Harmonic-Gaussian double-well potential stochastic resonance with its application to enhance weak fault characteristics of machinery
Zijian Qiao, Shuai Chen, Zhihui Lai, Shengtong Zhou, Miguel A. F., Sanjuan

TL;DR
This paper investigates stochastic resonance in harmonic-Gaussian double-well potentials, deriving analytical expressions and demonstrating how damping influences antiresonance, with applications in enhancing weak fault signals in machinery diagnostics.
Contribution
It introduces a detailed analysis of SR in harmonic-Gaussian double-well potentials, including analytical SNR expressions and the impact of damping on antiresonance phenomena, applied to machinery fault detection.
Findings
Antiresonance occurs when the potential loses stability.
Adding damping removes the antiresonance behavior.
Enhanced weak fault signals in machinery diagnostics.
Abstract
Noise is ubiquitous and unwanted in detecting weak signals, which would give rise to incorrect filtering frequency-band selection in signal filtering-based methods including fast kurtogram, teager energy operators and wavelet packet transform filters and meanwhile would result in incorrect selection of useful components and even mode mixing, end effects and etc. in signal decomposition-based methods including empirical mode decomposition, singular value decomposition and local mean decomposition. On the contrary, noise in stochastic resonance (SR) is beneficial to enhance weak signals of interest embedded in signals with strong background noise. Taking into account that nonlinear systems are crucial ingredients to activate the SR, here we investigate the SR in the cases of overdamped and underdamped harmonic-Gaussian double-well potential systems subjected to noise and a periodic…
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Taxonomy
Topicsstochastic dynamics and bifurcation · Probabilistic and Robust Engineering Design · Statistical Distribution Estimation and Applications
