequency of the stator current space vector and the estimated electromagnetic torque. The obtained results show a possible non-invasive gear tooth surface damage fault detection with a fault sensitivity comparable to the one obtained with invasive methods. A set-up based on a 250W three-phase squirrel-cage induction machine shaft-connected to a single-stage gear has been used for this purpose.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"45 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":"115280678","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.2013.6645712
M. Fernández-Temprano, P. E. Gardel-Sotomayor, Ó. Duque-Pérez, D. Morinigo-Sotelo
This paper presents a procedure for broken rotor bar diagnosis in induction motors based in data extracted from stator current, which is calculated in the time and frequency domains. Data comes from a tested motor fed by different types of supply: direct line and two different Voltage Source Inverters. Diagnosis is always difficult in Voltage Source Inverter fed motors due to inherent noise level and the presence of additional non-related fault harmonics in the stator current spectrum. Moreover, the motor was tested under different load conditions, from no-load to full-load. Diagnosis is also more difficult at lower load levels. Previous to fault classification, a variable reduction was carried out using Principal Component Analysis. Fault classification was performed using Linear Discriminant Analysis. The motor was tested with different fault severities, what allowed us to perform an analysis oriented to different maintenance approaches, considering the criticality of the motor.
{"title":"Broken bar condition monitoring of an induction motor under different supplies using a linear discriminant analysis","authors":"M. Fernández-Temprano, P. E. Gardel-Sotomayor, Ó. Duque-Pérez, D. Morinigo-Sotelo","doi":"10.1109/DEMPED.2013.6645712","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645712","url":null,"abstract":"This paper presents a procedure for broken rotor bar diagnosis in induction motors based in data extracted from stator current, which is calculated in the time and frequency domains. Data comes from a tested motor fed by different types of supply: direct line and two different Voltage Source Inverters. Diagnosis is always difficult in Voltage Source Inverter fed motors due to inherent noise level and the presence of additional non-related fault harmonics in the stator current spectrum. Moreover, the motor was tested under different load conditions, from no-load to full-load. Diagnosis is also more difficult at lower load levels. Previous to fault classification, a variable reduction was carried out using Principal Component Analysis. Fault classification was performed using Linear Discriminant Analysis. The motor was tested with different fault severities, what allowed us to perform an analysis oriented to different maintenance approaches, considering the criticality of the motor.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"36 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":"129199330","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.2013.6645759
A. Hultgren, S. Bui, J. Linner, P. Ranstad, M. Lenells
A high voltage and high power fault tolerant application of a resonant converter is presented. The resonant converter load shows frequent short circuits making the load voltage drop to zero within some us, implying high stress on the main circuit components. A load voltage short circuit fault tolerant system is suggested by including a novel way of augmenting the controller with a load voltage estimator. The estimator can detect load voltage short circuit and will then be a part of a fault tolerant high voltage resonant converter.
{"title":"Fault tolerant high voltage resonant power converter application","authors":"A. Hultgren, S. Bui, J. Linner, P. Ranstad, M. Lenells","doi":"10.1109/DEMPED.2013.6645759","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645759","url":null,"abstract":"A high voltage and high power fault tolerant application of a resonant converter is presented. The resonant converter load shows frequent short circuits making the load voltage drop to zero within some us, implying high stress on the main circuit components. A load voltage short circuit fault tolerant system is suggested by including a novel way of augmenting the controller with a load voltage estimator. The estimator can detect load voltage short circuit and will then be a part of a fault tolerant high voltage resonant converter.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"41 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":"128321675","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.2013.6645761
B. Baptista, M. Abadi, A. Mendes, S. Cruz
This paper presents the results of an experimental investigation regarding the performance of a three-phase induction motor fed by a three-level neutral-point-clamped converter with fault tolerant control strategies. A discussion about the fault diagnostic method used in this work, together with the used fault tolerant control strategy is presented. Experimental results regarding the thermal, electrical and mechanical behavior of a three-phase induction machine as well as the global efficiency of the ac drive under inverter normal and post-fault reconfiguration operations are discussed.
