Power equipment fault probability prediction method and system considering insulation defect types and fault relevance

Abstract

The invention discloses a power equipment fault probability prediction method considering insulation defect categories and fault relevance. The method comprises the following steps: (1) collecting PRPS map data of power equipment and preprocessing the PRPS map data; (2) extracting partial discharge characteristics based on the pre-processed PRPS atlas data; (3) inputting the partial discharge characteristics into a trained convolutional neural network, and outputting a probability value P (Dk) that the power equipment has a certain type of insulation defects through the trained convolutional neural network; inputting the partial discharge characteristics into a trained long-short-term memory neural network, and enabling the trained long-short-term memory neural network to output the faultprobability P (F | Dk) of the power equipment under the condition of Dk; and (4) obtaining the final fault probability P (F) of the power equipment based on the following formula. In addition, the invention also discloses a power equipment fault probability prediction system.

Description

technical field [0001] The invention relates to a fault prediction method and system in an electric power system, in particular to a fault probability prediction method and system for electric equipment. Background technique [0002] Gas-insulated switchgear (GIS) is widely used in power systems, and its internal structure is complex. It is difficult to repair after a fault occurs, and it is easy to cause heavy losses. There are many reasons for the failure of GIS equipment, mainly due to insulation defects, accompanied by partial discharge. It is of great significance to analyze the severity of defects based on partial discharge signals, conduct risk assessment, and then carry out effective early warning and formulate reasonable maintenance strategies based on the assessment results, which are of great significance to ensure the safe and reliable operation of equipment. The risk assessment model is a model that combines probability to predict and evaluate the possible cons...

AI Technical Summary

Problems solved by technology

However, there are few studies on risk assessment or failure probability calculation for GIS equipment

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