Title :
Multi-sensor information fusion method and its applications on fault detection of diesel engine
Author :
Guo, He ; Pan Xingiong ; Chaojie, Zhang ; Tingfeng, Ming ; Jiufeng, Qin
Author_Institution :
Coll. of Naval Archit. & Power, Naval Univ. of Eng., Wuhan, China
Abstract :
We proposed a method of multi-sensor information fusion based on Dempster-Shafer evidential theory for fault detection. At first, the basic probability assignment function (BPAF) is constructed based on probability statistics and fuzzy membership function. Then, the Dempster-Shafer evidential theory is applied to multi-sensor information fusion. Finally, the proposed method is applied to fault detection of a certain diesel engine. The experiment results indicate that the problem of multi-sensor information fusion in diesel engine fault detection is solved by using Dempster-Shafer evidential theory, and the uncertainty of single sensor information is avoided. The proposed methods are effective and the conclusions of fault detection are creditable.
Keywords :
diesel engines; fault diagnosis; fuzzy set theory; mechanical engineering computing; sensor fusion; statistical distributions; uncertainty handling; BPAF; Dempster-Shafer evidential theory; basic probability assignment function; diesel engine fault detection; fuzzy membership function; multisensor information fusion method; probability statistics; Artificial intelligence; Dempster-Shafer evidential theory; fault detection; fuzzy membership function; multi-sensor information fusion;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2011 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-1586-0
DOI :
10.1109/ICCSNT.2011.6182489