Mechanical Equipment Condition Monitoring and Fault Diagnosis based on Frequency-Domain Blind Deconvolution

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Journal of Vibration and Shock ›› 2012, Vol. 31 ›› Issue (12) : 34-41.

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Mechanical Equipment Condition Monitoring and Fault Diagnosis based on Frequency-Domain Blind Deconvolution

PAN Nan, WU Xing, CHI Yi-lin, LIU Xiao-qin, LIU Chang

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Abstract

basis of introducing the model of Frequency-Domain Blind Deconvolution (FDBD), key techniques in engineering signal feature extraction were comprehensively related and analyzed in this paper, which include the methods of suppressing difference between circular and partial convolution, the methods of removing permutation indeterminacy, the applications of Complex-Domain Blind Separation Algorithms. Aimed at vibration and acoustic signal feature extraction in complex environment and equipment with complex mechanical structures, and the application values of FDBD and its research status in machinery condition monitoring and fault diagnosis were reviewed and summarized, the practical application value was verified by acoustics experiment. Finally, the main problems which need to be studied further in this area were pointed out.

Key words

Frequency-domain blind deconvolution / Mechanical fault diagnosis / Difference between circular and partial convolution / Complex-domain blind separation algorithm / Permutation indeterminacy

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PAN Nan;WU Xing;CHI Yi-lin;LIU Xiao-qin;LIU Chang. Mechanical Equipment Condition Monitoring and Fault Diagnosis based on Frequency-Domain Blind Deconvolution [J]. Journal of Vibration and Shock, 2012, 31(12): 34-41