Fault feature extraction method of rolling bearings based on coupled resonance system with vibrational resonance-assisted enhanced stochastic resonance

Stochastic resonance (SR), as a signal processing method that is able to use noise to enhance weak periodic signals, provides effective technical support for the detection of weak signals. However, due to the constraints of potential functions or control means, the detection results of a single SR system on weak signals often fails to achieve the desired effect. Through the interaction between different subsystems, SR under the action of multiple systems can obtain rich dynamic response characteristics and improve the detection ability of weak signals. Therefore, this paper proposes a fault feature extraction method of rolling bearings based on a coupled resonance system with vibrational resonance (VR)-assisted enhanced SR. First, a SR system based on a matched steady-state potential model is constructed, which has the ability to alleviate the phenomenon of output saturation to some extent compared with the classical bistable SR. Second, inspired by the synergy of multiple systems, a coupled resonance system with VR-assisted enhanced SR is constructed by combining VR control and SR control, which has the dual advantages of VR and SR and performs well in weak signal detection. Finally, simulation experiment and fault data of rolling bearings are adopted to analyze the suggested method, and the comparison results with other SR methods verify its practicality and superiority.