Next Article in Journal
An Intelligent Space for Mobile Robot Localization Using a Multi-Camera System
Previous Article in Journal
Enclosed Electronic System for Force Measurements in Knee Implants
Article Menu

Export Article

Open AccessArticle
Sensors 2014, 14(8), 15022-15038; doi:10.3390/s140815022

Fault Detection of a Roller-Bearing System through the EMD of a Wavelet Denoised Signal

Department of Mechanical, Robotics and Energy Engineering, Dongguk University-Seoul, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea
*
Author to whom correspondence should be addressed.
Received: 26 May 2014 / Revised: 2 August 2014 / Accepted: 5 August 2014 / Published: 14 August 2014
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [2951 KB, uploaded 14 August 2014]   |  

Abstract

This paper investigates fault detection of a roller bearing system using a wavelet denoising scheme and proper orthogonal value (POV) of an intrinsic mode function (IMF) covariance matrix. The IMF of the bearing vibration signal is obtained through empirical mode decomposition (EMD). The signal screening process in the wavelet domain eliminates noise-corrupted portions that may lead to inaccurate prognosis of bearing conditions. We segmented the denoised bearing signal into several intervals, and decomposed each of them into IMFs. The first IMF of each segment is collected to become a covariance matrix for calculating the POV. We show that covariance matrices from healthy and damaged bearings exhibit different POV profiles, which can be a damage-sensitive feature. We also illustrate the conventional approach of feature extraction, of observing the kurtosis value of the measured signal, to compare the functionality of the proposed technique. The study demonstrates the feasibility of wavelet-based de-noising, and shows through laboratory experiments that tracking the proper orthogonal values of the covariance matrix of the IMF can be an effective and reliable measure for monitoring bearing fault. View Full-Text
Keywords: fault detection; wavelet de-noising; empirical mode decomposition; intrinsic mode function; proper orthogonal value fault detection; wavelet de-noising; empirical mode decomposition; intrinsic mode function; proper orthogonal value
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Ahn, J.-H.; Kwak, D.-H.; Koh, B.-H. Fault Detection of a Roller-Bearing System through the EMD of a Wavelet Denoised Signal. Sensors 2014, 14, 15022-15038.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top