TY - JOUR
T1 - Research on conditional characteristics vision real-time detection system for conveyor belt longitudinal tear
AU - Qiao, Tiezhu
AU - Li, Xinyu
AU - Pang, Yusong
AU - Lü, Yuxiang
AU - Wang, Feng
AU - Jin, Baoquan
N1 - Accepted Author Manuscript
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - belts
KW - coal
KW - conveyors
KW - mining equipment
KW - real-time systems
UR - http://resolver.tudelft.nl/uuid:97aa86b5-691d-447e-bfe2-23ae0821263c
UR - http://www.scopus.com/inward/record.url?scp=85031493770&partnerID=8YFLogxK
U2 - 10.1049/iet-smt.2017.0100
DO - 10.1049/iet-smt.2017.0100
M3 - Article
AN - SCOPUS:85031493770
SN - 1751-8822
VL - 11
SP - 955
EP - 960
JO - IET Science, Measurement and Technology
JF - IET Science, Measurement and Technology
IS - 7
ER -