The Application Of Insulator Fault Diagnosis Based On Fuzzy Neural Petri Netsdiagnosis

Insulator as transmission system important device, under normal working situation by the atmospheric pollution and so on factors, such as pollution flashover accident happened frequently, the direct impact on the security and stability of power supply system. The present study results show that lead to external insulator fault there are many factors and their relationship is very complicated, it is difficult to do effective, accurate monitoring and diagnosis, therefore insulator of degradation, filthy discharge and flashover problems such as diagnosis and forecast in the future will be in the field of power transmission hot research topic.This article through system researches the development process and mechanism of insulator filthy flash collaterals discharge, and makes full use of the evaluation technology and methods that the experts has summed up, describes the special relationship between each input characteristic quantities. Finally constructs the insulator fault diagnosis modle used on the power network to prevent pollution flashover which can accurately and efficiently and system diagnosis the insulator fault, the modle integrates fuzzy reasoning, Petri network and artificial neural network technology and so on. Through the further research this article validates that this design has efficient diagnosis and the ability to learn by itself, finally compiled a set of simulation program for the proposed theory which based on the object-oriented technology of VC++6.0, and the results show that the design of fault diagnosis system in this paper is very applicable and practical.