Research on data fusion of multi-sensors based on fuzzy preference relations

被引:0
|
作者
Huijuan Hao
Maoli Wang
Yongwei Tang
Qingdang Li
机构
[1] Shandong Provincial Key Laboratory of Computer Networks,Qilu University of Technology (Shandong Academy of Sciences), Shandong Computer Science Center (National Supercomputer Center in Jinan)
[2] University of Kassel,Technological Electronics Department, Faculty of Electrical Engineering and Computer Science, Institute of Nanostructure Technologies and Analytics
[3] Qingdao University of Science and Technology,Chinesisch
来源
Neural Computing and Applications | 2019年 / 31卷
关键词
Fuzzy preference relations; Weight; Data fusion; Multi-sensors signals; Adaptive weighted estimate algorithm;
D O I
暂无
中图分类号
学科分类号
摘要
For the data fusion of multi-sensors, the determination of weight directly affects the accuracy and performance of the fusion algorithm. In order to improve the accuracy of fusion algorithm, an adaptive weighted algorithm based on fuzzy preference relations is proposed. The degree of preference between signals is represented by introducing the improved logsig function, and then, the weight is calculated by fuzzy preference relations. Simulation results show that the proposed algorithm is significantly better than the mean value method, and the accuracy is basically equivalent to the method based on correlation function. The analysis of the actual vibration signals in axis system verifies the validity of the algorithm in the practical application. The algorithm in this paper has good dynamic performance and is easy to be implemented. It can be applied to the actual multi-vibration signal estimation to provide more accurate parameters for the next step of fault diagnosis.
引用
收藏
页码:337 / 346
页数:9
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