Research On State Maintenance Of Electric Energy Metering Device Based On Artificial Intelligence Technology

Electric energy metering is of great significance to power supply enterprises because it directly affects part of the income of power enterprises.Moreover,accurate measurement is also the key element to the trust between power enterprises and users.At the present stage,behind the vigorous development of the power market,higher management requirements are also put forward for the work related to energy metering.It is necessary to ensure the accurate and reliable metering of energy metering devices.At the same time,with the increasing number of users and the expanding scope of power supply,the increasing workload directly leads to the disproportionate scale between the operation and maintenance managers and the power metering equipment to be maintained,and the staff can not handle such a large number of power metering equipment;In addition,with the increasing economic awareness of users,their requirement of metering accuracy is also gradually improving,which is not enough to rely on improving the level of measurement management,but also fundamentally rely on the progress and development of science and technology to achieve.At present,thanks to various computer operating systems,database technology,cloud computing functions and rapid development,especially the wide application of Internet network technology,we have more freedom to choose new technical means in measurement management to promote the improvement of management level.On the basis of introducing the research background and significance of condition-based maintenance technology for electric energy metering devices,comparing and analyzing the differences between domestic and foreign equipment condition-based maintenance technology,this paper introduces the basic concept and main structure of electric energy metering device system,and then analyses and designs the implementation method of artificial intelligence technology applied to the condition-based maintenance of electric energy metering devices in detail,which supplies power to Guangzhou.The load data collected by the metrology automation system of Guangzhou Power Supply are used as data sources for analysis and research,and the corresponding theoretical and empirical criteria are obtained.This paper focuses on the combination of artificial intelligence technology and condition-based maintenance of electric energy metering devices,studies the realization method of crossover algorithm and BP neural network in condition-based maintenance of electric energy metering devices,and establishes two schemes of condition-based maintenance technology based on crossover algorithm and BP neural network through secondary processing of the collected data of measurement automation system.The operation status of the device is analyzed theoretically,and the comprehensive evaluation of the condition-based maintenance of the electric energy metering device is realized through the analysis of practical cases,which verifies the feasibility of the research results and ensures the safe,stable,accurate and reliable operation of the electric energy metering device.