Aiming at the common faults of industrial boilers, a boiler fault diagnosis technology based on data mining method is proposed. By establishing an intelligent data mining tool, fault diagnosis knowledge is directly obtained from a large amount of real-time data for fault diagnosis. The core of the data mining tool is to use information entropy technology to assist the generation of the initial population of the genetic algorithm. The effective integration of genetic algorithm and information entropy greatly improves the working performance of the data mining method. This method is applied to a complex fault case of a thermal power plant boiler. The results show that its diagnostic accuracy can meet the requirements of field application.
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