Application of multi-sensor information fusion in fault diagnosis of rotating machinery

被引：2

作者：

Guan, Ke ^{[1
]}

Mei, Tao ^{[1
]}

Wang, Deji ^{[1
,2
]}

机构：

[1] Chinese Acad Sci, Inst Intelligent Machines, Hefei 230031, Peoples R China

[2] USTC, Dept Automat, Hefei 230029, Peoples R China

来源：

2006 IEEE INTERNATIONAL CONFERENCE ON INFORMATION ACQUISITION, VOLS 1 AND 2, CONFERENCE PROCEEDINGS | 2006年

关键词：

multi-sensor; information fusion; fault diagnosis; rotating machinery;

D O I：

10.1109/ICIA.2006.305750

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The typical faults of rotating machinery include unbalance, misalignment, bearing housing looseness, etc. The experimental rotor-bearing system is built and multi-sensor information fusion based on D-S evidence theory is applied in the fault diagnosis of rotating machinery. The fault type is determined through the fusion results and from the research it can be concluded that this approach is more effective, accurate and reliable than that of single sensor.

引用

页码：425 / 429

页数：5

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