Power equipment fault intelligent analysis method and system

Abstract

The invention discloses a power equipment fault intelligent analysis method and system, and the method comprises the steps: firstly collecting the fault information of power equipment of a transformer substation and a corresponding diagnosis result, constructing an equipment fault set, then monitoring the operation state of the power equipment in real time, and deleting the repeated information in the original fault information, thereby improving the diagnosis efficiency of a diagnosis system; all related information of cases in a database is traversed according to feature words of the deleted fault information, feature matching is carried out, and equipment fault diagnosis is carried out based on a Bayesian network; a corresponding processing scheme is determined according to the diagnosis result, the equipment fault is solved, the corresponding fault condition and the processing result are stored in a database, and key feature words influencing the fault are marked one by one in the fault information. According to the technical scheme, the limitation of manual management of the power equipment is effectively made up, data reference can be provided in real time, the equipment outage time caused by equipment faults can be effectively shortened, and small faults and common faults are reduced.

Description

technical field [0001] The invention belongs to the field of electric equipment maintenance, and in particular relates to an intelligent analysis method and system for electric equipment faults. Background technique [0002] The substation is an important place in the power system to change the voltage level, collect current and receive and distribute electric energy. However, due to the complexity of the substation's own structure and construction environment, the probability of damage and failure of substation equipment has increased significantly. It is of great significance to the safe operation of the substation to detect the operating status of the equipment and find out the fault in time. [0003] At present, it is difficult to find solutions to the daily operation problems of substation equipment in books. For a long time, operators often manage substation equipment based on years of accumulated experience. However, the accumulation of these experiences requires a ...

AI Technical Summary

Problems solved by technology

When diagnosing substation component faults, because of the characteristics of substation fault manifestations such as diversity, uncertainty, and blind feature extraction, the extracted fault feature information contains a large amount of redundant or mismatched information, which affects the timeliness of diagnosis. performance and rapidity, and the calculation workload is greatly increased, so these redundant information must be reduced to make the result more accurate

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