Next Article in Journal
On Some Properties of Tsallis Hypoentropies and Hypodivergences
Next Article in Special Issue
The Property of Chaotic Orbits with Lower Positions of Numerical Solutions in the Logistic Map
Previous Article in Journal
Redundancy of Exchangeable Estimators
Article Menu

Export Article

Open AccessArticle
Entropy 2014, 16(10), 5358-5376; doi:10.3390/e16105358

Research and Development of a Chaotic Signal Synchronization Error Dynamics-Based Ball Bearing Fault Diagnostor

1
Department of Electrical Engineering , National Chin-Yi University of Technology, No.57, Sec. 2, Zhongshan Rd., Taiping Dist., Taichung 41170, Taiwan
2
Department of Aeronautics and Astronautics, National Cheng Kung University, No.1, University Road, Tainan City 701, Taiwan
*
Author to whom correspondence should be addressed.
Received: 30 August 2014 / Revised: 5 October 2014 / Accepted: 8 October 2014 / Published: 15 October 2014
(This article belongs to the Special Issue Recent Advances in Chaos Theory and Complex Networks)
View Full-Text   |   Download PDF [2759 KB, uploaded 24 February 2015]   |  

Abstract

This paper describes the fault diagnosis in the operation of industrial ball bearings. In order to cluster the very small differential signals of the four classic fault types of the ball bearing system, the chaos synchronization (CS) concept is used in this study as the chaos system is very sensitive to a system’s variation such as initial conditions or system parameters. In this study, the Chen-Lee chaotic system was used to load the normal and fault signals of the bearings into the chaos synchronization error dynamics system. The fractal theory was applied to determine the fractal dimension and lacunarity from the CS error dynamics. Extenics theory was then applied to distinguish the state of the bearing faults. This study also compared the proposed method with discrete Fourier transform and wavelet packet analysis. According to the results, it is shown that the proposed chaos synchronization method combined with extenics theory can separate the characteristics (fractal dimension vs. lacunarity) completely. Therefore, it has a better fault diagnosis rate than the two traditional signal processing methods, i.e., Fourier transform and wavelet packet analysis combined with extenics theory. View Full-Text
Keywords: ball bearing; chaos synchronization error dynamics; fractal theory; extenics theory ball bearing; chaos synchronization error dynamics; fractal theory; extenics theory
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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

Kuo, Y.-C.; Hsieh, C.-T.; Yau, H.-T.; Li, Y.-C. Research and Development of a Chaotic Signal Synchronization Error Dynamics-Based Ball Bearing Fault Diagnostor. Entropy 2014, 16, 5358-5376.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top