Fault Feature Enhancement Method for Cylinder Head Vibration Signal Based on Multiscale Principal Component Analysis

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Journal of Vibration and Shock ›› 2013, Vol. 32 ›› Issue (6) : 143-148.

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Fault Feature Enhancement Method for Cylinder Head Vibration Signal Based on Multiscale Principal Component Analysis

YIN Gang, ZHANG Ying-tang, LI Zhi-ning,CHENG Li-jun,YU Ji-quan

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Abstract

For the engine cylinder head vibration signal contains the relatively weak fault information, an feature enhancement method based on multiscale principal component analysis is proposed. First, vibration signal is decomposed by wavelet package and principal component analysis is used for all sub-bands coordinate transformation. Then, a signal is reconstructed in the new coordinate system. We use wavelet package to decompose the new signal and the energy of each sub-band is the feature vector of engine’s fault. Simulated signal testify the effectiveness of the proposed method. Experimnet used the proposed algorithm combined with support vector machine for eleven kinds fault of engine show that the fault classification accuracy could reach 98.76%.

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wavelet package / feature enhancement / multiscale principal component analysis / fault diagnosis / support vector machine

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YIN Gang;ZHANG Ying-tang;LI Zhi-ning;CHENG Li-jun;YU Ji-quan. Fault Feature Enhancement Method for Cylinder Head Vibration Signal Based on Multiscale Principal Component Analysis[J]. Journal of Vibration and Shock, 2013, 32(6): 143-148