Research Article | OPEN ACCESS
A Novel Fault Diagnosis Method for Gear Transmission Systems Using Combined Detection Technologies
1Zhichun Li and 2Wei Ding
1School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, China
2Nanyang Institute of Technology, Nanyang 470004, China
Research Journal of Applied Sciences, Engineering and Technology 2013 18:3354-3358
Received: December 13, 2012 | Accepted: January 19, 2013 | Published: October 10, 2013
Abstract
This study focuses on the condition monitoring and fault diagnosis of gear transmission systems. Since the gear transmission systems have been used in very wide applications, such as the aerospace engineering, manufacturing industry, marine engineering, etc., it is crucial to monitor the working condition of the gear transmission systems. For this purpose, a new method has been proposed in this study to investigate the condition monitoring and fault diagnosis of gear transmission systems. In the new method, the oil analysis and vibration analysis have been integrated to collect the fault signals of the gears. Then an intelligent classifier based on the Support Vector Machine (SVM) is adopted to diagnose the fault types of the gears. To verify the proposed approach, the fault experiments have been carried out in a gear fault simulator. The analysis results show that the lubricant information and vibration information can be well used for the accurate fault detection of the gears. The fault diagnosis rate reaches up to 91.7%. Hence, the proposed method can be used in practice for the condition monitoring and fault diagnosis of gear transmission systems.
Keywords:
Condition monitoring, fault diagnosis, gear transmission,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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