Electric energy meter operation state monitoring method based on genetic algorithm and social agglomeration

Abstract

The invention relates to an electric energy meter operation state monitoring method based on a genetic algorithm and social agglomeration, and the method comprises the following steps: 1) obtaining the basic data of a to-be-detected electric energy meter, and extracting the power utilization characteristic parameters of the to-be-detected electric energy meter; 2) on the basis of the power utilization characteristic parameters, acquiring the operation state of the to-be-tested electric energy meter by adopting an electric energy meter state evaluation model based on a genetic algorithm and a multivariate neural network; wherein the power utilization characteristic parameters are selected according to electric energy meter operation state correlation factors, and the electric energy meter operation state correlation factors are determined based on a social agglomeration algorithm. Compared with the prior art, the method has the advantages of promoting the state alternation of the electric energy meter to be reasonable and intelligent, timely discovering the fault meter and the electric energy meter with potential quality hazards, guaranteeing the operation quality level of the electric energy meter and the like.

Description

technical field [0001] The invention relates to a method for monitoring the state of an electric energy meter, in particular to a method for monitoring the operating state of an electric energy meter based on a genetic algorithm and community clustering. Background technique [0002] As a statutory measuring instrument, the electric energy meter is responsible for the measurement, storage and transmission of important information such as voltage, current, and electric energy. The accuracy and timeliness of electric energy measurement and information transmission are related to the quality and efficiency of electricity bill settlement between the power company and customers. . For the millions of operating electric energy meters that measure a large amount of electricity, at present, regular on-site inspections are generally used to monitor their operating status. The huge amount of investment in transportation and manpower is difficult to meet the current management directi...

AI Technical Summary

Problems solved by technology

The investment in transportation and manpower is huge, and it is difficult to meet the current management direction of reducing staff and increasing efficiency.

At the same time, with the advancement of science and technology and the improvement of product quality, the on-site operation failure rate of electric energy meters is getting lower and lower, and frequent on-site inspections lack practical significance

[0003] Judging the operation status of the entire batch of electric energy meters based on the results of sampling inspections, and based on this to determine the entire batch of electric energy meters to rotate or continue to use the random inspection supervision method is currently a method of evaluating the operating state of electric energy and operating replacement methods that are commonly used. The method is more troublesome

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