The Recovery of Weak Impulsive Signals Based on Stochastic Resonance and Moving Least Squares Fitting

Kuosheng Jiang, Guanghua Xu, Lin Liang, Tangfei Tao, Fengshou Gu

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

In this paper a stochastic resonance (SR)-based method for recovering weak impulsive signals is developed for quantitative diagnosis of faults in rotating machinery. It was shown in theory that weak impulsive signals follow the mechanism of SR, but the SR produces a nonlinear distortion of the shape of the impulsive signal. To eliminate the distortion a moving least squares fitting method is introduced to reconstruct the signal from the output of the SR process. This proposed method is verified by comparing its detection results with that of a morphological filter based on both simulated and experimental signals. The experimental results show that the background noise is suppressed effectively and the key features of impulsive signals are reconstructed with a good degree of accuracy, which leads to an accurate diagnosis of faults in roller bearings in a run-to failure test.
Original languageEnglish
Pages (from-to)13692-13707
Number of pages16
JournalSensors
Volume14
Issue number8
DOIs
Publication statusPublished - 29 Jul 2014

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