A novel mechanical fault signal feature extraction method based on unsaturated piecewise tri-stable stochastic resonance

Abstract Stochastic resonance (SR) is widely studied in signal feature extraction. The standard tri-stable SR (STSR) method possesses superior performance than the classical bistable SR (CBSR) method in signal feature extraction, but it still has output saturation phenomenon, which will reduce the signal-to-noise ratio (SNR) of the output signal and the signal amplitude of the characteristic frequency as the CBSR method. For the purpose of avoiding the influence of output saturation on the STSR method, a piecewise tri-stable stochastic resonance (PTSR) method is proposed and applied in fault feature signal extraction. Firstly, the simulation signals are processed using the PTSR method and the STSR method separately, then the comparison shows that the output signal has larger signal amplitude and a higher SNR. Ultimately, the devised PTSR method is utilized for extracting fault characteristics of two groups of actual signals, which also has better output characteristics compared with the STSR method.

• Publication year

  2021

• Venue

  Measurement

• Publication date

  2021-01-15

• Fields of study

  Physics, Engineering

• Identifiers
  DOI 10.1016/j.measurement.2020.108374
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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