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Shock and Vibration
Volume 2015, Article ID 420168, 14 pages
http://dx.doi.org/10.1155/2015/420168
Research Article

Principal Components of Superhigh-Dimensional Statistical Features and Support Vector Machine for Improving Identification Accuracies of Different Gear Crack Levels under Different Working Conditions

1Department of Systems Engineering and Engineering Management, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong
2School of Mechatronics Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, Sichuan 611731, China
3Department of Mechanical Engineering, University of Alberta, Edmonton, AB, Canada T6G 1H9

Received 16 March 2015; Revised 2 June 2015; Accepted 16 June 2015

Academic Editor: Matteo Aureli

Copyright © 2015 Dong Wang et al. 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.

How to Cite this Article

Dong Wang, Kwok-Leung Tsui, Peter W. Tse, and Ming J. Zuo, “Principal Components of Superhigh-Dimensional Statistical Features and Support Vector Machine for Improving Identification Accuracies of Different Gear Crack Levels under Different Working Conditions,” Shock and Vibration, vol. 2015, Article ID 420168, 14 pages, 2015. https://doi.org/10.1155/2015/420168.