Structural damage detection of adaptive tangent-based unsaturated bistable stochastic resonance

Abstract

The output saturation of classical bistable stochastic resonance (CBSR) limits its ability to enhance weak signal characteristics. To solve this problem, an adaptive tangent-based unsaturated bistable stochastic resonance (TUBSR) method is proposed. We construct a tangent-based piecewise unsaturated bistable potential model, and select the optimal system parameters with genetic algorithm (GA) to adaptively adjust the structure of potential model, so as to improve the output saturation and obtain a larger output signal-to-noise ratio (SNR). The simulated signals are used to verify that the TUBSR method can effectively improve the detection ability of weak signals. Finally, the method is applied to the damage detection of bearing inner race and the crack detection of curved plate. The results demonstrate that compared with CBSR and other improved bistable SR method, the TUBSR method has better detection ability for weak signals.