基于EMD与GA-PLS的特征选择算法及应用

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振动与冲击 ›› 2012, Vol. 31 ›› Issue (4) : 134-138.

论文

基于EMD与GA-PLS的特征选择算法及应用

李胜，张培林

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Feature Selection Algorithm Based on EMD and GA-PLS and its Application

Li Sheng ; Zhang Pei-lin

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文章历史 +

摘要

针对振动信号非平稳性和特征优化选择的问题，提出一种基于EMD和GA-PLS的特征选择算法。在该算法中，首先，采用EMD方法将振动信号分解成多个固有模态函数(Intrinsic Mode Function, IMF)，对IMF分量建立自回归（AR）模型，以AR模型系数和残差作为初始特征向量，然后，遗传算法与偏最小二乘法相结合(GA-PLS)的算法对初始特征向量进行筛选得到新的特征向量，最后，以新的特征向量为输入，建立分类器，用来识别手动换向阀的工作状态和判断故障类型。实验结果表明，采用该特征选择算法能准确地选择出特征，并能应用于手动换向阀的故障诊断

Abstract

In order to solve problems of the nonstationarity of vibration signal and the optimization of feature selection, feature selection algorithm based on EMD and GA-PLS is proposed. In this algorithm, firstly, EMD method is used to decompose the vibration signals into a number of intrinsic mode function components, and the auto-regressive mode (AR) model of each IMF component is established. The main auto-regressive parameters and the loss function are regarded as original feature vectors. Then, genetic algorithm-partial least squares (GA-PLS) algorithm is used to selecting new feature vectors, which are high correlation with fault information, from original feature vectors. Finally, when these new feature vectors are used as inputs, classifiers are established for identifying the conditions and fault patterns of manual operated directional valve. Experimental results show that all the feature vectors are selected correctly, and the proposed algorithm can be used in the fault diagnosis.

导出引用

李胜;张培林. 基于EMD与GA-PLS的特征选择算法及应用[J]. 振动与冲击, 2012, 31(4): 134-138

Li Sheng;Zhang Pei-lin. Feature Selection Algorithm Based on EMD and GA-PLS and its Application[J]. Journal of Vibration and Shock, 2012, 31(4): 134-138