Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

6-2011

Abstract

This paper studies the stator currents collected from several inverter-fed laboratory induction motors and proposes a new feature based frequency domain analysis method for performing the detection of induction motor faults, such as the broken rotor-bar or bearing fault. The mathematical formulation is presented to calculate the features, which are called FFT-ICA features in this paper. The obtained FFT-ICA features are normalized by using healthy motor as benchmarks to establish a feature database for fault detection. Compare with conventional frequency-domain analysis method, no prior knowledge of the motor parameters or other measurements are required for calculating features. Only one phase stator current waveforms are enough to provide consistent diagnosis of inverter-fed induction motors at different frequencies. The proposed method also outperforms our previous time domain analysis method.

Keywords

Fast Fourier Transform, Fault detection, Independent Component Analysis, Induction motors fed from inverter

Discipline

Operations Research, Systems Engineering and Industrial Engineering | Theory and Algorithms

Research Areas

Intelligent Systems and Optimization

Publication

2011 6th IEEE Conference on Industrial Electronics and Applications ICIEA: June 21-23, Beijing: Proceedings

First Page

27

Last Page

32

ISBN

9781424487554

Identifier

10.1109/ICIEA.2011.5975545

Publisher

IEEE

City or Country

Piscataway, NJ

Additional URL

https://doi.org/10.1109/ICIEA.2011.5975545

Download

Share

COinS