Power Equipment Defects Prediction Based on the Joint Solution of Classification and Regression Problems Using Machine Learning Methods

Power Equipment Defects Prediction Based on the Joint Solution of Classification and Regression Problems Using Machine Learning Methods

Our paper proposes a method for constructing a system for predicting defects and failures of power equipment and the time of their occurrence based on the joint solution of regression and classification problems using machine learning methods. A distinctive feature of this method is the use of the e...

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Bibliographic Details
Main Authors: Ivan Shcherbatov, Evgeny Lisin, Andrey Rogalev, Grigory Tsurikov, Marek Dvořák, Wadim Strielkowski
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Electronics
Subjects:
defect forecasting system
power equipment
technical condition index
machine learning
neural network
SCADA
Online Access:https://www.mdpi.com/2079-9292/10/24/3145

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