A Novel Information Fusion Method of the Infrared and Visible Light Images Based on Target Region Feature

Applied laser ◽  
2012 ◽  
Vol 32 (5) ◽  
pp. 440-445
Author(s):  
钟平 Zhong Ping ◽  
施云龙 Shi Yunlong ◽  
杨晓冬 Yang Xiaodong ◽  
王洋 Wang Yang ◽  
王士乐 Wang Shile
Keyword(s):  
Visible Light ◽  
Information Fusion ◽  
Fusion Method ◽  
Target Region ◽  
Region Feature

A Novel Information Fusion Method of the Infrared and Visible Light Images Based on Target Region Feature

Applied laser ◽  
2012 ◽  
Vol 32 (5) ◽  
pp. 440-445
Author(s):  
钟平 Zhong Ping ◽  
施云龙 Shi Yunlong ◽  
杨晓冬 Yang Xiaodong ◽  
王洋 Wang Yang ◽  
王士乐 Wang Shile
Keyword(s):  
Visible Light ◽  
Information Fusion ◽  
Fusion Method ◽  
Target Region ◽  
Region Feature

Arc Detection and Recognition in the Pantograph-Catenary System Based on Multi-Information Fusion

2020 ◽  
Vol 2674 (10) ◽  
pp. 229-240
Author(s):  
Shize Huang ◽  
Wei Chen ◽  
Bo Sun ◽  
Ting Tao ◽  
Lingyu Yang
Keyword(s):  
Visible Light ◽  
Information Fusion ◽  
High Speed ◽  
Evidence Theory ◽  
Detection Methods ◽  
Fusion Method ◽  
Fusion Model ◽  
Threshold Method ◽  
High Speed Trains ◽  
Catenary System

The pantograph-catenary system is critical to high-speed railways. Electric arcs in the pantograph-catenary system indicate possible damages to the whole railway system, and detecting them in time has been a critical task. In this paper, a fusion method for the pantograph-catenary arc detection based on multi-type videos is proposed. First, convolutional neural network (CNN) is employed to detect arcs in visible light images, and a threshold method is applied to identify arcs in infrared images. Second, the CNN-based environment perception model is established on visible light images. It obtains the dynamical adjustment of the reliability weights for different scenarios where trains usually work. Finally, the information fusion model based on evidence theory uses those weights and integrates the detection results on visible light images and infrared results. The experimental results demonstrate the fusion method can avoid misjudgments of the two individual detection methods in certain scenarios, and perform better than each of them. This approach can adapt to the complex environments of high-speed trains.

Fault Classification of Hydroelectric Generating Unit Based on Improved Evidence Theory

2014 ◽  
Vol 7 (1) ◽  
pp. 78-83 ◽  
Author(s):  
Jiatang Cheng ◽  
Li Ai ◽  
Zhimei Duan ◽  
Yan Xiong
Keyword(s):  
Fault Diagnosis ◽  
Information Fusion ◽  
Evidence Theory ◽  
Fault Classification ◽  
Fusion Method ◽  
Inconsistent Result ◽  
High Conflict

Aiming at the problem of the conventional vibration fault diagnosis technology with inconsistent result of a hydroelectric generating unit, an information fusion method was proposed based on the improved evidence theory. In this algorithm, the original evidence was amended by the credibility factor, and then the synthesis rule of standard evidence theory was utilized to carry out information fusion. The results show that the proposed method can obtain any definitive conclusion even if there is high conflict evidence in the synthesis evidence process, and may avoid the divergent phenomenon when the consistent evidence is fused, and is suitable for the fault classification of hydroelectric generating unit.

A novel information fusion method based on Dempster-Shafer evidence theory for conflict resolution

2011 ◽  
Vol 15 (3) ◽  
pp. 399-411 ◽  
Author(s):  
Jianping Yang ◽  
Hong-Zhong Huang ◽  
Qiang Miao ◽  
Rui Sun
Keyword(s):  
Conflict Resolution ◽  
Information Fusion ◽  
Evidence Theory ◽  
Fusion Method
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