The Study Based On A Time Bayes Petri Net Method Orienting Fault Diagnosis

The fault diagnosis is a technology about logical relationship between the fault information and analysis of failure mechanism. Establishing the reasonable diagnosis model and eliminate the uncertainty problem in the process of diagnosis of fault disturbance are need to solve the key problems in the diagnostic techniques. Among them, the study is a difficulty for the uncertainty. Different scholars both at home and abroad from different perspectives put forward a lot of analysis and processing method.In view of the many uncertainties existing in the fault diagnosis problem,this paper consider the time uncertainty impact of the distribution and reasoning of the temporal information, Based on the fuzzy theory, bayes probability reasoning and Petri net theory, the paper put forward a kind of time bayes Petri net model (TBPN). About the model originally time uncertainty problem, the model can be transformed to quantitative description of fault information, and concluded the probability of failure. TBPN model is divided into the classified information processing stages and information inference phase two parts on the network struct:The information belonging to stage the belonging of the fault information is used to put forward a kind of ownership strategy, and gives the fault information and the corresponding matching rules; According to have good information, the information processing stage calculates failure probability, and finds the failure probability of the failure source. The paper proposes token’s formal representation, the corresponding time ownership strategy, information support function and information, support function.The result of the fault diagnosis example of substation indicates that this model and method can construct the reasonable model and solve the problem. Espically, when the informations are incomplete, the method can complete the fuzzy reasoning smoothly. It can be used in more complicate fault diagnosis process.