Information-fusion method for fault diagnosis based on reliability evaluation of evidence
评估诊断证据可靠性的信息融合故障诊断方法

In fault diagnosis methods based on evidence theory with information fusion, the reliabilities of evidences will affect the accuracy of diagnosis results. However, most existing fusion diagnosis methods do not take the reliabilities of the evidences into account comprehensively. The main factors which determine the reliability of evidence are the precision of individual sensor and the performance of the method in obtaining the evidence, as well as the uncertainties in the observation environment. They are considered static factors and dynamic factors. The original evidence is rst modi ed by a static discount-factor obtained by optimizing the indication function of Pignistic probability measure. This result is further modi ed by a dynamic discount-factor which is obtained by applying the measurement method to evidence similarity in Pignistic vectors. Double-modi ed evidences are combined by Dempster combination rule to obtain the nal diagnosis results. Experiments on the multi-functional exible rotor-testing validate the effectiveness of the proposed method.