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Broken rotor bar detection in LS-PMSM based on startup current analysis using wavelet entropy features

High-efficiency motors are being gradually introduced in many industrial applications because of their positive impacts on the environment by reducing energy consumption and CO2emission. In this respect, line start permanent magnet synchronous motors (LS-PMSMs) have been introduced recently.Due to t...

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Main Authors: Mehrjou, Mohammad Rezazadeh, Mariun, Norman, Misron, Norhisam, Mohd Radzi, Mohd Amran, Musa, Suleiman
Format: Article
Language:English
Published: MDPI 2017
Online Access:http://psasir.upm.edu.my/id/eprint/61030/1/Broken%20rotor%20bar%20detection%20in%20LS-PMSM%20based%20on%20startup%20current%20analysis%20using%20wavelet%20entropy%20features.pdf
http://psasir.upm.edu.my/id/eprint/61030/
https://pdfs.semanticscholar.org/cc13/6a98056267b217e32d8ea99f07d1598dbba4.pdf
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spelling my.upm.eprints.610302019-05-06T01:53:46Z http://psasir.upm.edu.my/id/eprint/61030/ Broken rotor bar detection in LS-PMSM based on startup current analysis using wavelet entropy features Mehrjou, Mohammad Rezazadeh Mariun, Norman Misron, Norhisam Mohd Radzi, Mohd Amran Musa, Suleiman High-efficiency motors are being gradually introduced in many industrial applications because of their positive impacts on the environment by reducing energy consumption and CO2emission. In this respect, line start permanent magnet synchronous motors (LS-PMSMs) have been introduced recently.Due to their unique configuration, LS-PMSMs allow the obtaining of super premium efficiency levels,accompanied with a high torque and power factor. However, since the use of LS-PMSMs in the industry is in its infancy, no efficient scheme has yet been reported for broken rotor bar (BRB) fault detection in this type of motor. Accordingly, the main aim of this research is to investigate the fault-related feature for BRB faults on LS-PMSMs. In this regard, a simulation model and experimental setup for the investigation of BRB in LS-PMSM are implemented. The detection strategy for BRB in LS-PMSM proposed here is based on the monitoring of the start-up current signal and discrete wavelet transform. The entropy features are used as fault-related features for BRB faults. Finally, the ability of these features is validated for the detection of BRB in LS-PMSM through statistical analysis. In this research, the importance of the starting load is also considered for BRB detection in LS-PMSMs. MDPI 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/61030/1/Broken%20rotor%20bar%20detection%20in%20LS-PMSM%20based%20on%20startup%20current%20analysis%20using%20wavelet%20entropy%20features.pdf Mehrjou, Mohammad Rezazadeh and Mariun, Norman and Misron, Norhisam and Mohd Radzi, Mohd Amran and Musa, Suleiman (2017) Broken rotor bar detection in LS-PMSM based on startup current analysis using wavelet entropy features. Applied Sciences, 7 (8). pp. 1-20. ISSN 2076-3417 https://pdfs.semanticscholar.org/cc13/6a98056267b217e32d8ea99f07d1598dbba4.pdf 10.3390/app7080845
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description High-efficiency motors are being gradually introduced in many industrial applications because of their positive impacts on the environment by reducing energy consumption and CO2emission. In this respect, line start permanent magnet synchronous motors (LS-PMSMs) have been introduced recently.Due to their unique configuration, LS-PMSMs allow the obtaining of super premium efficiency levels,accompanied with a high torque and power factor. However, since the use of LS-PMSMs in the industry is in its infancy, no efficient scheme has yet been reported for broken rotor bar (BRB) fault detection in this type of motor. Accordingly, the main aim of this research is to investigate the fault-related feature for BRB faults on LS-PMSMs. In this regard, a simulation model and experimental setup for the investigation of BRB in LS-PMSM are implemented. The detection strategy for BRB in LS-PMSM proposed here is based on the monitoring of the start-up current signal and discrete wavelet transform. The entropy features are used as fault-related features for BRB faults. Finally, the ability of these features is validated for the detection of BRB in LS-PMSM through statistical analysis. In this research, the importance of the starting load is also considered for BRB detection in LS-PMSMs.
format Article
author Mehrjou, Mohammad Rezazadeh
Mariun, Norman
Misron, Norhisam
Mohd Radzi, Mohd Amran
Musa, Suleiman
spellingShingle Mehrjou, Mohammad Rezazadeh
Mariun, Norman
Misron, Norhisam
Mohd Radzi, Mohd Amran
Musa, Suleiman
Broken rotor bar detection in LS-PMSM based on startup current analysis using wavelet entropy features
author_facet Mehrjou, Mohammad Rezazadeh
Mariun, Norman
Misron, Norhisam
Mohd Radzi, Mohd Amran
Musa, Suleiman
author_sort Mehrjou, Mohammad Rezazadeh
title Broken rotor bar detection in LS-PMSM based on startup current analysis using wavelet entropy features
title_short Broken rotor bar detection in LS-PMSM based on startup current analysis using wavelet entropy features
title_full Broken rotor bar detection in LS-PMSM based on startup current analysis using wavelet entropy features
title_fullStr Broken rotor bar detection in LS-PMSM based on startup current analysis using wavelet entropy features
title_full_unstemmed Broken rotor bar detection in LS-PMSM based on startup current analysis using wavelet entropy features
title_sort broken rotor bar detection in ls-pmsm based on startup current analysis using wavelet entropy features
publisher MDPI
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/61030/1/Broken%20rotor%20bar%20detection%20in%20LS-PMSM%20based%20on%20startup%20current%20analysis%20using%20wavelet%20entropy%20features.pdf
http://psasir.upm.edu.my/id/eprint/61030/
https://pdfs.semanticscholar.org/cc13/6a98056267b217e32d8ea99f07d1598dbba4.pdf
_version_ 1643837489533681664
score 13.211869

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