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Detection and Diagnosis of Motor Stator Faults using Electric Signals from Variable Speed Drives

Shaeboub, Abdulkarim, Abusaad, Samieh, Hu, Niaoqing, Gu, Fengshou and Ball, Andrew (2015) Detection and Diagnosis of Motor Stator Faults using Electric Signals from Variable Speed Drives. In: Proceedings of the 21st International Conference on Automation and Computing (ICAC). IEEE. ISBN 978-0-9926801-0-7

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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 in sidebands 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.

Item Type: Book Chapter
Additional Information: ‘Best Student Paper Awarded’
Subjects: T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering
School of Computing and Engineering > Automotive Engineering Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering > Diagnostic Engineering Research Centre > Energy, Emissions and the Environment Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Machinery Condition and Performance Monitoring Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
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Depositing User: Cherry Edmunds
Date Deposited: 05 Oct 2015 13:24
Last Modified: 02 Dec 2016 03:35
URI: http://eprints.hud.ac.uk/id/eprint/26002

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