Fault Pattern Recognition Based on Bispectrum Entropy Model

HUANG Jin-ying;PAN Hong-xia;BI Shi-hua;CUI Bao-zhen

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  • Sponsored by: China Association for Science and Technology (CAST)

    Editor-In-Chief: Xu Yida

    ISSN 1000-1093

    　

  • Hosted By: China Ordnance Society

    Published By: Acta Armamentarii

    CN 11-2176/TJ

Acta Armamentarii, a Chinese monthly journal, was first published in 1979. The journal is supervised by China Association for Science and Technology, sponsored by China Ordnance Society，and edited and published by Editorial Board of Acta Armamentarii. The Journal is included in all important domestic databases，and also collected by Engineering Index (EI, USA), Chemical Abstracts (CA, USA), Science Abstracts (SA, UK）, Abstract Journal (AJ, Russia), and Current Bibliography on Science and Technology(CBST).Acta Armamentarii has been selected into the journal Of Ordnance Science and Technology (Weapons Industry) Field Of High Quality Scientific and Technological Periodical Classification Catalogue (2022 edition), ranking T1, and the journal of Automotive Engineering Field of High Quality Scientific and technological Periodical classification Catalogue, ranking T2.
Acta Armamentarii ›› 2012, Vol. 33 ›› Issue (6) : 718-723. DOI: 10.3969/j.issn.1000-1093.2012.06.014
Paper

Fault Pattern Recognition Based on Bispectrum Entropy Model

  • HUANG Jin-ying1,2， PAN Hong-xia1， BI Shi-hua2， CUI Bao-zhen1
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Abstract

A fault pattern recognition method was developed on the basis of information entropy and bispectrum theory. The bispectrum features of vibration signal were analyzed. And a bispectrum entropy algorithm based on energy distribution was derived under the condition of subspace distribution probability. Then, the vibration signals of a gearbox under four conditions were extracted experimentally. And a BP neural network for the fault pattern recognition was established by using the bispectrum entropy feature as input. Finally, this method was verified by successfully recognizing four fault patterns of the gearbox.

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HUANG Jin-ying， PAN Hong-xia， BI Shi-hua， CUI Bao-zhen. Fault Pattern Recognition Based on Bispectrum Entropy Model. Acta Armamentarii. 2012, 33(6): 718-723 https://doi.org/10.3969/j.issn.1000-1093.2012.06.014

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