随机共振
方位(导航)
计算机科学
信号(编程语言)
探测理论
故障检测与隔离
声学
模式识别(心理学)
物理
人工智能
探测器
电信
噪音(视频)
执行机构
图像(数学)
程序设计语言
作者
Lifang He,Zhiyuan Jiang,Yanxin Gao
标识
DOI:10.1088/1402-4896/ad6249
摘要
Abstract In order to solve the common output saturation of stochastic resonance systems and the limitation of classical index SNR for blind detection, a novel adaptive quasi-periodic potential stochastic resonance blind detection method is proposed. First, a model of quasi-periodic potential stochastic resonance (QPPSR) possessing infinite steady state is constructed and analyzed for its structure change pattern. The superior performance of the model is verified by using the fourth-order Runge-Kutta algorithm. Secondly, the mechanism of QPPSR is analyzed using the probability flow method, which reveals the relationship between system parameters and performance. Again, a novel comprehensive blind detection index (CBDI) is exquisitely constructed to make up for the shortcomings of each indicator. Finally, CBDI and QPPSR are constructed into an adaptive blind detection system and applied to bearing fault detection. The results analyzed by experiments verify the good engineering application prospect of CBDI-QPPSR.
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