Equipment Fault Diagnosis Method and System Based on Bayesian Network

Abstract

The invention discloses a Bayesian network-based equipment fault diagnosis method and system. Wherein, the method can retrieve the physical model of the corresponding equipment from the memory and the failure condition probability information of the training data set after association rule mining according to the known faults of the equipment to be diagnosed, and give the known faults. The optimal fault diagnosis under the fault information recommends and stores the optimal fault diagnosis and stores the optimal fault diagnosis, which can fully consider the uncertainty of the information, and the diagnostic results given are the best under the current conditions. Solutions, rather than qualitative values, can update the database according to the actual diagnosis results to ensure the accuracy of diagnosis.

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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