Home            Contact us            FAQs
    
      Journal Home      |      Aim & Scope     |     Author(s) Information      |      Editorial Board      |      MSP Download Statistics

     Research Journal of Applied Sciences, Engineering and Technology

    Abstract
2013(Vol.6, Issue:18)
Article Information:

A Novel Fault Diagnosis Method for Gear Transmission Systems Using Combined Detection Technologies

Zhichun Li and Wei Ding
Corresponding Author:  Zhichun Li 
Submitted: 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.

Key words:  Condition monitoring, fault diagnosis, gear transmission, , , ,
Abstract PDF HTML
Cite this Reference:
Zhichun Li and Wei Ding, . A Novel Fault Diagnosis Method for Gear Transmission Systems Using Combined Detection Technologies. Research Journal of Applied Sciences, Engineering and Technology, (18): 3354-3358.
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Information
   Sales & Services
Home   |  Contact us   |  About us   |  Privacy Policy
Copyright © 2024. MAXWELL Scientific Publication Corp., All rights reserved