核函数在液压泵故障诊断中的应用研究

Application of Kernel Function in Fault Diagnosis of Hydraulic Pump

支持向量机是基于统计学习理论上发展起来的一种新型机器学习方法。在用支持向量机对液压泵故障诊断中,采用了不同的核函数及核函数参数进行分类,取得了较好的效果,讨论了选取不同核函数对分类性能的影响。

Support Vector Machine（SVM）is a new kind of machine learning methods developed from statistics learning theory. The different kernel functions and kernel parameters are applied in fault diagnosis of hydraulic pump. Experiment results are showed that the classifying performance of fault classifiers has great relations with the kernel function in SVM.