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Phase-compensation-based dynamic time warping for fault diagnosis using the motor current signal

Zhen, Dong, Zhao, H.L., Gu, Fengshou and Ball, Andrew (2012) Phase-compensation-based dynamic time warping for fault diagnosis using the motor current signal. Measurement Science and Technology, 23 (5). 055601. ISSN 0957-0233

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    Abstract

    Dynamic time warping (DTW) is a time-domain-based method and widely used in various similar recognition and data mining applications. This paper presents a phase-compensation-based DTW to process the motor current signals for detecting and quantifying various faults in a two-stage reciprocating compressor under different operating conditions. DTW is an effective method to align two signals for dissimilarity analysis. However, it has drawbacks such as singularities and high computational demands that limit its application in processing motor current signals for obtaining modulation characteristics accurately in diagnosing compressor faults. Therefore, a phase compensation approach is developed to reduce the singularity effect and a sliding window is designed to improve computing efficiency. Based on the proposed method, the motor current signals measured from the compressor induced with different common faults are analysed for fault diagnosis. Results show that residual signal analysis using the phase-compensation-based DTW allows the fault-related sideband features to be resolved more accurately for obtaining reliable fault detection and diagnosis. It provides an effective and easy approach to the analysis of motor current signals for better diagnosis in the time domain in comparison with conventional Fourier-transform-based methods

    Item Type: Article
    Subjects: Q Science > Q Science (General)
    Q Science > QC Physics
    Schools: School of Computing and Engineering
    School of Computing and Engineering > Automotive Engineering Research Group
    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
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    Depositing User: Sara Taylor
    Date Deposited: 24 Apr 2012 14:54
    Last Modified: 04 Jun 2013 01:38
    URI: http://eprints.hud.ac.uk/id/eprint/13349

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