Research On Auxiliary Machine Intelligence Maintenance Decsion System In Thermal Power Plant

For mang years, the maintenance management mode of the thermal power plant of our country is schedule maintenance based on the operating time. It is with high costs to maintain and the fault rate of the equipment remains high. It can't meet the electric industrial development and need of the reform at present, so we must study the new maintenance tactics by RCM. This text in current to analyse thermal power plant and three equipment of the pilot project maintain at the foundation of the way. In order to ensure the lowest cost, using the methods of the plant management realize the maintenance according to the classification of the plant. Because of the data which associated with the classification, optimized maintenance cycle, maintenance decision is very much, we must setup the plant maintenance decision support system, which includes knowledge base ,database ,mode database ,and reasoning mechanism based on the using of the modern information analysis and collection of the experience and knowledge of the experts.The research contents of this text include mainly:(1) Have carried on the summary in maintaining the development of the system and current situation both at home and abroad, And has studied to the present CMMS existing problem of thermal power plant of our country. Propose developing intelligence and maintaining the importance with systematic decision.(2) Use and judge the law and carry on decision research to the way of maintaining fuzzily synthetically by RCM.(3) Having studied the method of changing trend prediction of operation state of the equipment.(4) On the basis of trend prediction, studying the maintenance tactics decision of the equipment of state maintenance by RBF neural network.(5) Maintain the decision system and carry on preliminary research in developing the complementing machine equipment intelligence of thermal power plant, have proposed design philosophy and basic frame.