Information Fusion Technology Applied Research In Fault Diagnosis

Fault diagnosis is a new multi-subject-crossed technique, It has been developed rapidly in last twenty years, and it has brought huge benefit. Information fusion is a subject formed recently, it has been researched and applied in many fields. But, it is in starting stage in fault diagnosis. There are much available information in fault diagnosis. Only when the available information is used, can the precision and credibility be improved. So fault diagnosis is a process of information. The fault diagnosis model is put forward in this paper. Based on the analysis of single neural network characteristic, the model of integrated neural network is put forward. At the same time , the way to establish model, the principle to compose and the strategy to realize are given in this paper. The result based on the simulation of the example show it is a effective way by using network to deal with the characteristic information. To the incertitude of fault diagnosis, the decision-making fusion based on evidence theory is put forward. The basic conception of evidence theory is introduced. With the simulation based on the example, we can know evidence theory fusion improved the fault diagnosis precision. It is hard to give the basic probability function in the process of using the evidence theory, So the model based on network and D-S evidence is put forward. The simulation of the example show it is feasible and effective.