Research on Fault Diagnosis Based on Wavelet Packet Multi-class Classification SVM

Xiaogang Xu, Songling Wang, Fei Li, Zhengren Wu, Wei Sun
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引用次数: 2

Abstract

It’s still in search that how to apply SVM in muti-classify. Directed Acyclic Graph is easier to be computed and has better learning effect than other arithmetic. Experimental platform is used to simulate typical faults of circumrotate machines. Based on the frequency domain feature, energy eigenvector of frequency domain is presented using wavelet packet analysis method. DAGSVM is applied in classification, a "grid-search" is applied on C and using cross-validation. The classify effect is more veracious that of BP network.
基于小波包多类分类SVM的故障诊断研究
如何将支持向量机应用于多分类,目前还在研究中。有向无环图比其他算法更容易计算,具有更好的学习效果。利用实验平台模拟旋转机械的典型故障。基于频域特征,利用小波包分析方法给出了频域能量特征向量。采用DAGSVM进行分类,对C进行“网格搜索”,并进行交叉验证。分类效果比BP网络更准确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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