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A Fast Intuitionistic Fuzzy Support Vector Machine Algorithm and Its Application in Wind Turbine Gearboxes Fault Diagnosis

  • Bin Jiao
  • Qing Zhang
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 323)

Abstract

Support vector machine has been successfully applied to the fault diagnosis field, but there are still some problems in practical applications. In this paper we proposed an improved algorithm which reduces the number of support vectors through the reduction of the sample spae to improve the efficiency of the algorithm. As the traditional fuzzy support vector machine cannot classify the sample with the same membership, so we use intuition index to lower the probability of the sample to get the same membership. Here we improve the accuracy of the algorithm through properly redefine the fuzzy membership and intuition index. Finally, we use the improved algorithm to build a multi-classifier based on one against one principle and the voting rules, and apply the multi-classification algorithm to the wind turbine gearbox fault diagnosis. The diagnose results prove that the improved algorithm we proposed can properly resolve the problem of wind turbine gearboxes fault diagnosis.

Keywords

wind turbine gearbox fault diagnosis intuitionistic fuzzy support vector machine 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Bin Jiao
    • 1
    • 2
  • Qing Zhang
    • 1
    • 2
  1. 1.Shanghai DianJi UniversityShanghaiChina
  2. 2.East China University of Science and TechnologyShanghaiChina

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