智能化综采技术下采煤机顶底板截割轨迹规划分析研究

Analysis and research on cutting trajectory planning of shearer roof and floor under intelligent fully mechanized mining technology

由于井下综采工作面现场环境复杂,双滚筒电牵引采煤机自适应截割过程中,顶底板截割高度不能及时进行调整,导致出现顶底板轨迹控制较差,截割效率低的问题。基于此,本文以王坪煤业MG400/980-WD交流电牵引采煤机顶底板截割轨迹规划为研究对象,首先基于克里金插值算法构建煤层三维静态模型,获取初始顶底板截割轨迹,将初始轨迹与历史截割数据相融合,通过LSTM神经网络算法实现下一刀轨迹预测动态修正。从验证结果来看,修正前轨迹误差范围在5~15 cm,经过动态修正后轨迹误差范围集中在0~10 cm,修正后小误差比例占总区域的96%以上,提高了轨迹的准确度。

Due to the complex environment of the underground fully mechanized mining face,the cutting height of the roof and floor cannot be adjusted in time during the adaptive cutting process of the double drum electric traction shearer,resulting in poor control of the roof and floor trajectory and low cutting efficiency.Based on this,this paper takes the roof and floor cutting trajectory planning of MG400/980-WD alternating current traction shearer in Wangping Coal Industry as the research object.Firstly,a three-dimensional static model of coal seam is constructed based on Kriging interpolation algorithm to obtain the initial roof and floor cutting trajectory.The initial trajectory is integrated with the historical cutting data,and the dynamic correction of the next tool trajectory prediction is realized by LSTM neural network algorithm.From the verification results,the trajectory error range before correction is 5~15 cm,and the trajectory error range after dynamic correction is concentrated in 0-10 cm.The proportion of small error after correction accounts for more than 96%of the total area,which improves the accuracy of the trajectory.