Multi-sensor Information Fusion Method and Its Applications on Fault Detection of Diesel Engine

摘要：

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.

关键词： Dempster-Shafer evidential theory fault detection fuzzy membership function multi-sensor information fusion

作者: He Guo Pan Xinglong Zhang Chaojie Ming Tingfeng Qin Jiufeng

作者单位: College of Naval Architecture and Power, Naval University of Engineering, 717 Jiefang Street, Wuhan, College of Naval Architecture and Power, Naval zniversity of Engineering, 717 Jiefang Street, Wuhan,

会议类型: 国际会议

会议名称: 2011 International Conference on Computer Science and Network Technology(2011计算机科学与网络技术国际会议 ICCSNT 2011)

会议地点: 哈尔滨

会议语种:英文

页码: 2551-2555

在线出版日期: 2011-12-24（万方平台首次上网日期，不代表论文的发表时间）