Detection and diagnosis of motor stator faults using electric signals from variable speed drives

Abdulkarim Shaeboub, Samieh Abusaad, Niaoqing Hu, Fengshou Gu, Andrew Ball

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Motor current signature analysis has been investigated widely for diagnosing faults of induction motors. However, most of these studies are based on open loop drives. This paper examines the performance of diagnosing motor stator faults under both open and closed loop operation modes. It examines the effectiveness of conventional diagnosis features in both motor current and voltage signals using spectrum analysis. Evaluation results show that the stator fault causes an increase in the sideband amplitude of motor current signature only when the motor is under the open loop control. However, the increase inside bands can be observed in both the current and voltage signals under the sensorless control mode, showing that it is more promising in diagnosing the stator faults under the sensorless control operation.
LanguageEnglish
Title of host publicationProceedings of the 21st International Conference on Automation & Computing
PublisherIEEE
Number of pages6
ISBN (Electronic)9780992680114, 9780992680107
DOIs
Publication statusPublished - 2 Nov 2015
Event21st International Conference on Automation and Computing: Automation, Computing and Manufacturing for New Economic Growth - University of Strathclyde, Glasgow, United Kingdom
Duration: 11 Sep 201512 Sep 2015
Conference number: 21
https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7301994 (Link to Conference Proceedings)

Conference

Conference21st International Conference on Automation and Computing
Abbreviated titleICAC
CountryUnited Kingdom
CityGlasgow
Period11/09/1512/09/15
Internet address

Fingerprint

Variable speed drives
Electric fault currents
Stators
Electric potential
Induction motors
Spectrum analysis

Cite this

Shaeboub, A., Abusaad, S., Hu, N., Gu, F., & Ball, A. (2015). Detection and diagnosis of motor stator faults using electric signals from variable speed drives. In Proceedings of the 21st International Conference on Automation & Computing IEEE. https://doi.org/10.1109/IConAC.2015.7313938
Shaeboub, Abdulkarim ; Abusaad, Samieh ; Hu, Niaoqing ; Gu, Fengshou ; Ball, Andrew. / Detection and diagnosis of motor stator faults using electric signals from variable speed drives. Proceedings of the 21st International Conference on Automation & Computing. IEEE, 2015.
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title = "Detection and diagnosis of motor stator faults using electric signals from variable speed drives",
abstract = "Motor current signature analysis has been investigated widely for diagnosing faults of induction motors. However, most of these studies are based on open loop drives. This paper examines the performance of diagnosing motor stator faults under both open and closed loop operation modes. It examines the effectiveness of conventional diagnosis features in both motor current and voltage signals using spectrum analysis. Evaluation results show that the stator fault causes an increase in the sideband amplitude of motor current signature only when the motor is under the open loop control. However, the increase inside bands can be observed in both the current and voltage signals under the sensorless control mode, showing that it is more promising in diagnosing the stator faults under the sensorless control operation.",
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author = "Abdulkarim Shaeboub and Samieh Abusaad and Niaoqing Hu and Fengshou Gu and Andrew Ball",
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Shaeboub, A, Abusaad, S, Hu, N, Gu, F & Ball, A 2015, Detection and diagnosis of motor stator faults using electric signals from variable speed drives. in Proceedings of the 21st International Conference on Automation & Computing. IEEE, 21st International Conference on Automation and Computing, Glasgow, United Kingdom, 11/09/15. https://doi.org/10.1109/IConAC.2015.7313938

Detection and diagnosis of motor stator faults using electric signals from variable speed drives. / Shaeboub, Abdulkarim; Abusaad, Samieh; Hu, Niaoqing; Gu, Fengshou; Ball, Andrew.

Proceedings of the 21st International Conference on Automation & Computing. IEEE, 2015.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Detection and diagnosis of motor stator faults using electric signals from variable speed drives

AU - Shaeboub, Abdulkarim

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AU - Hu, Niaoqing

AU - Gu, Fengshou

AU - Ball, Andrew

PY - 2015/11/2

Y1 - 2015/11/2

N2 - Motor current signature analysis has been investigated widely for diagnosing faults of induction motors. However, most of these studies are based on open loop drives. This paper examines the performance of diagnosing motor stator faults under both open and closed loop operation modes. It examines the effectiveness of conventional diagnosis features in both motor current and voltage signals using spectrum analysis. Evaluation results show that the stator fault causes an increase in the sideband amplitude of motor current signature only when the motor is under the open loop control. However, the increase inside bands can be observed in both the current and voltage signals under the sensorless control mode, showing that it is more promising in diagnosing the stator faults under the sensorless control operation.

AB - Motor current signature analysis has been investigated widely for diagnosing faults of induction motors. However, most of these studies are based on open loop drives. This paper examines the performance of diagnosing motor stator faults under both open and closed loop operation modes. It examines the effectiveness of conventional diagnosis features in both motor current and voltage signals using spectrum analysis. Evaluation results show that the stator fault causes an increase in the sideband amplitude of motor current signature only when the motor is under the open loop control. However, the increase inside bands can be observed in both the current and voltage signals under the sensorless control mode, showing that it is more promising in diagnosing the stator faults under the sensorless control operation.

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Shaeboub A, Abusaad S, Hu N, Gu F, Ball A. Detection and diagnosis of motor stator faults using electric signals from variable speed drives. In Proceedings of the 21st International Conference on Automation & Computing. IEEE. 2015 https://doi.org/10.1109/IConAC.2015.7313938