Next Article in Journal
Evaluation of Candidate Measures for Home-Based Screening of Sleep Disordered Breathing in Taiwanese Bus Drivers
Previous Article in Journal
Thermoresistive Strain Sensor and Positioning Method for Roll-to-Roll Processes
Article Menu

Export Article

Open AccessArticle
Sensors 2014, 14(5), 8096-8125; doi:10.3390/s140508096

Wayside Bearing Fault Diagnosis Based on a Data-Driven Doppler Effect Eliminator and Transient Model Analysis

1
Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
2
College of Electrical Engineering and Automation, Anhui University, Hefei 230093, China
*
Authors to whom correspondence should be addressed.
Received: 10 January 2014 / Revised: 26 April 2014 / Accepted: 28 April 2014 / Published: 5 May 2014
(This article belongs to the Section Physical Sensors)

Abstract

A fault diagnosis strategy based on the wayside acoustic monitoring technique is investigated for locomotive bearing fault diagnosis. Inspired by the transient modeling analysis method based on correlation filtering analysis, a so-called Parametric-Mother-Doppler-Wavelet (PMDW) is constructed with six parameters, including a center characteristic frequency and five kinematic model parameters. A Doppler effect eliminator containing a PMDW generator, a correlation filtering analysis module, and a signal resampler is invented to eliminate the Doppler effect embedded in the acoustic signal of the recorded bearing. Through the Doppler effect eliminator, the five kinematic model parameters can be identified based on the signal itself. Then, the signal resampler is applied to eliminate the Doppler effect using the identified parameters. With the ability to detect early bearing faults, the transient model analysis method is employed to detect localized bearing faults after the embedded Doppler effect is eliminated. The effectiveness of the proposed fault diagnosis strategy is verified via simulation studies and applications to diagnose locomotive roller bearing defects. View Full-Text
Keywords: fault diagnosis; locomotive bearing; wayside monitoring; Doppler effect; transient model fault diagnosis; locomotive bearing; wayside monitoring; Doppler effect; transient model
Figures

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

Liu, F.; Shen, C.; He, Q.; Zhang, A.; Liu, Y.; Kong, F. Wayside Bearing Fault Diagnosis Based on a Data-Driven Doppler Effect Eliminator and Transient Model Analysis. Sensors 2014, 14, 8096-8125.

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