Abnormity detection method and device for electric power metering terminal, computer equipment and medium

Abstract

The invention relates to an abnormity detection method and device for an electric power metering terminal, computer equipment and a medium. The method comprises the steps of performing dimension reduction processing on a plurality of obtained target data sets based on a principal component analysis method to obtain a principal component matrix; calculating a weighted distance between each row of elements in the principal component matrix; based on a fuzzy C-means clustering algorithm, performing clustering flight on each row of elements in the principal component matrix according to the weighted distance to obtain a membership matrix; and judging whether the electric power metering terminal is abnormal according to the membership matrix. According to the abnormity detection method for theelectric power metering terminal, the distortion problem in clustering analysis can be avoided, so that the clustering effect can be improved, and whether the electric power metering terminal is abnormal can be accurately judged.

Description

technical field [0001] The present invention relates to the technical field of electric power detection, in particular to a method, device, computer equipment and medium for abnormal detection of electric power metering terminals. Background technique [0002] At present, the power metering system is usually a power metering automation system. The system can realize the centralized detection and orderly power distribution of the user's power load, and can reduce the loss of the user's power failure and ensure the balance of supply and demand of the entire power grid. Therefore, it is very important to detect whether there is anomaly in the power metering terminal in the power metering system. The processing process of detecting abnormalities in power metering terminals is usually to find abnormalities, identify them, report for review, result verification, and on-site maintenance. The entire processing process will consume a lot of manpower and material resources. [0003]...

AI Technical Summary

Problems solved by technology

However, the traditional clustering analysis algorithm is usually classified according to the relationship between the data, which requires the data to be of the same importance and independent of each other.

However, there will inevitably be a high degree of correlation between the data of power metering terminals, so the traditional clustering analysis algorithm is less applicable

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