Two-stage equipment fault diagnosis method

Abstract

The present invention relates to a two-stage equipment fault diagnosis method and relates to the technical field of equipment fault diagnosis. According to the method provided by the present invention, the steps of the prediction model can be adjusted according to the requirements of different response times, calculation capabilities, details of fault diagnosis types, the dependence on human factors of maintenance personnel can be reduced, the efficiency of equipment fault diagnosis can be improved, important references can be provided for the maintenance personnel to determine the equipment faults, and the method can play an important role in the equipment fault type diagnosis under different conditions.

Description

technical field [0001] The invention relates to the technical field of equipment fault diagnosis, in particular to a two-stage equipment fault diagnosis method. Background technique [0002] In the whole process of equipment maintenance support, the relationship between equipment failure phenomenon (or failure symptom) and failure cause (or failure unit) is complex, and has the characteristics of randomness and uncertainty. [0003] Due to the lack of reasoning ability and self-learning ability under inaccurate conditions, traditional fault diagnosis methods have exposed the disadvantages of low efficiency and high cost of fault diagnosis. [0004] Early fault diagnosis methods relied too much on the judgment of domain experts or experienced maintenance personnel, resulting in extremely subjective and high cost in the process of diagnosing faults. [0005] The general forecasting method ignores the time order factors of the acquisition of all feature sequences, resulting in...

AI Technical Summary

Problems solved by technology

Processing unbalanced data together will lead to overfitting, making the failure prediction effect unreliable

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