Open AccessResearch on visible light and infrared vision real‐time detection system for conveyor belt longitudinal tear
Author(s) -
Qiao Tiezhu,
Liu Weili,
Pang Yusong,
Yan Gaowei
Publication year - 2016
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2015.0297
Subject(s) - hough transform , artificial intelligence , computer vision , conveyor belt , infrared , computer science , histogram , charge coupled device , optics , engineering , image (mathematics) , physics , mechanical engineering
Conveyor belt longitudinal tear is one of the most serious problems in coal mining. It is very important to detect it in real‐time before the length of the tear is too long. In this study, a method of longitudinal tear detection based on visible light charge coupled device (CCD) and infrared CCD is proposed. A visible light and infrared vision real‐time detection system for conveyor belt longitudinal tear is designed based on this method. In this method, the infrared CCD uses adaptive histogram equalisation coordinating with Hough transform line detection. The visible light CCD, coordinating with a laser line source, uses the Hough transform algorithm and the features from accelerated segment test algorithm. These two kinds of CCDs work together to make detection results reliable. Experimental results show that the proposed method is effective and adaptive, and meets the requirements for reliable, real‐time and online longitudinal tear detection. Compared to several current methods, the proposed method has a better performance on efficiency of detection.