{"title":"The performance of a three-phase induction motor fed by a three-level NPC converter with fault tolerant control strategies","authors":"B. Baptista, M. Abadi, A. Mendes, S. Cruz","doi":"10.1109/DEMPED.2013.6645761","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645761","url":null,"abstract":"This paper presents the results of an experimental investigation regarding the performance of a three-phase induction motor fed by a three-level neutral-point-clamped converter with fault tolerant control strategies. A discussion about the fault diagnostic method used in this work, together with the used fault tolerant control strategy is presented. Experimental results regarding the thermal, electrical and mechanical behavior of a three-phase induction machine as well as the global efficiency of the ac drive under inverter normal and post-fault reconfiguration operations are discussed.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"123 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":"127409963","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.2013.6645738
G. Verez, O. Bennouna, Y. Amara, G. Hoblos, G. Barakat
This paper presents an analytical model for the study of magnetic vibrations in a permanent magnet synchronous motor. The analytical model is based, for the magnetic aspect, on the magnetically coupled circuits approach widely used for modeling electrical machines under faults. This approach associated with the winding functions technique yields to a system of differential equations governing the machine. Its solution helps to compute the Maxwell stress on the stator core. An analytical mechanical model describing the structure displacement and the relied vibrations has also been developed. It is based on the resolution of the equation of motion with Flügge-Byrne-Lur'ye theory. A good agreement has been obtained between results issued from the developed analytical model with those issued from finite element analyses. Analytical models have the advantage to be more convenient for the diagnosis purpose because of the consequent reduction of the calculation time as compared to numerical methods.
{"title":"Magnetically coupled circuit based magnetic vibrations modeling of PMSM","authors":"G. Verez, O. Bennouna, Y. Amara, G. Hoblos, G. Barakat","doi":"10.1109/DEMPED.2013.6645738","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645738","url":null,"abstract":"This paper presents an analytical model for the study of magnetic vibrations in a permanent magnet synchronous motor. The analytical model is based, for the magnetic aspect, on the magnetically coupled circuits approach widely used for modeling electrical machines under faults. This approach associated with the winding functions technique yields to a system of differential equations governing the machine. Its solution helps to compute the Maxwell stress on the stator core. An analytical mechanical model describing the structure displacement and the relied vibrations has also been developed. It is based on the resolution of the equation of motion with Flügge-Byrne-Lur'ye theory. A good agreement has been obtained between results issued from the developed analytical model with those issued from finite element analyses. Analytical models have the advantage to be more convenient for the diagnosis purpose because of the consequent reduction of the calculation time as compared to numerical methods.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"6 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":"131247410","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.2013.6645745
D. F. Kavanagh, D. Howey, M. Mcculloch
Insulation is a fundamental part of electric machines as it provides suitable electrical isolation between the different parts and sub-components. Developing techniques for analysing properties of insulation is extremely useful for the assessment of operating conditions, insulation quality and degradation (state of health). This paper investigates a novel non-invasive experimental approach to characterise phase-to-phase and phase-to-ground insulation by measuring electrical impedance and derived parameters (capacitance, dissipation factor) over a wide frequency range (100 to 2 MHz) at various different temperatures. Due to its simplicity the method lends itself better to an electrostatics interpretation compared with the typical twisted pair approach. Analysis is presented for the method which show its effectiveness under different operating conditions. This work has important applications in the area of condition monitoring of insulation using impedance based measurements.
