A new blind deconvolution method based on signal subspace

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Journal of Vibration and Shock ›› 2022, Vol. 41 ›› Issue (3) : 139-147.

ZHOU Tao1,2, ZHAO Ming1, GUO Dong2, OU Shudong1

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Abstract

The deconvolution methods have been widely applied to extract the fault impulse from the vibration signal. However, due to the complex and changeable operating conditions of the equipment, the difficulty in accurately predicting the fault feature period and the interference of random impulse, the current deconvolution method is difficult to meet the requirements of the enhanced fault impulse in the complex environment of the industrial site. To solve the above problem, a blind deconvolution method based on signal subspace was proposed. The method decomposed the test signal space and separated each subspace by singular value decomposition (SVD), restrained subspace noise by sparse code shrinkage. Then effective subspace was screened based on impulse sparse index. Finally fault impulse was extracted by iteration. The experimental results of bearing simulation signals in variable speed and train bearing show that proposed method can effectively eliminate the interference of random impulse and noise, avoid the influence of energy on subspace screening, and accurately extract fault impulse without the precise fault feature period.

Key words

Blind deconvolution / Singular value decomposition / Minimum entropy deconvolution / Variable speed

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ZHOU Tao1,2, ZHAO Ming1, GUO Dong2, OU Shudong1. A new blind deconvolution method based on signal subspace[J]. Journal of Vibration and Shock, 2022, 41(3): 139-147

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