An Improved Multisensor Data Fusion Method and Its Application in Fault Diagnosis

被引:31
|
作者
Wang, Zhongyan [1 ]
Xiao, Fuyuan [2 ]
机构
[1] Southwest Univ, Hanhong Coll, Chongqing 400715, Peoples R China
[2] Southwest Univ, Sch Comp & Informat Sci, Chongqing 400715, Peoples R China
来源
IEEE ACCESS | 2019年 / 7卷
关键词
Conflict evidence; Dempster's combination rule; belief entropy; Dempster-Shafer evidence theory; information theory; COMBINING BELIEF FUNCTIONS; DEMPSTER-SHAFER THEORY; DECISION-MAKING; UNCERTAINTY; EVIDENCES; SYSTEM;
D O I
10.1109/ACCESS.2018.2889358
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A multisensor system is used to improve the ability of monitoring and tracking accuracy of an engineering system since only one sensor is not enough, whereupon, faulty diagnosis, as a typical information fusion problem which is under multisensor environment, has attracted much attention in recent years. The evidence theory has been widely used to solve this problem. However, when there is a high level of conflict between the information gathered from different sensors, the counter-intuitive result could be obtained when using the classical Dempster's combination rule. To address this problem, an improved multisensor data fusion method is proposed to fuse the data collected from multisensors. Some numerical examples are illustrated to show that the proposed method is effective and feasible. Moreover, the fusion results using different methods are analyzed, which indicate the superiority and stronger application of the proposed method in the field of fault diagnosis.
引用
收藏
页码:3928 / 3937
页数:10
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