Xiaoping Zhao1, 4, Yifei Wang2, *, Yonghong Zhang2, Jiaxin Wu1, Yunqing Shi3
CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 571-587, 2020, DOI:10.32604/cmc.2020.06363
- 08 April 2019
Abstract Stochastic resonance can use noise to enhance weak signals, effectively
reducing the effect of noise signals on feature extraction. In order to improve the early fault
recognition rate of rolling bearings, and to overcome the shortcomings of lack of
interaction in the selection of SR (Stochastic Resonance) method parameters and the lack
of validation of the extracted features, an adaptive genetic random resonance early fault
diagnosis method for rolling bearings was proposed. compared with the existing methods,
the AGSR (Adaptive Genetic Stochastic Resonance) method uses genetic algorithms to
optimize the system parameters, and further optimizes More >
Login
Register
