Authors: V.G. Kashirskikh, A.N. Gargaev, V.M. Zavyalov, I.Yu. Semykina

Title of the article: Computer system for electric drives fault diagnosis of mining shovels

Year: 2016, Issue: 6, Pages: 159-168

Branch of knowledge: Electrical engineering

Index UDK: 621.313.33:62-83

DOI: -

Abstract: Electric drives fault diagnosis of mining shovels is suggested to carry out based on the results of monitoring for current electromagnetic and mechanical parameters, and variables of electric drives obtained during their operation using modern computer technology. The paper showed the structure of developed system of fault diagnosis that allows controlling the state of electric drive and detecting emerging faults. To determine in real time the current parameters and variables of DC motor, which during their operation can’t be measured, was used dynamic identification based on the measured current and voltage of the motor windings, and mathematical estimation methods. Parameters of the mechanical subsystem of electric drive are identified by a mobile measuring system. The authors also give the structure and characteristics of the one-step neural network predictor of current, used to predict the current in the armature and field windings of motor. Analysis of the technical state of electric drive on the strength of diagnostic features is performed in a special analyzer, built on the basis of pre-trained artificial neural network. The results of these studies support the possibility of creating a diagnostic system for the main electric drives of mining shovels using estimation methods and apparatus of artificial neural networks.

Key words: electric drive DC motor diagnosis dynamic identification estimation predictor artificial neural network

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