Generalized Roughness Bearing Faults Diagnosis Based on Induction Motor Stator Current
Despite their reliability, induction motors tend to fail. Around 41% of faults in motors are bearing related and that is the most common fault in motor field. Due to the lack of research on generalized roughness bearing fault diagnostics by use of a stator current spectrum, the presented study analy...
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Spolecnost pro radioelektronicke inzenyrstvi
2018-12-01
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Online Access: | https://www.radioeng.cz/fulltexts/2018/18_04_1166_1173.pdf |
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doaj-e54dd94f517f48139b663e5d35d900682020-11-24T21:18:05ZengSpolecnost pro radioelektronicke inzenyrstviRadioengineering1210-25122018-12-0127411661173Generalized Roughness Bearing Faults Diagnosis Based on Induction Motor Stator CurrentI. AndrijauskasM. VaitkunasR. AdaskeviciusDespite their reliability, induction motors tend to fail. Around 41% of faults in motors are bearing related and that is the most common fault in motor field. Due to the lack of research on generalized roughness bearing fault diagnostics by use of a stator current spectrum, the presented study analyses both single-point and generalized roughness bearing faults and their classification possibilities. In this paper, a new method for generalized roughness ball bearing fault identification by use of a stator current signal analysis is presented. The algorithm relies on Discrete Wavelet Transform and Welch's spectral density analysis. The composition of both methods is used for building a feature vector for the classifier. In order to achieve classification, support vector machine classifier with linear kernel function has been applied. The validation experiment and results are presented.https://www.radioeng.cz/fulltexts/2018/18_04_1166_1173.pdfInduction motorstator current spectrumwavelet decompositionWelch’s spectral densitybearing fault diagnosis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
I. Andrijauskas M. Vaitkunas R. Adaskevicius |
spellingShingle |
I. Andrijauskas M. Vaitkunas R. Adaskevicius Generalized Roughness Bearing Faults Diagnosis Based on Induction Motor Stator Current Radioengineering Induction motor stator current spectrum wavelet decomposition Welch’s spectral density bearing fault diagnosis |
author_facet |
I. Andrijauskas M. Vaitkunas R. Adaskevicius |
author_sort |
I. Andrijauskas |
title |
Generalized Roughness Bearing Faults Diagnosis Based on Induction Motor Stator Current |
title_short |
Generalized Roughness Bearing Faults Diagnosis Based on Induction Motor Stator Current |
title_full |
Generalized Roughness Bearing Faults Diagnosis Based on Induction Motor Stator Current |
title_fullStr |
Generalized Roughness Bearing Faults Diagnosis Based on Induction Motor Stator Current |
title_full_unstemmed |
Generalized Roughness Bearing Faults Diagnosis Based on Induction Motor Stator Current |
title_sort |
generalized roughness bearing faults diagnosis based on induction motor stator current |
publisher |
Spolecnost pro radioelektronicke inzenyrstvi |
series |
Radioengineering |
issn |
1210-2512 |
publishDate |
2018-12-01 |
description |
Despite their reliability, induction motors tend to fail. Around 41% of faults in motors are bearing related and that is the most common fault in motor field. Due to the lack of research on generalized roughness bearing fault diagnostics by use of a stator current spectrum, the presented study analyses both single-point and generalized roughness bearing faults and their classification possibilities. In this paper, a new method for generalized roughness ball bearing fault identification by use of a stator current signal analysis is presented. The algorithm relies on Discrete Wavelet Transform and Welch's spectral density analysis. The composition of both methods is used for building a feature vector for the classifier. In order to achieve classification, support vector machine classifier with linear kernel function has been applied. The validation experiment and results are presented. |
topic |
Induction motor stator current spectrum wavelet decomposition Welch’s spectral density bearing fault diagnosis |
url |
https://www.radioeng.cz/fulltexts/2018/18_04_1166_1173.pdf |
work_keys_str_mv |
AT iandrijauskas generalizedroughnessbearingfaultsdiagnosisbasedoninductionmotorstatorcurrent AT mvaitkunas generalizedroughnessbearingfaultsdiagnosisbasedoninductionmotorstatorcurrent AT radaskevicius generalizedroughnessbearingfaultsdiagnosisbasedoninductionmotorstatorcurrent |
_version_ |
1726010409331195904 |