Journal
MEASUREMENT
Volume 143, Issue -, Pages 246-257Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2019.05.010
Keywords
Conveyor belt; Longitudinal tear; Multispectral visual detection; Image fusion
Funding
- National Natural Science Foundation of China-Shanxi coal-based low-carbon joint fund [U1810121]
- Natural Science Foundation of China-Shanxi [201801D121180]
Ask authors/readers for more resources
As an important part of modern coal mine production, conveyor belts are widely used in the coal collection and transportation. In order to ensure the safe operation of the coal mine conveyor belt and solve the drawbacks of the existing conveyor belt longitudinal tear detection technology, a multispectral visual detection method for conveyor belt longitudinal tear is proposed in this paper. The experimental results show that the multispectral visual detection method not only can identify the conveyor belt longitudinal tear, but also accurately classifies and identify other states of the conveyor belt. The accuracy of multispectral visual detection method is over 90.06%, and the precision of longitudinal tearing recognition is over 92.04%. The proposed method is verified to meet the requirements of reliability and real-time in the industrial field. (C) 2019 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available