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A new method of accurate broken rotor bar diagnosis based on modulation signal bispectrum analysis of motor current signals

Gu, Fengshou, Wang, T., Alwodai, Ahmed, Tian, Xiange, Shao, Yimin and Ball, Andrew (2014) A new method of accurate broken rotor bar diagnosis based on modulation signal bispectrum analysis of motor current signals. Mechanical Systems and Signal Processing. ISSN 0888-3270

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Abstract

Motor current signature analysis (MCSA) has been an effective way of monitoring electrical machines for many years. However, inadequate accuracy in diagnosing incipient broken rotor bars (BRB) has motivated many studies into improving this method. In this paper a modulation signal bispectrum (MSB) analysis is applied to motor currents from different broken bar cases and a new MSB based sideband estimator (MSB-SE) and sideband amplitude estimator are introduced for obtaining the amplitude at (1±2s)fs(1±2s)fs (s is the rotor slip and fsfs is the fundamental supply frequency) with high accuracy. As the MSB-SE has a good performance of noise suppression, the new estimator produces more accurate results in predicting the number of BRB, compared with conventional power spectrum analysis. Moreover, the paper has also developed an improved model for motor current signals under rotor fault conditions and an effective method to decouple the BRB current which interferes with that of speed oscillations associated with BRB. These provide theoretical supports for the new estimators and clarify the issues in using conventional bispectrum analysis.

Item Type: Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
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 > High-Performance Intelligent Computing
School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
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Depositing User: Cherry Edmunds
Date Deposited: 09 Jun 2014 11:02
Last Modified: 01 Dec 2016 15:49
URI: http://eprints.hud.ac.uk/id/eprint/20882

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