Feature extraction for vibration-based fault detection in Permanent Magnet Synchronous Motors

This paper presents a study of different time and frequency indicators, extracted from vibration signals of a Permanent Magnet Synchronous Machine (PMSM), for fault detection and diagnosis purpose. First, a multi-physical model of the machine, able to generate the vibration displacement under differ...

Full description

Saved in:
Bibliographic Details
Main Authors: Alameh, K., Cite, N., Hoblos, G., Barakat, G.
Format: Conference Proceeding
Language:English
Subjects:
Analytical model
Analytical models
Atmospheric modeling
Demagnetization Fault
Eccentricity fault
Fault Detection
Feature extraction
Permanent Magnet Motors
Rotors
Stator windings
Time and Frequency Indicators
Vibration signal
Vibrations
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper presents a study of different time and frequency indicators, extracted from vibration signals of a Permanent Magnet Synchronous Machine (PMSM), for fault detection and diagnosis purpose. First, a multi-physical model of the machine, able to generate the vibration displacement under different operating conditions, is simulated. Then, a brief state-of-the-art on the most encountered machine faults, with their electromagnetic and mechanical signatures, is presented. In this study, both rotor eccentricity and Permanent Magnet (PM) demagnetization faults are considered and introduced in the model by changing some of its parameters. After that, time- and frequency-domains signal processing techniques are applied to extract crucial features sets, related to healthy and faulty cases, from vibration signals. The evolution of these indicators with respect to faults degrees is analyzed to select proper criteria for each one, which can be effectively used latter in fault detection and diagnosis applications.
DOI:10.1109/TAEECE.2015.7113620