Extracting non-stationary signal under strong noise background: Time-varying system analysis

The extraction of non-stationary feature information under strong noise background is a difficult problem. In this paper, novel general time-varying scale transformation aperiodic stochastic resonance proposed to extract and enhance the weak signal background. theoretical framework parameters Duffing system built for resonance. By studying region migration when coefficient takes different values, an optimal achieved. Also, optimized with cross-correlation as index. Compared existing methods, method can be applied stronger has robustness. When same background, provide output higher signal-to-noise ratio coefficient. Finally, experimental analysis faulty bearing vibration verifies high accuracy, which indicates good enhancement ability method.