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

fYear

2012

fDate

15-18 June 2012

Firstpage

336

Lastpage

338

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2012 International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4673-0786-4

Type

conf

DOI

10.1109/ICQR2MSE.2012.6246248

Filename

6246248