煤
探地雷达
雷达
接口(物质)
支持向量机
煤矿开采
地质学
采矿工程
雷达成像
人工智能
均方误差
计算机科学
遥感
模式识别(心理学)
计算机视觉
工程类
数学
统计
最大气泡压力法
电信
气泡
并行计算
废物管理
作者
Xin Wang,Duan Zhao,Yikun Wang
标识
DOI:10.1142/s0218001423540095
摘要
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.
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