Full Information Fault Diagnosis Based on Improved Evidence Theory

Abstract

Aiming at the problem that a single sensor is difficult to describe the rotor vibration accurately,a full information fault diagnosis method of rotor based on improved D-S evidence fusion theory is proposed.Wavelet analysis and information entropy are combined to extract vibration signal full information fault feature vectors of each measuring point.And these feature vectors are made to be the input of the corresponding BP neural networks to get the original evidences of each measuring point.These original evidences are preprocessed by the conflict degree,and the new evidences are weighted average fused according to the credibility.Experimental results show that this method can obtain original evidences effectively and reduce the influence that comes from the evidence conflict,the accuracy rate of this method can reach 93%,and it is higher than that of the conventional BP method and BP-D-S fusion method.