School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, 221116, China.
School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongong, New South Wales, 2522, Australia.
Sci Rep. 2018 Jan 9;8(1):190. doi: 10.1038/s41598-017-18625-y.
Recognition of coal and gangue (roof rock) is a key technology to realize fully mechanized top coal caving automated mining. This paper proposes to detect the instantaneous refuse content of drawn coal and gangue mixture during top coal caving by using natural gamma-ray technology. The generating environment of coal and rock seams, the distribution characteristics of natural gamma ray from coal and roof-rock and the principle of coal-gangue recognition using natural gamma-ray method were analyzed. The natural gamma ray radiation characteristics of coal and roof-rock seams from seven different typical coal mine areas who has thick coal seams in China have been researched, and a connection between radiation intensity and refuse content was set up. The experiments on the mixed condition of roof-rock drawn from caving opening in the caving process of fully-mechanized top coal caving working face was taken and the radiative signals was real-time detected by using the self-developed coal-gangue recognition experimental system. The experiments results demonstrate the feasibility of using natural gamma-ray technology to perform real-time detection of refuse content of drawn coal and gangue mixture and the availability of self-developed coal-gangue recognition detector.
识别煤和矸石（顶板岩石）是实现综采放顶煤自动化开采的关键技术。本文提出利用自然伽马射线技术检测综采放顶煤过程中抽出的煤矸混合物的瞬时含矸率。分析了煤岩地层的生成环境、煤和顶板岩石中自然伽马射线的分布特征以及利用自然伽马射线法识别煤矸石的原理。研究了中国七个具有厚煤层的典型矿区的煤岩地层的自然伽马射线辐射特征，并建立了辐射强度与含矸率之间的关系。在综采放顶煤工作面放顶煤过程中，对采空区抽出的顶板岩石进行了混合条件下的实验，并利用自主研发的煤矸石识别实验系统实时检测了辐射信号。实验结果表明，利用自然伽马射线技术实时检测抽出的煤矸混合物的含矸率是可行的，自主研发的煤矸识别探测器是有效的。
