Research on Multi-sensor Information Fusion Algorithm with Sensor Fault Diagnosis

Author(s):  
Chun Xiao ◽  
Zhengdong Fang
IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 23717-23725
Author(s):  
Jiaxing Wang ◽  
Dazhi Wang ◽  
Sihan Wang ◽  
Wenhui Li ◽  
Keling Song

2016 ◽  
Vol 12 (05) ◽  
pp. 53 ◽  
Author(s):  
Lin Liandong

This study aims to solve the problem of multi-sensor information fusion, which is a key issue in the multi-sensor system development. The main innovation of this study is to propose a novel multi-sensor information fusion algorithm based on back propagation neural network and Bayesian inference. In the proposed algorithm, a triple is defined to represent a probability space; thereafter, the Bayesian inference is used to estimate the posterior expectation. Finally, we construct a simulation environment to test the performance of the proposed algorithm. Experimental results demonstrate that the proposed algorithm can significantly enhance the accuracy of temperature detection after fusing the data obtained from different sensors.


2017 ◽  
Vol 11 ◽  
pp. 05003
Author(s):  
Ling-Wen Meng ◽  
Ji-Pu Gao ◽  
Ming-Yong Xin ◽  
Jin-Mei Xiong ◽  
Guo Rui

2010 ◽  
Vol 40-41 ◽  
pp. 637-642
Author(s):  
Xiao Hua Liu ◽  
Song Qing Li

From the intelligent fault diagnosis system requirements, this article analyzes the relationship between the fault diagnosis and the multi-information fusion basing on the summing up the multi-sensor information fusion technology, and studies the hierarchical structure of multi-sensor information fusion system and the content of integration, and establishes an intelligent fault diagnosis model with the multi-information fusion, which provides strong support for large-scale equipments, system monitoring and fault diagnosis in production process.


2014 ◽  
Vol 22 (6) ◽  
pp. 1504-1515 ◽  
Author(s):  
Gang Cheng ◽  
Xi-hui Chen ◽  
Xian-lei Shan ◽  
Hou-guang Liu ◽  
Chang-fei Zhou

Sign in / Sign up

Export Citation Format

Share Document