Fault Diagnosis of Vacuum Circuit Breaker Based on Multi-sensor for Vibration Signals of Fusion

According to the characteristics of fault diagnosis for vacuum circuit breaker,a decision level information fusion diagnosis method is presented by using wavelet packet,RBF neural network and D-S evidence theory.Firstly,according to the method of wavelet packet-energy spectrum,vibration signals are decomposed and extracted feature vector as a basis for diagnosis;Then,neural network model is established,and the initial diagnosis results are obtained through the RBF neural network;Finally,the diagnosis results are used as the basic probability distribution value to each fault mode,and the D-S evidence theory is applied,and the final fusion diagnosis results are obtained.The experiment shows that the proposed method is effective to diagnose the faults of vacuum circuit breakers.