基于支架数据优化的工作面矿压预测模型研究  

Mine pressure prediction model for fully mechanized working face based on data optimization of hydraulic support

作　　者：冯银辉 宋阳 李务晋 吴雨欣 秦泽宇 FENG Yinhui;SONG Yang;LI Wujin;WU Yuxin;QIN Zeyu(Beijing Tianma Intelligent Control Technology Co.,Ltd.,Beijing 101399,China;School of Mechatronics and Information Engineering,China University of Mining and Technology-Beijing,Beijing 100083,China;School of Chemical and Environmental Engineering,China University of Mining and Technology-Beijing,Beijing 100083,China)

机构地区：[1]北京天玛智控科技股份有限公司,北京101399 [2]中国矿业大学(北京)机电与信息工程学院,北京100083 [3]中国矿业大学(北京)化学与环境工程学院,北京100083

出　　处：《煤炭工程》2023年第6期101-107,共7页Coal Engineering

基　　金：天地科技股份有限公司科技创新创业资金项目(2020-2-TD-CXY004);国家能源集团重点项目(GJNY-21-25);天玛智控重点科技项目(2022TMO18-C1)。

摘　　要：矿压预测是实现综采工作面智能化的重要组成部分,具有广阔的应用场景。液压支架载荷是综采工作面覆岩运动的直接体现,其载荷峰值循环末阻力是判断顶板来压,开展煤矿顶板、水、火灾害防控的关键指标。本研究以预测循环末阻力的变化对矿压显现规律进行表征,形成一套基于区域化的支架数据质量优化方法,时空融合的顶板压力预测模型构建,以及多尺度部署的方法体系。实验结果表明结合了注意力机制的Conv1d+Bi-LSTM时空模型有效提取了液压支架的工况矩阵的特征信息,针对不同情况的数据优化方法提升了模型的预测精度,模型具有良好的鲁棒性与泛化性,可实现矿压的精确预测。多尺度的部署方法实现了模型灵活部署对实际预测有着重要意义。Mine pressure prediction is an important part of realizing the intellectualization of the fully mechanized mining face,which has a wide range of application scenarios.The hydraulic support load is a direct reflection of the overburden movement of the fully mechanized mining face,and the end-cycle resistance of the load peak is a key indicator for judging the pressure from the roof and carrying out the prevention and control of the coal mine roof,water,and fire disasters.The resistance variation at the end of the cycle is predicted to characterize the occurrence of mine pressure,and a set of support data quality optimization methods based on regionalization,roof pressure prediction model construction based on space-time fusion,and multi-scale deployment method systems are formed.The experimental results show that the Conv1d+Bi-LSTM temporal-spatial model combined with the attention mechanism can effectively extract the characteristic information of the working condition matrix of the hydraulic support,and the data optimization method for different situations improves the prediction accuracy of the model,and the model has good robustness with generalizability,accurate prediction of mineral pressure can be achieved.The multiscale deployment method realizes the flexible deployment of the model,which is of great significance for practical prediction.

关 键 词：矿压预测 液压支架 时空融合网络 矿山压力 周期来压 

分 类 号：TD355[矿业工程—矿井建设]