mechanical fault diagnosis based on cascaded bistable stochastic resonance and multi-fractal
Hao Yan1, Wang Tai-yong1,2, Wan Jian2, Zhang Pan2
1. College of Precision Instrument and Opto-electronics Engineering, Tianjin University, Tianjin, 300072;2. College of mechanical engineering, Tianjin University, Tianjin, 300072
The filtering performance of cascaded bistable stochastic resonance (CBSR) was analyzed. Depending on the filtering feature of CBSR and the measurement capability of general dimension for non-linear characteristics of signals, a method of mechanical fault diagnosis based on cascaded bistable stochastic resonance and multi-fractal was presented. The experiment results showed that this method, not only removing high frequency noise efficiently but also enhancing low frequency signals, obtained precise fractal dimension. The fractal dimension measured the non-linear characteristics of mechanical vibration signals accurately in order to implement mechanical fault diagnosis.