Research Article
Weak Vibration Signal Extraction Method of Mechatronics Equipment Based on Stochastic Resonance
@INPROCEEDINGS{10.1007/978-3-030-94182-6_4, author={Dong-bao Ma and Xue-mei Li and Ming-fei Qu and Xiao-zheng Wan}, title={Weak Vibration Signal Extraction Method of Mechatronics Equipment Based on Stochastic Resonance}, proceedings={IoT and Big Data Technologies for Health Care. Second EAI International Conference, IoTCare 2021, Virtual Event, October 18-19, 2021, Proceedings, Part II}, proceedings_a={IOTCARE PART 2}, year={2022}, month={6}, keywords={Stochastic resonance Mechatronics Weak vibration signal Signal extraction}, doi={10.1007/978-3-030-94182-6_4} }- Dong-bao Ma
Xue-mei Li
Ming-fei Qu
Xiao-zheng Wan
Year: 2022
Weak Vibration Signal Extraction Method of Mechatronics Equipment Based on Stochastic Resonance
IOTCARE PART 2
Springer
DOI: 10.1007/978-3-030-94182-6_4
Abstract
Existing weak vibration signal extraction methods are limited by the small frequency parameters of the signal, and it is difficult to determine the critical amplitude of the signal, resulting in the delay of weak vibration signal extraction. Therefore, this paper designs a weak vibration signal extraction method for mechatronics equipment based on stochastic resonance. Based on the particle dynamics equation of Brownian motion, a bistable stochastic resonance model is constructed. By using the model, the parameters of potential well function are adjusted to achieve the optimal matching of signal, noise and nonlinear function to achieve stochastic resonance. According to the relationship between the output signal-to-noise ratio and the parameters of the potential well function, the output signal-to-noise ratio of the weak vibration is calculated, and the appropriate noise intensity is determined to enhance the weak periodic signal. The single oscillator is extended to an array equation group composed of four oscillators with different initial phase of driving signal, and the weak vibration signal with any initial phase is extracted. The experimental results show that: compared with the traditional method, the time of weak vibration signal extraction of this method is less, which shows that the weak vibration signal extraction of this method is more real-time.
