随机共振
白噪声
断层(地质)
布朗运动
高斯噪声
随机过程
非线性系统
共振(粒子物理)
强度(物理)
统计物理学
控制理论(社会学)
计算机科学
数学
地质学
算法
人工智能
物理
量子力学
统计
噪音(视频)
地震学
图像(数学)
控制(管理)
作者
Yanfei Jin,Haotian Wang,Pengfei Xu,Wenxian Xie
标识
DOI:10.1016/j.probengmech.2023.103418
摘要
This paper investigates the stochastic resonance and mean-first passage time of a quad-stable potential in the presence of Gaussian white noise and periodic forcing. The analytical expressions of mean-first passage time and spectral amplification are obtained, respectively. It is found that even small noise intensity can lead to noise-assisted hopping between two adjacent potential wells for the case of small damping coefficient. For large noise intensity, the escape process of Brownian particles is accelerated in an underdamped nonlinear system. Moreover, the curve of spectral amplification displays a typical resonant peak at an optimal noise intensity, suggesting the onset of stochastic resonance. Meanwhile, with the decrease of periodic signal frequency, the peak value of spectral amplification is enhanced. Especially, an optimal quad-stable potential structure exists to maximize the stochastic resonance effect. The proposed multi-stable stochastic resonance method is applied to the fault diagnosis of inner and outer race bearing, and the quantum particle swarm optimization algorithm is used to optimize the system parameters and damping coefficient. The good agreement between fault frequency and theoretical value validates efficiency of the proposed method. Compared with the overdamped tri-stable stochastic resonance method, the performance of fault diagnosis is enhanced substantially by the proposed method.
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