Title :
Information correlation entropy based D-S evidence theory used in fault diagnosis
Author :
Zhu, Hanqing ; Ma, Zhenshu ; Sun, Huagang ; Wang, Haoyi
Author_Institution :
Ordnance Tech. Res. Inst., Ordnance Eng. Coll., Shijiazhuang, China
Abstract :
Dempster-Shafer (D-S) evidence theory based multi-sensor information fusion (MSIF) plays an important role in fault diagnosis. Aiming to solve the problems via classical evidence theory, an improved D-S evidence theory through the introduction of information correlation entropy theory is reported in this paper. Then, the proposed method is employed to gearbox fault diagnosis. Experiment analysis results indicate that the new method is effective for MSIF.
Keywords :
case-based reasoning; correlation methods; entropy; fault diagnosis; gears; mechanical engineering computing; sensor fusion; uncertainty handling; D-S evidence theory; Dempster-Shafer evidence theory; MSIF; gearbox fault diagnosis; information correlation entropy theory; multisensor information fusion; Biological neural networks; Correlation; Entropy; Fault diagnosis; Indexes; Information entropy; Probability distribution; D-S evidence; MSIF; fault diagnosis; gearbox; information entropy;
Conference_Titel :
Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2012 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4673-0786-4
DOI :
10.1109/ICQR2MSE.2012.6246248
