Power generator fault diagnosis and health state evaluation method and electronic equipment

Abstract

The invention relates to a power generator fault diagnosis and health state evaluation method and electronic equipment. The method comprises the steps: acquiring state monitoring data of a power generator; preprocessing the state monitoring data to obtain preprocessed data; carrying out clustering processing on the preprocessed data to obtain clustering data; carrying out anomaly detection processing on the clustering data to obtain a predicted value; and carrying out fault diagnosis and health state evaluation on the power generator based on the predicted value. According to the method, fault diagnosis of the power generator can be realized, health assessment of the power generator can be realized, the defects of a traditional state detection and fault diagnosis method are avoided, the state monitoring and fault diagnosis efficiency of the power generator is further improved, the safety performance of a nuclear power unit is improved, and the practical engineering application value is improved.

Description

technical field [0001] The invention relates to the technical field of generator fault diagnosis, more specifically, to a generator fault diagnosis and health state evaluation method and electronic equipment. Background technique [0002] The safe and stable operation of generators is a prerequisite for the stable operation of nuclear power units. Real-time status monitoring and fault diagnosis of generators can detect potential abnormalities in time, which is of great significance to ensure the stable operation of generators. Generators are generally composed of stators, rotors, end covers, machine bases, bearings and other components, and each individual component is composed of many components. Since the components of the generator are too complex, how to effectively design the monitoring points of the generator and effectively extract the status information of the generator is particularly difficult. Therefore, effective condition monitoring and fault diagnosis of gener...

AI Technical Summary

Problems solved by technology

[0003] The current difficulties in fault diagnosis are as follows: 1) The component parts of the generator are too complex, resulting in many interference sources, and it is difficult to accurately extract the effective fault characteristic information of the generator;

[0004] 2) There is a gap between theoretical research and engineering application of fault diagnosis, and some fault diagnosis techniques cannot be directly used in generators

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