随机共振
断层(地质)
连贯性(哲学赌博策略)
自相关
方位(导航)
非线性系统
噪音(视频)
计算机科学
共振(粒子物理)
谐波
信号(编程语言)
控制理论(社会学)
算法
数学
物理
声学
统计
人工智能
地质学
控制(管理)
粒子物理学
量子力学
地震学
图像(数学)
程序设计语言
作者
Haitao Xu,Shengxi Zhou
标识
DOI:10.1016/j.ifacol.2022.10.546
摘要
For the sake of detecting the faults of bearing in the incipient stage, the efficient structure for fault diagnosis is necessary. However, the fault characteristics related to the fault diagnosis are extremely weak, and so they are difficult to be exacted. Stochastic resonance of the nonlinear system is a novel topic in the field of fault diagnosis, which can enhance the weak signal, and finally determine the fault types. Signal-to-noise ratio (SNR) is usually employed to induce the occurrence of stochastic resonance for fault diagnosis. While it may be also induce the coherence resonance, and the output can mistake the fault type. In this paper, a novel measuring index based on autocorrelation function is proposed to induce the stochastic resonance, and avoid the occurrence of coherence resonance. The measuring index is called as autocorrelation function harmonic to noise ratio index(AFHNR), and the structure for fault diagnosis based on AFHNR and stochastic resonance (Shorted as AFHNRSR) is successfully examined by the signals from numerical simulation and experimental rig.
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