Rotor Fault Diagnostic of Inverter Fed Induction Motor Using Frequency Analysis

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Tutkijat

Organisaatiot

  • Tallinn University of Technology

Kuvaus

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.

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoProceedings of the 2019 IEEE 12th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2019
TilaJulkaistu - 1 elokuuta 2019
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaIEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives - Toulouse, Ranska
Kesto: 27 elokuuta 201930 elokuuta 2019
Konferenssinumero: 12

Conference

ConferenceIEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives
LyhennettäSDEMPED
MaaRanska
KaupunkiToulouse
Ajanjakso27/08/201930/08/2019

ID: 38613489