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Statistical features analysis of transient current signal for broken bars fault detection in LS-PMSMs

Electrical motors constitute critical elements in certain industrial facilities and domestic fields as a prime mover. In spite of its good trait, failures in electrical motor cannot be impeded because it is mainly working in the industrial field. LS-PMSM is a high efficiency motor introduced recentl...

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Main Authors: Mehrjou, Mohammad Rezazadeh, Mariun, Norman, Karami, Mahdi, Misron, Norhisam, Mohd Radzi, Mohd Amran
Format: Conference or Workshop Item
Language:English
Published: IEEE 2015
Online Access:http://psasir.upm.edu.my/id/eprint/55674/1/Statistical%20features%20analysis%20of%20transient%20current%20signal%20for%20broken%20bars%20fault%20detection%20in%20LS-PMSMs.pdf
http://psasir.upm.edu.my/id/eprint/55674/
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spelling my.upm.eprints.556742017-06-07T04:52:22Z http://psasir.upm.edu.my/id/eprint/55674/ Statistical features analysis of transient current signal for broken bars fault detection in LS-PMSMs Mehrjou, Mohammad Rezazadeh Mariun, Norman Karami, Mahdi Misron, Norhisam Mohd Radzi, Mohd Amran Electrical motors constitute critical elements in certain industrial facilities and domestic fields as a prime mover. In spite of its good trait, failures in electrical motor cannot be impeded because it is mainly working in the industrial field. LS-PMSM is a high efficiency motor introduced recently in industrial field. LS-PMSM is a hybrid motor, which its rotor is combination of squirrel-cage rotor and high energy permanent magnets to have high starting torque and high efficiency together. Similar to other types of electrical motors, various faults that lead to malfunction of the motor occur in LS-PMSM during its operation. In this context, investigates diagnostic techniques for LS-PMSM with special reference to rotor faults. Since LS-PMSM has squirrel cage rotor, among different faults may happen in it, broken bar is the most important one. This paper deal with the finite element method to investigation of broken rotor bar faults on LS-PMSM with statistical feature analysis in the time domain using transient current signal. IEEE 2015 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/55674/1/Statistical%20features%20analysis%20of%20transient%20current%20signal%20for%20broken%20bars%20fault%20detection%20in%20LS-PMSMs.pdf Mehrjou, Mohammad Rezazadeh and Mariun, Norman and Karami, Mahdi and Misron, Norhisam and Mohd Radzi, Mohd Amran (2015) Statistical features analysis of transient current signal for broken bars fault detection in LS-PMSMs. In: 2015 IEEE 3rd International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA 2015), 24-25 Nov. 2015, Putrajaya, Malaysia. . 10.1109/ICSIMA.2015.7559034
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 Electrical motors constitute critical elements in certain industrial facilities and domestic fields as a prime mover. In spite of its good trait, failures in electrical motor cannot be impeded because it is mainly working in the industrial field. LS-PMSM is a high efficiency motor introduced recently in industrial field. LS-PMSM is a hybrid motor, which its rotor is combination of squirrel-cage rotor and high energy permanent magnets to have high starting torque and high efficiency together. Similar to other types of electrical motors, various faults that lead to malfunction of the motor occur in LS-PMSM during its operation. In this context, investigates diagnostic techniques for LS-PMSM with special reference to rotor faults. Since LS-PMSM has squirrel cage rotor, among different faults may happen in it, broken bar is the most important one. This paper deal with the finite element method to investigation of broken rotor bar faults on LS-PMSM with statistical feature analysis in the time domain using transient current signal.
format Conference or Workshop Item
author Mehrjou, Mohammad Rezazadeh
Mariun, Norman
Karami, Mahdi
Misron, Norhisam
Mohd Radzi, Mohd Amran
spellingShingle Mehrjou, Mohammad Rezazadeh
Mariun, Norman
Karami, Mahdi
Misron, Norhisam
Mohd Radzi, Mohd Amran
Statistical features analysis of transient current signal for broken bars fault detection in LS-PMSMs
author_facet Mehrjou, Mohammad Rezazadeh
Mariun, Norman
Karami, Mahdi
Misron, Norhisam
Mohd Radzi, Mohd Amran
author_sort Mehrjou, Mohammad Rezazadeh
title Statistical features analysis of transient current signal for broken bars fault detection in LS-PMSMs
title_short Statistical features analysis of transient current signal for broken bars fault detection in LS-PMSMs
title_full Statistical features analysis of transient current signal for broken bars fault detection in LS-PMSMs
title_fullStr Statistical features analysis of transient current signal for broken bars fault detection in LS-PMSMs
title_full_unstemmed Statistical features analysis of transient current signal for broken bars fault detection in LS-PMSMs
title_sort statistical features analysis of transient current signal for broken bars fault detection in ls-pmsms
publisher IEEE
publishDate 2015
url http://psasir.upm.edu.my/id/eprint/55674/1/Statistical%20features%20analysis%20of%20transient%20current%20signal%20for%20broken%20bars%20fault%20detection%20in%20LS-PMSMs.pdf
http://psasir.upm.edu.my/id/eprint/55674/
_version_ 1643835964206874624
score 13.211869

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