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	基于形态分析和支持向量机的轴承故障分类研究
	郝如江 ; 卢文秀 ; 褚福磊 ; Hao Rujiang ; Lu Wenxiu ; Chu Fulei
	2010-07-15 ; 2010-07-15
会议名称	2008年全国振动工程及应用学术会议暨第十一届全国设备故障诊断学术会议 ; CNKI
关键词	数学形态学 形态谱熵 故障分类 Mathematical morphology Pattern spectrum defect classification TH133.3
其他题名	DEFECT CLASSIFICATION OF BEARING WITH MATHEMATICAL MORPHOLOGY AND SUPPORT VECTOR MACHINE
中文摘要	形态分析是信号处理的一种非线性分析方法,滚动轴承故障信号是一种非线性非平稳信号。为了区分不同类型故障,采用多尺度形态开运算得到故障信号的形态谱,并由形态谱曲线计算形态谱熵,将形态谱熵和形态谱曲线的重心坐标作为支持向量机的输入参数进行故障模式分类。通过对实验数据的分析表明,形态学分析与支持向量机相结合的方法为轴承故障信号的分析、识别和分类提供了新的思路。; The mathematical morphology analysis is a nonlinear method for signal processing.The defective bearing signals are nonlinear and nonstationary.To identify different types of defects,The pattern spectrum curve was achieved by multiscale morphological opening operation,then the pattern spectrum entropy was figured out.The pattern spectrum entropy and the barycenter scale location of the spectrum curve were used to input data to the support vector machine to identify different types of signals.The experimental data measured from the bearing test rig were analyzed by this method and it was shown that the combination of mathematical morphology and support vector machine was ideal for defect characteristic extraction and classification,it was suitable for the on-line automated fault diagnosis and identification of the rolling element bearings.This application is promising and worth well exploiting.
会议录出版者	上海《振动与冲击》编辑部
语种	中文 ; 中文
内容类型	会议论文
源URL	[http://hdl.handle.net/123456789/67895]
专题	清华大学
推荐引用方式 GB/T 7714	郝如江,卢文秀,褚福磊,等. 基于形态分析和支持向量机的轴承故障分类研究[C]. 见:2008年全国振动工程及应用学术会议暨第十一届全国设备故障诊断学术会议, CNKI.

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