{"title":"An applied laboratory characterisation approach for electric machine insulation","authors":"D. F. Kavanagh, D. Howey, M. Mcculloch","doi":"10.1109/DEMPED.2013.6645745","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645745","url":null,"abstract":"Insulation is a fundamental part of electric machines as it provides suitable electrical isolation between the different parts and sub-components. Developing techniques for analysing properties of insulation is extremely useful for the assessment of operating conditions, insulation quality and degradation (state of health). This paper investigates a novel non-invasive experimental approach to characterise phase-to-phase and phase-to-ground insulation by measuring electrical impedance and derived parameters (capacitance, dissipation factor) over a wide frequency range (100 to 2 MHz) at various different temperatures. Due to its simplicity the method lends itself better to an electrostatics interpretation compared with the typical twisted pair approach. Analysis is presented for the method which show its effectiveness under different operating conditions. This work has important applications in the area of condition monitoring of insulation using impedance based measurements.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"26 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":"134371944","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.2013.6645708
A. J. Fernandez Gomez, T. Sobczyk
The aim of this paper is to recognize if the differences between effects due to external mechanical faults and internal electrical faults in induction motors can be diagnosed through Motor Current Signature Analysis (MCSA) techniques applying Fourier analysis. For that purpose an alternative algorithm to traditional Fast Fourier Transform was used. Positive and negative frequency spectra have been studied. The paper shows a comparison between frequency spectra of the symmetrical and natural components of stator currents for internal electrical fault (rotor cage asymmetry) and external mechanical fault represented by a periodical oscillating torque. Cage asymmetry is defined by symmetrical and asymmetrical factors. The study is based on the classical model of induction machine considering only effects of Main Magneto-motive Forces. Result shown corresponds to the steady-state performance of the motor supplied directly from the net as a sinusoidal voltage source. The advantages of the algorithm use for Fourier analysis have also been discussed.
{"title":"Motor current signature analysis apply for external mechanical fault and cage asymmetry in induction motors","authors":"A. J. Fernandez Gomez, T. Sobczyk","doi":"10.1109/DEMPED.2013.6645708","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645708","url":null,"abstract":"The aim of this paper is to recognize if the differences between effects due to external mechanical faults and internal electrical faults in induction motors can be diagnosed through Motor Current Signature Analysis (MCSA) techniques applying Fourier analysis. For that purpose an alternative algorithm to traditional Fast Fourier Transform was used. Positive and negative frequency spectra have been studied. The paper shows a comparison between frequency spectra of the symmetrical and natural components of stator currents for internal electrical fault (rotor cage asymmetry) and external mechanical fault represented by a periodical oscillating torque. Cage asymmetry is defined by symmetrical and asymmetrical factors. The study is based on the classical model of induction machine considering only effects of Main Magneto-motive Forces. Result shown corresponds to the steady-state performance of the motor supplied directly from the net as a sinusoidal voltage source. The advantages of the algorithm use for Fourier analysis have also been discussed.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"75 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":"133036120","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.2013.6645748
D. Matic, Ž. Kanović, D. Reljic, F. Kulić, D. Oros, V. Vasic
This paper covers a case study of broken bar detection for 3.15 MW motor in a thermal power plant application. The motor current is measured in one phase. Feature extraction is based on transient and steady state analysis. Hilbert and Wavelet transforms are used to extract broken bar features. To discuss rotor condition in time domain skewness and kurtosis of current envelope are also considered. Low shaft-load conditions are present. In case of high-voltage, high-power induction motor reliable broken bar detection is possible when contemporary digital signal processing techniques are used.
{"title":"Broken bar detection using current analysis — A case study","authors":"D. Matic, Ž. Kanović, D. Reljic, F. Kulić, D. Oros, V. Vasic","doi":"10.1109/DEMPED.2013.6645748","DOIUrl":"https://doi.org/10.1109/DEMPED.2013.6645748","url":null,"abstract":"This paper covers a case study of broken bar detection for 3.15 MW motor in a thermal power plant application. The motor current is measured in one phase. Feature extraction is based on transient and steady state analysis. Hilbert and Wavelet transforms are used to extract broken bar features. To discuss rotor condition in time domain skewness and kurtosis of current envelope are also considered. Low shaft-load conditions are present. In case of high-voltage, high-power induction motor reliable broken bar detection is possible when contemporary digital signal processing techniques are used.","PeriodicalId":425644,"journal":{"name":"2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)","volume":"75 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":"115133941","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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