Research and application of data mining in fault diagnosis for big machines

被引：2

作者：

Chen, Zhigang ^{[1
]}

Zhang, Laibin ^{[1
]}

Wang, Zhaohui ^{[1
]}

Liang, Wei ^{[1
]}

Li, Qinggang ^{[2
]}

机构：

[1] China Univ Petr, Coll Mech & Elect Engn, Beijing, Peoples R China

[2] Greatwall Drilling Co LTD, Logist Procurement Dept, Beijing, Peoples R China

来源：

2007 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, VOLS I-V, CONFERENCE PROCEEDINGS | 2007年

关键词：

fault diagnosis; fuzzy clustering; data mining; feature obtaining;

D O I：

10.1109/ICMA.2007.4304167

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The fault characteristics of big equipments are complex and difficult to distinguish, this paper presents a new method elaborating on selecting more interrelated vibration parameters as original characteristic vectors, and how to mine features from fault database and then analyze running conditions of rotating parts of big machines by applying fuzzy clustering. The theories of establishing models, specific algorithms and steps have been given in it. Applied example showed that the method vas correct and the result of the fault diagnosis had also been proved to be reliable and accurate.

引用

页码：3729 / +

页数：2

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