Fault diagnosis method for rolling bearing based on neighborhood component analysis

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Journal of Vibration and Shock ›› 2015, Vol. 34 ›› Issue (2) : 138-142.

ZHOU Hai-tao1,2，CHEN Jin1,2，DONG Guang-ming1,2

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Abstract

This paper proposed a novel fault diagnosis method for rolling bearing based on neighborhood component analysis(NCA). NCA is used to reduce the dimensions of input time and frequency domain features. Then the classification is performed. Fisher evaluation function is applied to select the proper object dimension. In order to show the advantages of the proposed method, the classification results based on both PCA and NCA are compared. The experiment shows that as a supervised dimension reduction method, NCA performs better than PCA.

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neighborhood component analysis / dimension reduction / rolling bearing / fault diagnosis

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ZHOU Hai-tao;CHEN Jin;DONG Guang-ming;. Fault diagnosis method for rolling bearing based on neighborhood component analysis[J]. Journal of Vibration and Shock, 2015, 34(2): 138-142