智能化综放工作面顶煤厚度探测方法

Top coal thickness detection method for intelligent fully-mechanized working face

  • 摘要: 提前探测综放工作面顶煤厚度可为精准控制放顶煤提供依据,有利于实现放煤采出率和煤质的平衡。通过分析探地雷达探测煤岩界面及煤层厚度的原理,设计了一种用于探测顶煤厚度的探地雷达装置,进一步提出了基于探地雷达的智能化综放工作面顶煤厚度探测方法:通过探地雷达装置发射和接收雷达脉冲波,接收信号经放大、采样、积分等处理形成雷达帧,通过WiFi方式实时传输至无人采煤机控制单元,最终传输至集控室控制台,由煤岩分界面提取软件处理、分析反射信号波形与灰度图,根据反射信号最大幅值与最小幅值确定煤岩分界面位置,通过最大或最小幅值位置与雷达脉冲发射起点的时间差计算出煤层厚度。在王家岭煤矿12309综放工作面对该方法进行测试,结果表明:某处雷达反射波灰度图解释的顶煤厚度探测结果为3383 m,与人工测量的实际值(316 m)误差为7%;可探测最大顶煤厚度为5 m,最大探测误差不超过10%,满足实际探测需求。

     

    Abstract: Detecting the thickness of the top coal in a fully mechanized working face in advance can provide a basis for precise control of the top coal caving, which is beneficial to achieving a balance between the coal caving recovery rate and coal quality. By analyzing the principle of ground-penetrating radar detecting coal-rock interface and coal seam thickness, a ground-penetrating radar device for detecting top coal thickness is designed, and an intelligent method for detecting the thickness of top coal in fully mechanized working face based on ground penetrating radar is further proposed. The radar pulse wave is transmitted and received by the ground-penetrating radar device, and the received signal is amplified, sampled and integrated to form a radar frame, which is transmitted to the control unit of the unmanned coal mining machine in real time by WiFi and finally to the console of the central control room. The coal-rock interface extraction software processes and analyzes the reflected signal waveform and gray-scale image, and determines the position of the coal-rock interface according to the maximum and minimum amplitude of the reflected signal. The method calculates the coal seam thickness by the time difference between the position of maximum or minimum amplitude and the starting point of radar pulse emission. The method is tested in the 12309 fully mechanized working face of Wangjialing Coal Mine. And the results show that the top coal thickness detection result interpreted by radar reflection wave gray-scale image at a certain place is 3.383 m, and the error of the actual value (3.16 m) detected manually is 7%. The maximum thickness of the top coal that can be detected is 5 m, and the maximum detection error does not exceed 10%. The performance meets the actual detection requirements.

     

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