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A Novel Transform Demodulation Algorithm for Motor Incipient Fault Detection

Hu, Niaoqing, Xia, Lurui, Gu, Fengshou and Qin, Guojun (2011) A Novel Transform Demodulation Algorithm for Motor Incipient Fault Detection. IEEE Transactions on Instrumentation and Measurement, 60 (2). pp. 480-487. ISSN 0018-9456

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Abstract

Faults, such as broken rotor bars, in induction motors may be detected by estimating the spectral signature of the stator currents, particularly the sidebands around the supply line frequency. However, the amplitude of the fundamental frequency (50 Hz) is considerably greater than the sideband amplitude. How to demodulate the signature frequency components under the heavy background of fundamental frequency, or how to remove the fundamental frequency, is becoming a key problem in motor current signature analysis. This paper puts forward a novel transform demodulation algorithm to solve the problem. The three-phase currents are transformed to a magnetic-torque (M-T) coordinate using this algorithm. It is found that the signature frequency components are demodulated in the magnetizing and torque-producing currents obtained by the transformation. Thus, the two demodulated M-T currents can be used to extract the enhanced signature frequency components of faults, and the incipient fault detection of induction motors is easy to realize. With both simulated and experimental data of broken rotor bars, it shows that the proposed algorithm can extract more detailed fault signature frequency components and realize the incipient fault detection of induction motors.

Item Type: Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TA Engineering (General). Civil engineering (General)
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
School of Computing and Engineering > Informatics Research Group
School of Computing and Engineering > Informatics Research Group > XML, Database and Information Retrieval Research Group
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Depositing User: Cherry Edmunds
Date Deposited: 27 Jul 2010 09:26
Last Modified: 18 Jul 2012 13:13
URI: http://eprints.hud.ac.uk/id/eprint/8202

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