Design and Implementation of W-shaped Steel Band Hole Image Recognition System Based on OpenCV-Python

The mine Roofbolter is widely used in drilling and supporting of underground roof and side wall, which greatly alleviates the imbalance of driving anchor. However, with the progress of sensor technology, electrical and electronic technology, electro-hydraulic proportional control technology and the...

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Veröffentlicht in:Journal of physics. Conference series Jg. 2202; H. 1; S. 12056 - 12062
Hauptverfasser: Chen, Xu, yuepin, Bai, Qiang, Guo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Bristol IOP Publishing 01.06.2022
Schlagworte:
Anchor bolts
Artificial intelligence
Belts
Continuous improvement
Control equipment
Drilling
Efficiency
Eye (anatomy)
Machine vision
Mental health
Metal strips
Mining machinery
Object recognition
OpenCV
Personnel
Physics
Programming languages
Proportional control
python
Roads & highways
Safety
Strip steel
Underground mines
User requirements
W-shaped steel with hole
Working conditions
ISSN:1742-6588, 1742-6596
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Abstract The mine Roofbolter is widely used in drilling and supporting of underground roof and side wall, which greatly alleviates the imbalance of driving anchor. However, with the progress of sensor technology, electrical and electronic technology, electro-hydraulic proportional control technology and the continuous improvement of users’ requirements for the safety and efficiency of bolt support, domestic and foreign mining equipment manufacturers have carried out the development of automatic bolt and anchor cable support equipment, especially to improve the performance requirements of control system and develop intelligent visualization technology. At present, the hole location in the process of drilling still needs to be identified and located by human eyes, which is inefficient and the working environment is a great threat to the physical and mental health of personnel, so it is urgent to introduce computer technology and artificial intelligence technology. In this paper, with the help of image recognition technology, machine vision recognition replaces human eye recognition of hole location, and puts forward an image recognition technology of W-shaped steel belt hole recognition system based on OpenCV to assist the scheme, so as to ensure the safety and efficiency of roadway support. This system uses pychar, opencv and python language to realize the recognition and positioning of W-shaped steel strip hole. The scheme has the advantages of small amount of calculation, high accuracy and fast recognition speed. This research conclusion provides a reference for the further spatial positioning analysis of W-shaped steel belt hole, and improves the efficiency of underground support operation and personnel safety.
AbstractList The mine Roofbolter is widely used in drilling and supporting of underground roof and side wall, which greatly alleviates the imbalance of driving anchor. However, with the progress of sensor technology, electrical and electronic technology, electro-hydraulic proportional control technology and the continuous improvement of users’ requirements for the safety and efficiency of bolt support, domestic and foreign mining equipment manufacturers have carried out the development of automatic bolt and anchor cable support equipment, especially to improve the performance requirements of control system and develop intelligent visualization technology. At present, the hole location in the process of drilling still needs to be identified and located by human eyes, which is inefficient and the working environment is a great threat to the physical and mental health of personnel, so it is urgent to introduce computer technology and artificial intelligence technology. In this paper, with the help of image recognition technology, machine vision recognition replaces human eye recognition of hole location, and puts forward an image recognition technology of W-shaped steel belt hole recognition system based on OpenCV to assist the scheme, so as to ensure the safety and efficiency of roadway support. This system uses pychar, opencv and python language to realize the recognition and positioning of W-shaped steel strip hole. The scheme has the advantages of small amount of calculation, high accuracy and fast recognition speed. This research conclusion provides a reference for the further spatial positioning analysis of W-shaped steel belt hole, and improves the efficiency of underground support operation and personnel safety.
Author yuepin, Bai
Chen, Xu
Qiang, Guo
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Cites_doi 10.1016/S1874-1029(13)60002-6
10.1016/j.ijleo.2016.12.064
ContentType Journal Article
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Snippet The mine Roofbolter is widely used in drilling and supporting of underground roof and side wall, which greatly alleviates the imbalance of driving anchor....
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SubjectTerms Anchor bolts
Artificial intelligence
Belts
Continuous improvement
Control equipment
Drilling
Efficiency
Eye (anatomy)
Machine vision
Mental health
Metal strips
Mining machinery
Object recognition
OpenCV
Personnel
Physics
Programming languages
Proportional control
python
Roads & highways
Safety
Strip steel
Underground mines
User requirements
W-shaped steel with hole
Working conditions
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Title Design and Implementation of W-shaped Steel Band Hole Image Recognition System Based on OpenCV-Python
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