Electricity metering equipment fault analysis method and device

Abstract

The invention discloses an electricity metering equipment fault analysis method and device. The method comprises steps that source data related to faults of electricity metering equipment are acquired; data cleaning of the source data is carried out; characteristic item selection of the source data after data cleaning is carried out; selected characteristic items are made to be sample data, and the sample data comprises training data, test data and prediction data; the training data and the test data are loaded into a machine learning model established based on the Xgboost algorithm, and the model is trained and tested; the prediction data is loaded into the trained model, and the electricity metering equipment fault analysis result is acquired . The method is advantaged in that accuracy of electricity metering equipment fault analysis can be improved, manpower resource cost is reduced, and efficiency is improved.

Description

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine

Login to view more

AI Technical Summary

Problems solved by technology

Although this method can find some measurement abnormalities to a certain extent, there are large errors through on-site verification.

The threshold value in this method is a range. How to set the threshold value as the most suitable

Images