断层(地质)
随机共振
信号(编程语言)
故障检测与隔离
噪音(视频)
控制理论(社会学)
计算机科学
拓扑(电路)
方位(导航)
算法
数学
人工智能
执行机构
地震学
程序设计语言
地质学
图像(数学)
控制(管理)
组合数学
作者
Jimeng Li,Junling Peng,Zhongke Shi,Jinfeng Zhang,Zong Meng
标识
DOI:10.1088/1361-6501/ad11ca
摘要
Abstract The accurate extraction of weak signal features under strong noise background plays a crucial role in the fault detection of rolling bearings. In order to promote the ability of stochastic resonance (SR) system to detect weak signals and improve the output performance of the system, a multi-system coupled cascaded SR (MCCSR) system is investigated and applied to the fault detection of rolling bearings. Firstly, a MCCSR system is constructed by exploiting the positive synergistic effect between multiple systems, which consists of a triangular-topology coupled system composed of three SR subsystems and a cascaded SR system with topology output as input. This system makes full use of the advantages of coupled system and cascaded system in weak signal detection. In terms of parameter optimization, a stepwise multi-parameter optimization strategy is proposed, which adopts different optimization methods for different parameters, and avoids the inconsistency between error and step factor by improving the least mean square algorithm. Finally, through the comparative analysis of numerical simulation and experimental signals, it is verified that the proposed method can effectively enhance the weak signal features and improve the system output signal-to-noise ratio, which can better serve for rolling bearing fault detection.
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