基于MSPCA的缸盖振动信号特征增强方法研究

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振动与冲击 ›› 2013, Vol. 32 ›› Issue (6) : 143-148.

论文

基于MSPCA的缸盖振动信号特征增强方法研究

尹刚1，张英堂1，李志宁1，程利军1，于继全2

作者信息 +

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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文章历史 +

摘要

针对发动机缸盖振动信号信噪比低的问题，提出了基于多尺度主元分析的故障特征增强方法。将缸盖振动信号小波包分解后，利用主成分分析对所有子带系数进行坐标变换，信号重构后再进行小波包分解，计算新坐标系下各子带的能量作为发动机故障的特征向量。仿真信号验证了本文所提算法对微弱冲击信号的增强能力，与支持向量机结合用于发动机十一种故障的诊断实例表明，故障分类准确率可达到98.76%。

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%.

导出引用

尹刚;张英堂;李志宁;程利军;于继全. 基于MSPCA的缸盖振动信号特征增强方法研究[J]. 振动与冲击, 2013, 32(6): 143-148

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