Abstract

To solve the problem that the weak fault signal is difficult to extract under strong background noise, an asymmetric second-order stochastic resonance method is proposed. By adjusting the damping factor and the asymmetry, weak signals, noise, and potential wells are matched to each other to achieve the best stochastic resonance state so that weak fault characteristics can be effectively extracted in strong background noise. Under adiabatic approximation, the effects of damping coefficient, noise intensity, and asymmetry on the output signal-to-noise ratio are discussed based on the two-state model theory. Under the same parameters, the output signal-to-noise ratio of the asymmetric second-order stochastic resonance system is better than that of the underdamped second-order stochastic resonance system. The bearing fault and field engineering experimental results are provided to justify the comparative advantage of the proposed method over the underdamped second-order stochastic resonance method.

Highlights

  • Rolling bearings are an important part of a mechanical system and the most prone to failure

  • We find that the underdamped second-order stochastic resonance (USSR) is superior to the first-order overdamped stochastic resonance (SR) in extracting weak fault features

  • Due to the shortcomings of the USSR method itself, it cannot have a rich form of potential function

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Summary

Original Paper

Asymmetric second-order stochastic resonance weak fault feature extraction method Measurement and Control 2020, Vol 53(5-6) 788–795 Ó The Author(s) 2020 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/0020294020914946 journals.sagepub.com/home/mac

Introduction
ASSR model
Gaussian noise of zero mean and satisfies
SNR analysis
ASSR method
Experiment verification
Engineering experiment
Tooth ratio
ORCID iD

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