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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2005, Vol. 6 Issue ( 5): 13-    DOI: 10.1631/jzus.2005.A0433
    
Support Vector Machine for mechanical faults classification
JIANG Zhi-qiang, FU Han-guang, LI Ling-jun
Zhengzhou Aeronautical Institute of Industry Management, Zhengzhou 450015, China; Beijing Researching Institute for Metallurgical Equipment, Beijing 100029, China; School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
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Abstract  Support Vector Machine (SVM) is a machine learning algorithm based on the Statistical Learning Theory (SLT), which can get good classification effects with a few learning samples. SVM represents a new approach to pattern classification and has been shown

Key words： Aeronautical Industry Management Metallurgical Equipment Mechanical Engineering Support Vector Machine (SVM)      Fault diagnosis      Multi-fault classification      Intelligent diagnosis     
Received: 03 October 2003     
CLC:  TH17  
  TP18  
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JIANG Zhi-qiang
FU Han-guang
LI Ling-jun
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JIANG Zhi-qiang, FU Han-guang, LI Ling-jun. Support Vector Machine for mechanical faults classification. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2005, 6( 5): 13-.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2005.A0433     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2005/V6/I 5/13

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