CHENG Yuanxin HAN Nannan DING Enjie ZHAO Duan WANG Xin, . Study on recognition method of coal and rock interface based on effective medium theory[J]. COAL SCIENCE AND TECHNOLOGY, 2017, (10).
Citation:
CHENG Yuanxin HAN Nannan DING Enjie ZHAO Duan WANG Xin, . Study on recognition method of coal and rock interface based on effective medium theory[J]. COAL SCIENCE AND TECHNOLOGY, 2017, (10).
CHENG Yuanxin HAN Nannan DING Enjie ZHAO Duan WANG Xin, . Study on recognition method of coal and rock interface based on effective medium theory[J]. COAL SCIENCE AND TECHNOLOGY, 2017, (10).
Citation:
CHENG Yuanxin HAN Nannan DING Enjie ZHAO Duan WANG Xin, . Study on recognition method of coal and rock interface based on effective medium theory[J]. COAL SCIENCE AND TECHNOLOGY, 2017, (10).
School of Information and Control Engineering, China University of Mining and Technology State and Local United Engineering Lab of Mine Internet Applied Technology Internet of Things ( Perception Mine) Research Center, China University of Mining and Technology
In order to solve the present problems existed in the coal-rock interface recognition by labor, an automatic recognition technology of the coal-rock interfa ce was studied. According to the differences of the coal and rock dielectric characteristics, the Bruggeman effective medium theory was applied to establish the coal-roc k boundary model based on the coal content detection. Based on the coal-rock mixed medium powder as an example, a test was conducted for the verification. Witha s imulation on the real-time varied coal-rock mixed medium of the coal content, the relative dielectric constants of the coal-rock mixed medium were real timely obtained. The model was applied to the calculation on the coal content of the mixture and a comparison to the threshold value was conducted. Thus the cutting status of the coal shearer was judged. The test results showed that within the test frequency of 0.01 ~ 30 MHz, the coal content of the coal-rock mixed medium all could pass the obtaine d value calculated with the method. Within the frequency of 0.5 ~ 30 MHz, there would be a small relative error between the theoretical coal content and the actual coal content and could be controlled below 2.60% in average. The calculation results of the model all could accurately recognize the coal-rock interface and could provide a new coal-rock recognition method to realize a minerless mining in the underground mine.