Equipment fault diagnosis method

The invention belongs to the technical field of equipment operation guarantee, and particularly relates to an equipment fault diagnosis method. The method comprises the following steps: determining the category, rated parameters and initial life cycle of research equipment; establishing an expert system model rule base according to object category characteristics; establishing an object historical database; introducing an artificial neural network to model a high-dimensional nonlinear problem; fault diagnosis is realized by using a BP neural network; according to the equipment fault diagnosis method, technologies such as big data and an artificial intelligence algorithm are introduced to digitalize, model and standardize equipment rated parameters, equipment operation conditions, equipment operation and maintenance history and experience and the like, meanwhile, a diagnosis system is endowed with intelligent learning and changing capabilities, and debugging parameters are fed back and corrected according to r