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Proceedings of the 2nd International Symposium on Information Processing (ISIP 2009)

Huangshan, China, August 21-23, 2009

Editors: Fei Yu, Jian Shu, and Guangxue Yue

AP Catalog Number: AP-PROC-CS-09CN002

ISBN: 978-952-5726-02-2 (Print), 978-952-5726-03-9 (CD-ROM)

Page(s): 372-376

The Application of Binary Tree-Based Fuzzy SVM Multi-Classification Algorithm to Fault Diagnosis on the Gearbox of Ships

Zhan Yulong, Tan Qinming, and Liu Zuancang

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Support Vector MachineSVMis widely applied to fault diagnosis of machines. However, this classification method has some weaknesses. For example, it can not separate fuzzy information, particularly sensitive to the interference and the isolated points of the training samples. Besides, it has great demand for memory in calculation. In view of the problems mentioned above, a binary tree-based fuzzy SVM multi-classification algorithm (BTFSVM) has been put forward. This paper focuses on the study of the application of the theory BTFSVM to fault diagnosis on the gearbox of ships. Simulation experiments show that the algorithm has better anti-interference ability and classification effects than others. Consideration should be taken into account that it can be further applicable to the diagnosis on other mechanical faults of ships.

Index Terms

binary tree, FSVM, gearbox, fault diagnosis

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