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
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;
Conference_Titel :
Information Acquisition, 2006 IEEE International Conference on
Conference_Location :
Weihai
Print_ISBN :
1-4244-0528-9
Electronic_ISBN :
1-4244-0529-7
DOI :
10.1109/ICIA.2006.305750
