Abstract

The paper discusses the method of identifying the technical condition of induction motors by classifying the energy data coming from the main common power bus. The work shows the simulation results of induction motor operation. The correlation between occurring defects and current diagrams is presented. The developed simulation model is demonstrated. The general algorithm for conducting experiments is described. Five different experiments to develop an algorithm for the classification are conducted: determination of the motors number in operation with different power; determination of the motors number in operation with equal power; determination of the mode and load of induction electric motor; determination of the fault and its magnitude with regard to operation and load of induction motor; determination of the fault and its magnitude with regard to operation and load of induction motor with regard to non-linear load in the flow. The article also presents an algorithm for preprocessing data to solve the classification problem. In addition, the classification results are shown and recommendations for testing and using the classification algorithm on a real object are made.

Highlights

  • One of the significant trends resulting from the growing technological, environmental, economic and social challenges to the fuel, energy and mineral complex is the transition to industry 4.0 production enterprises [1]

  • Digitalization, is taking place, based on a redesign of business forms focused on the digital representation of data [2]

  • The electric motor is a key link in the emergence of robotic production and autonomous factories, as well as in the development of remote areas [5]

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Summary

Introduction

One of the significant trends resulting from the growing technological, environmental, economic and social challenges to the fuel, energy and mineral complex is the transition to industry 4.0 production enterprises [1]. Despite the fact that an enterprise within the framework of digital transformation strives to switch to state forecasting of its assets, the complexity and high cost of applying damage detection and control systems for each piece of equipment are not conducive to enterprises changing the existing system of regulated repair [7]. This system involves a transition from electrical equipment to components with new products at fixed intervals. The economic effect of repair work is often unreasonably low

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