Method for intelligently diagnosing electric energy meter

Abstract

The invention relates to a method for intelligently diagnosing an electric energy meter. The method includes the following steps: 1. acquiring data of an electric energy meter and event data through field detection and an electric energy information acquiring system; 2. analyzing single faults the data of the electric energy meter and the event data which are acquired from 1, single faults analysis including 6 types of intelligent diagnosis analysis models of which each includes a plurality of intelligent diagnosis themes; 3. analyzing fault association of the association relations among different intelligent diagnosis themes and establishing an association model so as to obtain the result of further intelligent diagnosis; 4. and outputting the result of the single fault diagnosis of the intelligent diagnosis themes from 2 and the result of further intelligent diagnosis from 3 to a field detection worker, helping the field detection worker to detect and diagnose the electric energy meter. According to the invention, the method diagnoses and analyzes the operation of the electric energy meter through data comparison, statistics analysis and data mining, which can effectively determine whether the electric energy meter works normally.

Description

technical field [0001] The invention belongs to the technical field of power quality detection, in particular to an intelligent diagnosis method for an electric energy meter. Background technique [0002] In recent years, with the expansion of domestic power demand and power grid scale, the voltage level has been continuously improved, and the number of large-capacity and high-voltage level users has continued to increase. It has become the focus of social attention. During the detection process, the accuracy of the diagnosis of the electric energy meter is higher. In the existing detection process, the electric energy meter diagnosis is mainly carried out in the electric energy meter field by manual methods. The quantitative and accurate judgment of the programmed method relies on manual experience data to judge, which is easy to cause inaccurate or misdiagnosed diagnosis, and it is difficult to meet the needs of lean measurement management. SUMMARY OF THE INVENTION [0...

AI Technical Summary

Problems solved by technology

[0002] In recent years, with the expansion of domestic power demand and grid scale, the voltage level has been continuously improved, and the number of large-capacity and high-voltage users has continued to increase. It has become the focus of social attention. During the detection process, the accuracy of electric energy meter diagnosis is required to be higher. In the existing detection process, electric energy meter diagnosis is mainly carried out manually at the electric energy meter site. There is a lack of data support on site, and illegally passed Quantitative and accurate judgments by procedural methods are all based on manual experience data, which can easily lead to inaccurate or misdiagnosed situations, and it is difficult to meet the needs of lean management of measurement

Images