DocumentCode
3461565
Title
Application of Multi-sensor Information Fusion in Fault Diagnosis of Rotating Machinery
Author
Guan, Ke ; Mei, Tao ; Wang, Deji
Author_Institution
Inst. of Intelligent Machines, Chinese Acad. of Sci., Hefei
fYear
2006
fDate
20-23 Aug. 2006
Firstpage
425
Lastpage
429
Abstract
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
Keywords
condition monitoring; electric machine analysis computing; electric motors; fault diagnosis; inference mechanisms; sensor fusion; D-S evidence theory; fault diagnosis; multisensor information fusion; rotating machinery; rotor-bearing system; Condition monitoring; Decision making; Fault diagnosis; Information analysis; Intelligent robots; Machinery; Optimal control; Reliability theory; Sensor fusion; Sensor phenomena and characterization; fault diagnosis; information fusion; multi-sensor; rotating machinery;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Acquisition, 2006 IEEE International Conference on
Conference_Location
Weihai
Print_ISBN
1-4244-0528-9
Electronic_ISBN
1-4244-0529-7
Type
conf
DOI
10.1109/ICIA.2006.305750
Filename
4097972
Link To Document