Research on conditional characteristics vision real-time detection system for conveyor belt longitudinal tear
Tiezhu Qiao (Taiyuan University of Technology)
Xinyu Li (Taiyuan University of Technology)
Y Pang (TU Delft - Transport Engineering and Logistics)
Yuxiang Lü (Taiyuan University of Technology)
Feng Wang (Taiyuan University of Technology)
Baoquan Jin (Taiyuan University of Technology)
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Abstract
Conveyor belt longitudinal tear is one of the most serious problems in coal mining. Existing systems cannot realise lossless and real-time detection for longitudinal tear of conveyor belt. Currently, visual detecting systems are proposed by many researchers and are becoming the future trend. A visual recognition system based on using laser and area light sources is designed in this study, which can recognise and count abrasions, incomplete-tears, and complete-tears. The advantage of the system is to prevent longitudinal tear based on multi-feature information. In the process of detecting conditional characteristics, laser and area light sources are responsible for enhancing contrast between conditional features and conveyor belt surface, meanwhile false corner filtration and single-point feature identification method are designed for improving recognition accuracy of the system. Compared with several current systems, the designed system has a better performance on recognising complex tear characteristics of conveyor belt, thus the problem of starting warning only based on single feature can be effectively avoided.