Stochastic resonance in overdamped systems with fractional power nonlinearity

Yang, Jianhua; Sanjuán, Miguel A. F.; Chen, Pengpeng; Liu, Houguang

doi:10.1140/epjp/i2017-11701-8

Cited by 10 publications

(2 citation statements)

References 34 publications

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“…is interesting nonlinear phenomenon makes it possible for the weak signals to strengthen their intensities by absorbing a certain fraction of the noise energy, thus highlighting the weak signals [8,9]. SR has attracted much attention from the physics and engineering community in the research areas such as dynamical nonlinearity [10][11][12], structure monitoring [13], and energy harvesting [14][15][16]. Moreover, in view of the good performance of SR using noise to enhance periodic signal features, SR-based weaksignal detection and fault diagnosis methods have been investigated and successfully applied in rolling bearing fault diagnosis [17,18].…”

Section: Introductionmentioning

confidence: 99%

Rolling Bearing Fault Diagnosis Based on Adaptive Multiparameter-Adjusting Bistable Stochastic Resonance

Lai

Wang

Zhang

et al. 2020

Shock and Vibration

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The weak-signal detection technologies based on stochastic resonance (SR) play important roles in the vibration-based health monitoring and fault diagnosis of rolling bearings, especially at their early-fault stage. Aiming at the parameter-fixed vibration signals in practical engineering, it is feasible to diagnose the potential rolling bearing faults through adaptively adjusting the SR system parameters, as well as other generalized parameters such as the amplitude-transformation coefficient and scale-transformation coefficient. However, extant adaptive adjustment methods focus on the system parameters, while the adjustments of other adjustable parameters have not been fully studied, thus limiting the detection performance of the adaptive SR method. In order to further enhance the detection performance of adaptive SR methods and extend their application in rolling bearing fault diagnosis, an adaptive multiparameter-adjusting SR (AMPASR) method for bistable systems based on particle swarm optimization (PSO) algorithm is proposed in this paper. This method can produce optimal SR output through adaptively adjusting multiparameters, thus realizing fault feature extraction and further fault diagnosis. Furthermore, the influence of algorithm parameters on the optimization results is discussed, and the optimization results of the Langevin system and the Duffing system are compared. Finally, we propose a weak-signal detection method based on the AMPASR of the Duffing system and employ three diagnosis examples involving inner ring fault, outer ring fault, and rolling element fault diagnoses to demonstrate its feasibility in rolling bearing fault diagnosis.

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Section: Introductionmentioning

confidence: 99%

Rolling Bearing Fault Diagnosis Based on Adaptive Multiparameter-Adjusting Bistable Stochastic Resonance

Lai

Wang

Zhang

et al. 2020

Shock and Vibration

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“…Among them, the composite cell coordinate system (CCCS) method [13,14] is usually used to obtain the global properties in the deterministic system, containing attractor, basin of attraction, boundary, and so on. e stochastic generalized cell mapping (SGCM) method [15,16] is used to obtain the stochastic response [17][18][19] in the stochastic system. e rest of this paper is as follows.…”

Section: Introductionmentioning

confidence: 99%

Statistical Characteristics of the First Passage Time Analysis for the Gene Regulatory Circuit in Bacillus subtilis by Cell Mapping Method

Wang

Yuan

et al. 2020

Complexity

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In this paper, we will explore the stochastic exit problem for the gene regulatory circuit in B. subtilis affected by colored noise. The stochastic exit problem studies the state transition in B. subtilis (from competent state to vegetative state in this case) through three different quantities: the probability density function of the first passage time, the mean of first passage time, and the reliability function. To satisfy the Markov nature, we convert the colored noise system into the equivalent white noise system. Then, the stochastic generalized cell mapping method can be used to explore the stochastic exit problem. The results indicate that the intensity of noise and system parameters have the effect on the transition from competent to vegetative state in B. subtilis. In addition, the effectiveness of the stochastic generalized cell mapping method is verified by Monte Carlo simulation.

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Recovery and enhancement of unknown aperiodic binary signal by adaptive aperiodic stochastic resonance

2021

Pramana - J Phys

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Stochastic resonance in overdamped systems with fractional power nonlinearity

Cited by 10 publications

References 34 publications

Rolling Bearing Fault Diagnosis Based on Adaptive Multiparameter-Adjusting Bistable Stochastic Resonance

Rolling Bearing Fault Diagnosis Based on Adaptive Multiparameter-Adjusting Bistable Stochastic Resonance

Statistical Characteristics of the First Passage Time Analysis for the Gene Regulatory Circuit in Bacillus subtilis by Cell Mapping Method

Recovery and enhancement of unknown aperiodic binary signal by adaptive aperiodic stochastic resonance

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