Equipment fault diagnosis method and system based on bayesian network

Abstract

The invention discloses a device fault diagnosis method and a device fault diagnosis system based on a Bayesian network. Wherein the method may be based on a known fault of an input device to be diagnosed, a physical model of a corresponding device and failure condition probability information of the training data set after association rule mining are retrieved from a memory, the optimal fault diagnosis recommendation under the known fault information is given and the optimal fault diagnosis is stored and the optimal fault diagnosis is stored, fully considering the uncertainty of information,the diagnosis results are the optimal solution under the current conditions, not the qualitative value. The database can be updated according to the actual diagnosis results to ensure the accuracy ofdiagnosis.

Description

technical field [0001] The invention relates to the technical field of equipment fault diagnosis, in particular to a Bayesian network-based equipment fault diagnosis method and system. Background technique [0002] At present, the equipment fault diagnosis scheme developed and designed in the industry is relatively complete in function and can meet the needs of most cases. However, when it is used, it either ignores the uncertainty of information and gives a single diagnosis result; or completes multiple guidelines sequentially according to the established procedures and processes, and does not update the database according to the actual diagnosis results, so the accuracy of diagnosis cannot be guaranteed. Contents of the invention [0003] The purpose of the present invention is to propose a method and system for equipment fault diagnosis based on Bayesian network, which can fully consider the uncertainty of information, and the diagnosis results given are the optimal sol...

AI Technical Summary

Problems solved by technology

However, when it is used, it either ignores the uncertainty of information and gives a single diagnosis result; or completes multiple guidelines sequentially according to the established procedures and processes, and does not update the database according to the actual diagnosis results, so the accuracy of diagnosis cannot be guaranteed.

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