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    Empirical Wavelet Transform and Power Spectral Entropy for Rotating Machinery Fault Diagnosis

    Empirical Wavelet Transform and Power Spectral Entropy for Rotating Machinery Fault Diagnosis


    In order to extract the fault feature of rotating machines, a new method based on the empirical wavelet transform (EWT) and power spectral entropy (PSE) is proposed. EWT is introduced to first decompose the raw signal into several intrinsic mode function (IMF) signals. The power spectral entropy is used to quantify the complexity and uncertainty of each constructed component’s spectra; the difference value (D-value) between the neighboring entropies is, therefore, calculated to indicate the most information of reconstructed signals. Finally, the real signal is tested by the proposed method, whose results show that it can effectively extract the most abundant fault characteristic information in machinery fault signals.

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    Titel :

    Empirical Wavelet Transform and Power Spectral Entropy for Rotating Machinery Fault Diagnosis

    Weitere Titelangaben:

    Lect. Notes Electrical Eng.

    Beteiligte:
    Qin, Yong (Herausgeber:in) / Jia, Limin (Herausgeber:in) / Liu, Baoming (Herausgeber:in) / Liu, Zhigang (Herausgeber:in) / Diao, Lijun (Herausgeber:in) / An, Min (Herausgeber:in) / Zhang, Shunjie (Autor:in) / Qin, Yong (Autor:in) / Xin, Ge (Autor:in) / Wang, Yuze (Autor:in)
    Kongress:

    International Conference on Electrical and Information Technologies for Rail Transportation ; 2019 ; Qingdao, China October 25, 2019 - October 27, 2019

    Erschienen in:

    Proceedings of the 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019 ; Kapitel : 68 ; 717-726

    Lecture Notes in Electrical Engineering ; 639

    Erscheinungsdatum :

    2020-04-04

    Format / Umfang :

    10 pages

    ISBN :

    978-981-15-2866-8 , 978-981-15-2865-1

    ISSN :

    1876-1119 , 1876-1100

    DOI :

    https://doi.org/10.1007/978-981-15-2866-8_68

    Medientyp :

    Aufsatz/Kapitel (Buch)

    Format :

    Elektronische Ressource

    Sprache :

    Englisch

    Schlagwörter :

    Rotating machines , Fault diagnosis , Empirical wavelet transform , Power spectral entropy Engineering , Transportation Technology and Traffic Engineering , Computational Intelligence , Control and Systems Theory , Information Systems Applications (incl. Internet)

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