Partly Duffing Oscillator Stochastic Resonance Method and Its Application on Mechanical Fault Diagnosis

Due to the fact that the slight fault signals in early failure of mechanical system are usually submerged in heavy background noise, it is unfeasible to extract the weak fault feature via the traditional vibration analysis. Stochastic resonance (SR), as a method of utilizing noise to amplify weak si...

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Bibliographic Details
Published in:Shock and vibration 2016-01, Vol.2016 (2016), p.1-14
Main Authors: Wu, Hua, Luo, Xingqi, Jia, Rong, Dang, Jian, Chen, Di-Yi
Format: Article
Language:English
Subjects:
Duffing oscillators
Entropy
Fault diagnosis
Faults
Feature extraction
Machinery
Mechanical systems
Methods
Noise
Noise control
Noise intensity
Science
Signal processing
Stochastic resonance
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Summary:Due to the fact that the slight fault signals in early failure of mechanical system are usually submerged in heavy background noise, it is unfeasible to extract the weak fault feature via the traditional vibration analysis. Stochastic resonance (SR), as a method of utilizing noise to amplify weak signals in nonlinear dynamical systems, can detect weak signals overwhelmed in the noise. However, based on the analysis of the impact of noise intensity on SR effect, it is concluded that the detection results are dramatically limited by the noise intensity of measured signals, especially for incipient fault feature of mechanical system with poor working environment. Therefore, this paper proposes a partly Duffing oscillator SR method to extract the fault feature of mechanical system. In this method, to locate the appearance of weak fault feature and decrease noise intensity, the permutation entropy index is constructed to select the measured signals for the input of Duffing oscillator system. Then, according to the regulation of system parameters, a reasonable match between the selected signals and Duffing oscillator model is achieved to produce a SR phenomenon and realize the fault diagnosis of mechanical system. Experiment results demonstrate that the proposed method achieves a better effect on the fault diagnosis of mechanical system.
ISSN:1070-9622
1875-9203
DOI:10.1155/2016/3109385