Rotor Fault Diagnostic of Inverter Fed Induction Motor Using Frequency Analysis

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Researchers

Research units

  • Tallinn University of Technology

Abstract

Condition monitoring of electrical machines is essential in industrial operations for improving workplace safety and ensuring reliable and economical exploitation of the machines. Motor current signature analysis (MCSA) monitoring technique is gaining heightened popularity due to the simplicity of its algorithms and the least number of sensors required. In this paper, the harmonic spectrum of industrial inverter fed induction motor is investigated for the detection of broken rotor bars. To improve the legibility of the spectrum, the fundamental component is attenuated using infinite impulse response (IIR) filter because of its good transition band, less passband ripples and low order. The results are first taken from finite element method (FEM) based simulation, where the motor is fed with pure sinusoidal current and only faulty and spatial frequencies are investigated and used as a benchmark. The practical results are based on the measurements taken from the laboratory setup, where the motor under investigation is fed through an industrial inverter working under scalar control mode. The data acquisition is done with a good sampling rate of 100 kHz for better resolution.

Details

Original languageEnglish
Title of host publicationProceedings of the 2019 IEEE 12th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2019
Publication statusPublished - 1 Aug 2019
MoE publication typeA4 Article in a conference publication
EventIEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives - Toulouse, France
Duration: 27 Aug 201930 Aug 2019
Conference number: 12

Conference

ConferenceIEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives
Abbreviated titleSDEMPED
CountryFrance
CityToulouse
Period27/08/201930/08/2019

    Research areas

  • Fast Fourier transform, Fault diagnosis, Harmonic analysis, Induction motors

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