A method for determining longitudinal tear of conveyor belt based on feature fusion

被引：1
|
作者：
Zeng, Fei [1 ]
Zhang, Sheng [1 ]
机构：
[1] Wuhan Univ Sci & Technol, Minist Educ, Key Lab Met Equipment & Control Technol, Wuhan, Peoples R China
来源：
2019 6TH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE 2019) | 2019年
基金：
中国国家自然科学基金;
关键词：
longitudinal tear; conveyor belt; computer vision; image detection; feature fusion; VISION;
D O I：
10.1109/ICISCE48695.2019.00023
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Conveyor belt is often damaged by longitudinal rip while working in transport, which can lead to the scrapping of expensive machines, and sometimes causing fire and casualties. This paper presents a method for determining longitudinal tear of conveyor belt based on feature fusion. We analyze the main reasons of longitudinal rip and the image characteristics when the belt is ripped apart correspond with real operational conditions. Then the geometric characteristic and template matching feature based on gray image are selected to describe the characteristics of longitudinal tearing crack of conveyor belt. Finally, longitudinal tear of conveyor belt is determined based on DS evidence theory. The detection system based on computer vision is designed, which includes information collection apparatus, the image detecting apparatus, PC operating system and data transmission interface and the software is programmed by using MATLAB graphical user interface (GUI) technique. The presented method is useful for avoiding the risks of belt longitudinal rip under real operational conditions and for improving the production of transport's efficiency and effectiveness.
引用
收藏
页码：65 / 69
页数：5
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