On-line diagnosing method for faults of metering production facility

Abstract

The invention discloses an on-line diagnosing method for faults of a metering production facility. The method comprises the following steps that firstly, centralized monitoring data are collected; secondly, a diagnosing expert base (training sample) is established; thirdly, a fault prediction model based on an artificial neural network is established; fourthly, on-line diagnosis is carried out on the faults of the metering production facility. All of hardware production units of the metering production facility are provided with alarming equipment, however, when the faults actually occur, production is usually already influenced, and the alarming equipment does not send alarms aiming at production anomalies and some equipment faults. An on-line diagnosing system for the metering production facility constantly analyzes 'four-line-one-storeroom' system running data, a current system running state is judged, the faults are predicted, when the production anomalies or the equipment faults are predicted, staff can solve the problems in time, threats which might influence the production are eliminated, and the reliability of the metering production facility is greatly improved.

Description

technical field [0001] The invention relates to the technical field of electricity utilization in electric power systems, in particular to an online fault diagnosis method for metering production facilities. Background technique [0002] Metering production facilities "four lines and one warehouse" (single-phase smart energy meter automatic verification line, three-phase smart energy meter automatic verification line, low-voltage current transformer automatic detection line, power collection terminal automatic detection line, intelligent storage warehouse) each The monitoring data of the sub-control system is sent to the pre-acquisition server, and the centralized monitoring data of the metering center is collected. On this basis, the application of online fault diagnosis based on artificial neural network in the metering center is carried out. [0003] First sort out a large amount of centralized monitoring data, analyze the monitoring data of normal and faulty metering pr...

AI Technical Summary

Problems solved by technology

However, how to effectively ensure the reliability of metering automation production facilities and how to find problems in time are considered to be a major problem affecting the production of metering centers

[0005] 1. Each hardware production unit of the metering production facility has alarm equipment, but when the fault actually occurs, it has often affected production, and for production abnormalities and certain equipment failures, the alarm device of the production unit will not alarm. In this way, the metering production facility Reliability cannot be guaranteed at all

[0006] 2. For locating production abnormalities and equipment failures, the metering center mainly relies on traditional manual analysis methods, relying on work experience to analyze monitoring data and locate faults. The positioning accuracy is not high, it takes a lot of time, and the work efficiency is low, which directly affects The capacity of the whole production line

A failure of a production unit, if not resolved in time, will cause multiple production units on a production line to alarm, making it more difficult to manually locate the fault

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