Research And Implementation On Diagnosis Of Power Network Expert System Based On Fuzzy Identification

With the development of technology,neural networks, fuzzy systems, evolutionary computation, and some new areas of research have gradually developed, The main research field is the simulation of human intelligent behavior or evolutionary processes, they are not only intelligent, but also a high degree of parallelism, Therefore, people have great interest in these research areas, their application has covered agriculture, chemistry, commerce, communications and other fields.This paper appeared in the current network fault diagnosis problem. With the increasing modernization of power systems, the traditional fault diagnosis methods have not power efficient and accurate for a full diagnosis. So how can we improve equipment become very concerned about security issues, Design a fault diagnosis system can solve the disadvantages of traditional, reliable power supply is necessary, This article is use of expert systems to solve these problems and diagnose fault.First, in this paper, the basic theory of fault diagnosis method as the basis and analysis method of fault diagnosis ,understand the main structure of expert system, then comprehensive application of database theory and fuzzy theory, research full of fault diagnosis ,combined the fuzzy recognition technology and fault diagnosis expert system, and fuzzy algorithm is applied to the fuzzy rule base, inference engine and other modules to optimize the electrical network fault diagnosis, make the reason of fault more accurate and improve system reliability and security. Finally, design and implementation of Diagnosis Expert SystemMain content of this thesis is as follows:(1) Firstly, briefly introduces the background and significance of this diagnosis of power network fuzzy expert system, I am have a initial understanding of this system, analysis of several methods of fault diagnosis.(2) Secondly, studied the fault diagnosis expert system principles and basic structure, then discusses the fuzzy expert system has the advantages of traditional expert systems, and introduced the reason of selecting fuzzy expert system. (3) Thirdly, completed analysis and design of fault diagnosis expert system, This system is fully considered efficiency and the need to consider friendly interface, and decided to choose the VC++ as a development platform combined with a database platform SQLServer2005 to develop diagnosis expert system, ultimately realization of designing the knowledge base, rule base and inference engine.(4) In order to optimize the efficiency of power network diagnosis expert system learn the knowledge, decided to use the mechanism of combining self-learning knowledge base approach and manual input, improve the comprehensiveness and accuracy of learning knowledge, and application of fuzzy matching algorithm in the rule base and inference engine module, ultimately realize the main function of initialing setup, inputting fault information, and outputting the diagnosis result and so on.