Enhanced diagnostic certainty using information entropy theory

被引：31
作者：
Qu, LS
Li, LM [1 ]
Lee, J
机构：
[1] Xian Jiaotong Univ, Res Inst Diagnost & Cybernet, Xian 710049, Peoples R China
[2] Univ Wisconsin, Ctr Intelligent Maintenance Ctr, Milwaukee, WI 53211 USA
来源：
ADVANCED ENGINEERING INFORMATICS | 2003年 / 17卷 / 3-4期
关键词：
information entropy; machinery diagnosis; stability; diagnostic feature; maintenance;
D O I：
10.1016/j.aei.2004.08.002
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
As is well known, the information entropy is a basic notion in cybernetics. This paper mainly summarizes some applications of information entropy in our machinery diagnostic research practice. First, we use it as a quantitative measure of equipment diagnostibility, maintainability. Second, we introduce a criterion of complexity in frequency domain to evaluate the complexity of diagnostic signal in rotating machinery. Then a new criterion called the index of orbit complexity is proposed to evaluate the dynamic quality of rotor systems during their operation. Finally the entropy distance is applied as an effective diagnostic feature to discriminate the potential faults inside the operating machinery. Practical case studies and experiments show its effectiveness. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码：141 / 150
页数：10
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