Nondestructive Detection of Coal–Rock Interface Under Mining Environment Using Ground Penetrating Radar Image

Author:

Wang Xin12ORCID,Zhao Duan3,Wang Yikun4

Affiliation:

1. Jiangsu Vocational Institute of Architectural Technology, Xuzhou 221116, P. R. China

2. JiangSu Collaborative Innovation Center for Building Energy Saving and Construction Technology, Xuzhou 221116, P. R. China

3. IoT Perception Mine Research Center, China University of Mining and Technology, Xuzhou 221116, P. R. China

4. Jiangsu Province Engineering Research Center of Intelligent, Visual Recognition and Data Mining, Xuzhou 221000, P. R. China

Abstract

Shearer drum automatic height adjustment strategy under mining environment is based on the recognition of coal–rock interface and the ground penetrating radar (GPR) was used for coal–rock interface recognition in the study. First, a model was built to study the radar echo in complex coal seam and some simulations were made to study the influence of radar parameters. Second, the experiment study was implemented in the coal mine working face in Tengzhou city, Shandong province, China. In this study, it was applied for radar image creation, including the start time correction, filtering technique, Hilbert transform, A-scan, and B-scan. The support vector machine (SVM) method was used for searching the coal–rock interface echo in lots of waveforms. The coal–rock interface could be found clearly and intuitively in the radar images by the above method in unknown complex coal seam structure and the error is less than 2% in A-scan mode. The results show that the method can stably and reliably find the coal–rock interface even in dynamic scenarios with the accuracy of 95%, where the root mean square error (RMSE) is and the 0.1. The radar antenna can be fixed to the shearer rocker arm in real time during mining to detect the thickness of coal seam in looking-ahead, top/bottom and shear moving direction.

Funder

National Natural Science Foundation of China

Qinglan Project of Jiangsu Province of China

Jiangsu Construction System Science and Technology Project

Ph.D Fund of Jiangsu Collaborative Innovation Center for Building Energy Saving and Construct Technology

Publisher

World Scientific Pub Co Pte Ltd

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

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