Fault Diagnosis Of Hoist Electrical Control System Based On Fuzzy Expert System

Mine hoist, as one of the main equipments in the mine production, is a complex set ofmechanical and electrical units, as well as the main tool of mine production and transportation.The safety and reliability of the mine hoist operation not only directly affect the capacity ofthe entire mine and the economical efficiency, but also involve with the lives and the safety ofunderground miners. Because of the complex of the line structure, more control componentsand contacts with convoluted process are employed to find out the failure reasons, requiringrepairers equipped with extensive experience and knowledge. To meet the requirements of theactual demand of mine hoist monitoring and fault diagnosis, this paper presents a method offuzzy expert system used in mine hoist monitoring and fault diagnosis.Firstly, the configuration and working characteristic of the mine hoist and control systemare introduced. Secondly, the concept, the method and the species of the fault diagnosis arediscussed. And this paper presents the main content and the total frame of the expert systemof condition monitoring and fault diagnosis for the mine hoist. After that, the fault diagnosisof the mine hoist research is conducted by applying the theory of artificial intelligent,database and fuzzy theory. The constructing method of the knowledge base, knowledge basemanagement system and reasoning machine of fault diagnosis are especially researched,which is based on the fuzzy expert system for fault diagnosis; During the realization of thesystem, the membership function that reflects the fault fuzzy，fuzzy connection and fuzzydescription of knowledge based on relational database, are employed in this paper, with fuzzyreasoning based on the rule realized. Then by adopting the theory of software engineering,this paper develops the Knowledge Base, Knowledge Base Management System andReasoning Machine of Fault Diagnosis using VC++6.0program environment, and thesoftware is the core of the whole system. At last, this paper demonstrates application examples to testify the Knowledge Base Management System and Diagnosis ReasoningModule.