FAULT DIGNOSIS OF GEAR BASED ON KPCA and ECOC-SVM

an QIU Mian-hao WANG Zi-ying AN Gang LIU Dong-li

Journal of Vibration and Shock ›› 2009, Vol. 28 ›› Issue (5) : 1-5.

PDF(1755 KB)
PDF(1755 KB)
Journal of Vibration and Shock ›› 2009, Vol. 28 ›› Issue (5) : 1-5.
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FAULT DIGNOSIS OF GEAR BASED ON KPCA and ECOC-SVM

  • an QIU Mian-hao WANG Zi-ying AN Gang LIU Dong-li
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Abstract

Abstract:, A method was proposed based on combination of KPCA with ECOC-SVM to enhance accuracy of fault diagnosis of gear. Firstly, original sample vector was preprocessed based on KPCA to eliminate noise and redundancy. Secondly, some uncorrelated SVMs were constructed based on ECOC matrix to improve whole performance of fault tolerant of classification model. Finally, the new vector got through KPCA was used as training and testing sample of ECOC-SVM to recognize different fault state of gear. The result shows this method can extract better sample vector for classification, and has better effect of fault diagnosis.

Key words

kernel principal component analysis / fault diagnosis / error-correcting output codes-support vector machine / gear

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an QIU Mian-hao WANG Zi-ying AN Gang LIU Dong-li . FAULT DIGNOSIS OF GEAR BASED ON KPCA and ECOC-SVM[J]. Journal of Vibration and Shock, 2009, 28(5): 1-5
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