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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2007, Vol. 28 ›› Issue (5): 1085-1090.

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Classification Method of Diverse AdaBoost-SVM and Its Application  to Fault Diagnosis of Aeroengine

Hu Jinhai,Xie Shousheng,Cai Kailong,He Xiuran,Peng Jingbo   

  1. The Engineering Institute, Airforce Engineering University
  • Received:2006-09-01 Revised:2007-04-02 Online:2007-10-15 Published:2007-10-15
  • Contact: Hu Jinhai

Abstract:

A novel approach of fault diagnosis named Diverse AdaBoost-SVM is presented,which uses SVM considering the accuracy/diversity dilemma as weak learner for AdaBoost.The proposed method successfully solves the dilemma in AdaBoost algorithm by selecting more diverse weak learners in those moderately accurate ones, meanwhile overcomes the difficulty of selection of weak learner parameter and learning cycles  T  in the existing AdaBoost methods.

Key words: aeroengine,  , fault , diagnosis,  , ensemble , of , classification , methods,  , Adaboost,  , accuracy/diversity,  , SVM

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