Research on the weak signal detection method based on adaptive vibrational resonance

In this paper, the weak signal detection under α stable noise is investigated based on bistable vibrational resonance (VR) which is driven by a high frequency signal. On the one hand, the energy of the high frequency drive signal is transferred to the low frequency weak signal when VR occurs; on the other hand, the control of stochastic resonance (SR) is achieved based on VR, which transfers more noise energy into useful signal energy. In addition, considering the requirements of real-time detection, the amplitude and frequency of the high frequency drive signal are optimized by the knowledge-based particle swarm optimization (KPSO), which takes the mean signal-noise-ratio (MSNR) of output as the fitness function, and the property that VR system produces the best resonance effect just when the valid system parameter â(B,Ω) is greater than zero as knowledge. Finally, the parameter compensation is combined to achieve multi-high frequency weak signals detection with a stable noise. Furthermore, the method is applied to the vibration fault diagnosis of a mono-crystalline silicon furnace, and the experiment results show the effectiveness and practicability of the method.