The application of a correlation dimension in large rotating machinery fault diagnosis

被引：17
|
作者：
Wang, W [1 ]
Chen, J
Wu, Z
机构：
[1] Shanghai Jiao Tong Univ, State Key Lab Vibrat Shock & Noise, Shanghai 200030, Peoples R China
[2] Zhejiang Univ, Dept Mech Engn, Hangzhou 310027, Peoples R China
来源：
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE | 2000年 / 214卷 / 07期
关键词：
chaos; correlation dimension; large rotating machinery; fault diagnosis;
D O I：
10.1243/0954406001523155
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
This paper reports on the application of the correlation dimension in large rotating machinery fault diagnosis. The Grassberger-Procaccia algorithm and its modified version are introduced. Some important influencing factors relating directly to the computational precision of the correlation dimension are discussed. Industrial vibration signals measured from large rotating machinery with different faults are researched using the above-mentioned methods. The results show that the correlation dimension can provide some intrinsic information on an underlying dynamic system and can be used to classify different faults intelligently.
引用
收藏
页码：921 / 930
页数：10
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