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A fault diagnosis method and pattern matching algorithm based on combination of expert knowledge and fuzzy reasoning is proposed.,Aiming at many problems faced by large scientific installations in fault diagnosis, such as it is difficult to establish an accurate mathematical model because of the failure mechanism is not clear, the diagnostic information is incomplete and inaccurate, so it is difficult to carry out deterministic inference and Diagnostic data limitations do not enable data-driven self-learning .The method solves many Uncertainty issues in the fault diagnosis process, and forms User-oriented fuzzy expert system fault diagnosis basic platform by ntroducing fuzzy factors in diagnostic knowledge and the use of database-based fuzzy knowledge modeling methods,which Has been initially applied in a large-scale laser drive device test platform and Achieved intelligent diagnosis of system failure.