Intelligent Detection Technology of Coal–Rock Interface With Mining Based on Scissor and Fork Support
Coal mine intelligence is the development direction to realize the safe and efficient mining of coal mine, and the identification of coal-rock interface is one of the important problems restricting the intelligent mining of coal mine. Coal-rock radar can be used to detect coal-rock interface. Due to the fluctuation of coal seam in fully mechanized mining face, it is an important technology for intelligent detection and identification of coal-rock interface to realize adaptive height adjustment with mining to increase the accuracy of data acquisition. In this study, an intelligent detection technology of coal-rock interface with mining based on scissors and fork support is proposed. The height of coal-rock radar from the roof is automatically adjusted by intelligent support to realize intelligent detection of coal-rock radar with mining. The intelligent support system of scissors and forks is developed to adjust the overhanging detection distance of coal-rock radar in real time. An air - coal interface identification method based on peak detection is proposed, and the identification error is 6.7%. In order to verify the system performance, the error analysis experiment of radar data wireless transmission is designed, and the maximum error is 5.7%. The coal-rock model detection experiment is designed, and the automatic height adjustment error of the intelligent support optimized by the recognition algorithm is 5.9%. And the air - coal interface and coal - rock interface can be effectively detected in the actual mine face detection, and the relative error of detecting coal seam thickness is 4.7%. The results aim to realize the intelligent detection of coal-rock interface with mining, improve the accuracy of data collection and provide reliable technical support for intelligent, safe and efficient mining of coal mines.
Authors
- Haoran Zhang (ORCID: https://orcid.org/0000-0002-8751-5407)
- Xianlei Xu (ORCID: https://orcid.org/0000-0003-3934-2924)
- Jinglin Li (ORCID: https://orcid.org/0009-0000-4944-2334)
- Zheng Ma (ORCID: https://orcid.org/0000-0002-0251-1483)
Institutions
- Ministry of Natural Resources (CN)
- China University of Mining and Technology (CN)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2025-04-08
- DOI
- https://doi.org/10.1109/jsen.2025.3550925
- Primary Topic
- Geoscience and Mining Technology
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China