Intelligent ammeter fault real time prediction method based on decision-making tree

Abstract

Provided is an intelligent ammeter fault real time prediction method based on a decision-making tree, comprising the steps of: 1, pre-processing intelligent ammeter data of an electricity information acquisition system; 2, according to an intelligent ammeter fault determination model, screening the fault data of intelligent ammeters in the electricity information acquisition system and sending the fault data into an intelligent ammeter fault database; 3, dividing the historic data in the intelligent ammeter fault database into a training set and a test set, employing a decision-making tree algorithm to perform data excavation on the training set, and forming an intelligent ammeter fault decision-making tree and a preliminary classification rule; 4, through the data of the test set, performing accuracy assessment on the preliminary classification rule, determining the preliminary classification rule if the accuracy meets requirements, or else returning to the training set for training again; 5, generating an intelligent ammeter fault real time prediction model according to a finally determined classification rule; and 6, linking an intelligent ammeter real time fault database to the intelligent ammeter fault real time prediction model for real time prediction to obtain intelligent ammeter fault real time prediction results.

Description

technical field [0001] The invention relates to a fault prediction method for smart electric meters, in particular to a real-time fault prediction method for smart electric meters based on a decision tree. Background technique [0002] With the in-depth promotion of the construction of the "three collections and five majors" system of the State Grid Corporation of China, the construction of the electricity consumption information collection system promoted by the "big marketing" has taken shape, especially the smart energy meter has been widely promoted and applied. Once such a large number of smart meters fail, it will directly affect the vital interests of users and the security and stability of the society. Therefore, it is very important to predict the failure of smart meters in time and repair or replace them. [0003] With the widespread application of smart meters, operating faults are increasingly characterized by suddenness, multifacetedness, and complexity, and the...

AI Technical Summary

Problems solved by technology

The massive data provided by the electricity consumption information collection system just gives data mining technology a place to play, but in the field of smart meter fault prediction, the relevant research on data mining technology has not been carried out in depth.

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