| 基于数据挖掘的轴承故障特征模式提取 |
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| 引用本文： | 余志红,王朝晖,陈志刚.基于数据挖掘的轴承故障特征模式提取[J].轴承,2006(7):30-33. |
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| 作者姓名： | 余志红 王朝晖 陈志刚 |
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| 作者单位： | 中国石油大学,机电学院,北京,102249 |
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| 摘 要： | 离心压缩机轴承是主机中故障率最高的部件,针对其故障模式复杂难以辨识的特点,选取与其运行状态密切相关的多个振动参数作为原始特征模式,阐述如何从故障信号数据库中,应用模糊聚类方法对轴承运行状态进行评判,挖掘出对压缩机轴承故障诊断的敏感特征参数。通过现场采集到的大量数据验证,准确率达到95%。
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| 关 键 词： | 滑动轴承 故障 特征 参数 数据挖掘 |
| 文章编号： | 1000-3762（2006）07-0030-04 |
| 收稿时间： | 2006-02-23 |
| 修稿时间： | 2006-03-23 |
Bearing Fault Character Obtaining Based on Date Mining |
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| YU Zhi-hong,WANG Zhao-hui,CHEN Zhi-gang.Bearing Fault Character Obtaining Based on Date Mining[J].Bearing,2006(7):30-33. |
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| Authors: | YU Zhi-hong WANG Zhao-hui CHEN Zhi-gang |
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| Affiliation: | College of Mechanical and Electronic Engineering in the University of Petroleum, Beijing 102249, China |
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| Abstract: | There is frequent fault occurrence in the bearing of centrifugal gas compressor.According to the character of difficult diagnosis of it,to make several vibration parameters highly related to running conditions original mode,evaluate bearing running conditions by applying fuzzy clustering way and demonstrate how to mine the parameter sensitive to diagnosis of fault from database.It is confirmed that the accuracy reaches 95 percent by data collected from site. |
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| Keywords: | bearing fault character parameter data mining |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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