Journal of Systems Engineering and Electronics ›› 2012, Vol. 34 ›› Issue (12): 2554-2558.doi: 10.3969/j.issn.1001-506X.2012.12.26

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Fault diagnosis approach based on fuzzy chance constrained SVDD

QIN Liang, ZHOU Shao-lei, SHI Xian-jun, ZHANG Shu-tuan   

  1. Department of Control Engineering, Naval Aeronautical and Astronautical University, Yantai 264001, China
  • Online:2012-12-25 Published:2010-01-03

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Abstract:

Aiming at the problem of multi-fault pattern recognition for uncertain data, a method based on support vector data description is proposed. The possibility measure is introduced into support vector data description (SVDD) as a constraint condition. First, the programming is transformed into its dual form. Then, a fast training method based on sequential minimal optimization (SMO) is developed to get the result. Finally, a multi-class SVDD model is established based on one-class SVDD. Numeric experiments show that the accuracy and speed of classification are improved, and this method is suitable for practical use.

CLC Number: 

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