DocumentCode :
2151128
Title :
Gear fault diagnosis based on SVM
Author :
Ma, Shang-jun ; Liu, Geng ; Xu, Yongqiang
Author_Institution :
Sch. of Mechatronical Eng., Northwestern Polytech. Univ., Xi´´an, China
fYear :
2010
fDate :
11-14 July 2010
Firstpage :
140
Lastpage :
143
Abstract :
Elements of Support Vector Machine was applied to the fault diagnosis of gear system, and the two-class algorithms for 3 individual fault modes, which are No Fault Gear Mode, Crack of Dedendum Mode and Tooth Surface Abrasion Mode respectively, are well developed and set up. Through the training and testing simulation data samples and the signal samples from gear oscillation, these 3 different types of gear fault modes are finally identified and distinguished from each other at the rotating speed of 300r/min and 900r/min. The result validates that the Support Vector Machine is with excellent diagnostic ability in the fault diagnosis system of gear and with favorable prospect in this filed of application.
Keywords :
abrasion; cracks; fault diagnosis; gears; maintenance engineering; mechanical engineering computing; support vector machines; SVM; crack; dedendum mode; gear fault diagnosis; gear fault modes; support vector machine; tooth surface abrasion mode; Classification algorithms; Fault diagnosis; Gears; Kernel; Support vector machines; Testing; Training; Fault diagnosis; Feature extraction; Gear system; Support Vector Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wavelet Analysis and Pattern Recognition (ICWAPR), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6530-9
Type :
conf
DOI :
10.1109/ICWAPR.2010.5576299
Filename :
5576299
Link To Document :
بازگشت