Detection of three-dimensional belt deviation and longitudinal tearing defects based on binocular line laser technology
1
National Energy Group Ningxia Coal Industry Co., Ltd, Yinchuan 750000, China
2
China Coal Technology and Engineering Group Chongqing Research Institute Co., Ltd, Chongqing 400000, China
3
Tiandi (Changzhou) Automation Co., Ltd, Changzhou 213000, China
Submission date: 2024-01-08
Final revision date: 2024-06-17
Acceptance date: 2024-07-04
Online publication date: 2024-08-28
Publication date: 2024-08-28
Corresponding author
Hong Gao
China Coal Technology and Engineering Group Chongqing Research Institute Co., Ltd, Chongqing 400000, China
China Coal Technology and Engineering Group Chongqing Research Institute Co., Ltd, Chongqing 400000, China
Diagnostyka 2024;25(4):2024401
KEYWORDS
TOPICS
ABSTRACT
The detection of belt deviation and longitudinal tearing defects is the key to ensuring the safe and reliable operation of the equipment. A three-dimensional belt deviation and longitudinal tear defect detection system based on binocular line laser technology was proposed to address the low detection efficiency and high delay of conveyor belt deviation and longitudinal tear detection. A line laser was irradiated onto the surface of the belt through an image acquisition device, and the collected images were preprocessed. Image segmentation, feature extraction, and pattern recognition techniques were used to detect belt deviation and longitudinal tearing defects. These results confirmed that the system designed in this study only took an average of 20 to 30 milliseconds to process an image. The average accuracy of secondary detection was 97.37%, which was 7.5% higher than that of primary detection. The average processing time of the first level detection was 19.45ms. The average processing time of the two level detection was 23.73ms, which was 4.28ms longer than the first level detection. The designed 3D belt deviation and longitudinal tearing defect detection system based on binocular laser technology has high real-time and accuracy, which is very important for the safety production of enterprises.
FUNDING
This research received no external funding
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