采矿工程中基于路径规划的掘进方向的优化设计

Optimization Design of Excavation Direction in Mining Engineering Based on Path Planning

采矿工程中的掘进方向优化设计具有重要的经济和社会意义,传统的手动调整方法已不能满足需求。为此,本文提出了基于数据驱动和基于知识库两种技术路径的掘进方向优化设计方法。基于数据驱动的技术路径利用大数据分析和深度学习技术,从现场采集的监测参数中得到实时准确的数据分析和处理结果,构建数值模型并实现掘进方向的优化和控制。基于知识库的技术路径则重点整合和应用采矿工程中的领域知识,通过知识库的建立和更新,实现掘进方向规划的高效率和优化目标。本文的优化设计方法有效解决了掘进方向优化设计中存在的难点和问题,提高了采矿工程的效率和生产效益。

The optimization design of excavation dire ction in mining engineering has important economic and social significance,and traditional manual adjustment methods can no longer meet the needs.Therefore,this article proposes a method for optimizing the design of excavation direction based on two technical paths:data-driven and knowledge-based.Based on data-driven technology path,big data analysis and deep learning technology are utilized to obtain real-time and accurate data analysis and processing results from on-site monitoring parameters,construct numerical models,and achieve optimization and control of excavation direction.The technical path based on the knowledge base focuses on integrating and applying domain knowledge in mining engineering,and through the establishment and updating of the knowledge base,the high efficiency of the tunneling direction planning and the achievement of the optimization goal are achieved.The optimization design method in this paper effectively solves the difficulties and problems in the optimization design of excavation direction,and improves the efficiency and production efficiency of mining engineering.