DocumentCode
3494958
Title
Fault Diagnosis of Complex Systems Based on Multi-sensor and Multi-domain Knowledge Information Fusion
Author
Yong-Min Yang ; Ge, Zhe-xue ; Xu, Yong-min Yang
Author_Institution
Nat. Univ. of Defense Technol., Changsha
fYear
2008
fDate
6-8 April 2008
Firstpage
1065
Lastpage
1069
Abstract
This paper presents a framework for fault diagnosis of complex systems by proposing a new multi-sensor and multi-domain knowledge information fusion (MSMDK) model. In the model, the multi-domain case, rule and model knowledge are adopted for multi-sensor information reasoning, and then the advanced Dempster-Shafter (D-S) evidence theory is proposed for overall fusion, which has the advantage of avoiding the evidence conflict by defining the evidence preference weight (EPW). In addition, the basic belief assignment (BBA) methods of the three different domain knowledge are brought forward for entire fusion process. The experiments of fault diagnosis of helicopter autopilot are carried out and demonstrate that the proposed method can serve as an effective method for the fault diagnosis of complex dynamic systems.
Keywords
belief maintenance; fault diagnosis; inference mechanisms; large-scale systems; sensor fusion; uncertainty handling; Dempster-Shafter evidence theory; basic belief assignment method; complex dynamic system; evidence preference weight; fault diagnosis; helicopter autopilot; multidomain knowledge information fusion model; multisensor fusion model; multisensor information reasoning; Aerospace control; Automation; Fault detection; Fault diagnosis; Helicopters; Information entropy; Mathematical model; Mathematics; Mechatronics; Uncertainty; Complex systems; Dempster-Shafter Evidence Theory; Evidence Preference Weight; Fault Detection and Diagnosis; Information Fusion;
fLanguage
English
Publisher
ieee
Conference_Titel
Networking, Sensing and Control, 2008. ICNSC 2008. IEEE International Conference on
Conference_Location
Sanya
Print_ISBN
978-1-4244-1685-1
Electronic_ISBN
978-1-4244-1686-8
Type
conf
DOI
10.1109/ICNSC.2008.4525374
Filename
4525374
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