Conflict evidence management in fault diagnosis

Abstract

Dempster–Shafer (D–S) theory of evidence is widely used in many real application systems. It can not only deal with imprecise and uncertain information but also combine evidences of different sensors. Therefore it plays an important role in multi-sensor reports’ combination in fault diagnosis. However, when the evidences highly conflict with others, Dempster’s combination rule may lead to a counter-intuitive result and come to a wrong conclusion. It is inevitable to handle conflict in fault diagnosis. This paper proposes a new method to address the issue. Deng entropy function is adopted to measure the information volume of evidences. Evidence distance is introduced to represent the compatibility of evidences. An improved combination method considering both the uncertainty of evidences and the conflict degree of the system is proposed. The proposed method can deal with conflicting evidences efficiently. An application in fault diagnosis is illustrated to show the efficiency of the new method and the result is compared with that of other methods. Besides, and example in IRIS based on information fusion is given to validate the accuracy of the proposed method.