Rsearch On Diagnosis Of Insulator Malfuntion Based On Fuzzy Neual Petri Net

With the development of industry,energy equipment demand also rose sharply,in the electric energy in the process of using,the quality of electric energy most valued.Insulator is one of the most important equipment in the power system transmission,its use due to the influence of natural environment and industrial environment,the insulation of appearance of flashover and other kinds of accidents,seriously affected the transport of stability and system security.To do the timely and effective monitoring is very difficult,so as to solve this kind of problem diagnosis and research is the important research direction of transmission field.Studying on the insulator contamination discharge and pollution flashover,combined with the existing technical expert intelligent judgment and solving method,to establish the accuracy of insulator fault diagnosis system and efficiency,we should first establish the diagnosis reasoning model of insulator,the model can clearly describe the flashover stage,and the complex relationships between characteristics of each input and because these input will cause the characteristic quantity of fault insulators in the design.In the model of fuzzy production rules,Petri network,the integration of artificial neural network theory,which makes the change of diagnosis system is not only efficient inference ability and self-learning ability,and further reasoning and Research on the system,through the preparation of a final text system simulation program to verify the practicability of the system.This article has made three attempts: selected features of fault diagnosis of insulators,detailed analysis of the complex relationship between the insulator fault and the causes of formation,and the insulator contamination degree and the degree of deterioration and flashover probability.Better diagnosis using fuzzy Petri neural network fault diagnosis system.The system is constituted by fuzzy structure moreover,the output value of the corresponding fuzzy reasoning,this is better for the system,in the use of continuous function of adaptive fuzzy neural network,and then through the study of error feedback algorithms,and make simulation,the theoretical value and the actual comparison,so as to make the system more persuasive and accuracy.Finally the use of surface object technology platform,will design better diagnostic systems into the corresponding simulation system,which proves the feasibility of this system.Then the results were compared,summed perfect This can make self direction of future work.