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露天金属矿矿石破碎的能耗流转研究进展与展望

Research Progress and Prospects on Energy Consumption Flow in Ore Crushing of Open-pit Metal Mines

  • 摘要: 矿石由爆破至机械破磨等环节的能耗控制,是贯穿整个矿石生产的重要系统工程问题。针对大型露天金属矿山多工序协同增效的迫切需求,在回顾与总结国内外研究进展的基础上,结合团队近10 a围绕大型矿山多工序联动方面的研究积累,提出了露天金属矿矿石破碎的能耗流转理念,目的在于破解矿石开采工序割裂问题,实现全流程能耗优化与矿石质量稳定供给。据此分别阐述了钻进智能感知技术的矿岩破碎能耗建模方法、爆破块度三维信息提取方法、爆破块度空间分布特征指导铲装与配矿、基于可爆性差异的矿石破碎效率联动控制以及爆破振动能量演化特征等方面的研究进展。研究表明:(1)基于现场钻进参数构建的岩体破碎能量模型,并结合能时密度指标与效率评价函数,可有效表征岩体属性,为爆破、破碎、磨矿工序间的能耗合理调控奠定基础;(2)通过融合三维激光扫描、3D高斯泼溅及机器学习算法,实现了爆破块度从二维图像到三维几何特征的提取与体积计算,为破碎能耗计算与破碎机参数优化提供了关键数据支撑;(3)基于爆堆自适应分层模型、改进的路径规划算法及多目标智能配矿系统,形成了块度空间分布、铲装路径优化和多矿区协同配矿的精细化作业链条,有效支撑了铲装效率提升与矿石质量稳定;(4)基于可爆性分区的炸药与岩石匹配及考虑块度特征的破碎效率联动控制,可以实现炸药能量高效利用、降低全流程能耗;(5)爆破振动能量指标对岩体结构响应敏感,可将爆破振动这一有害效应转化为反演待爆区岩体信息的有效辅助手段。在此基础上,展望了“十五五”乃至更长一段时间该领域重点研究方向,认为未来需聚焦地形地质品位模型构建与可爆性精细分区、基于可爆性分区的炸药与岩石智能匹配与现场混装技术、基于可爆性差异的矿石破碎效率全过程联动控制、爆破振动能量指标表征岩体结构与损伤特征等方面开展攻关,以期形成全流程能耗优化与矿石质量稳定供给的系统性解决方案,为大型露天矿山实现绿色、高效、智能开采提供理论依据与技术支撑。

     

    Abstract: The pivotal systemic engineering issue in ore production is controlling energy consumption across the full process,from blasting through mechanical crushing and grinding. To address the paramount need for collaborative efficiency improvement in large open-pit metal mines,and based on a review and synthesis of research progress in China and abroad,together with the authors′decade of research on multi-process coupling in large mines,this paper proposes energy-flow transfer in ore fragmentation within open-pit metal mines as a central concept. Its aim is to address fragmentation in mining processes,achieve full-process energy optimization,and guarantee a stable supply of ore with consistent quality. Accordingly,this paper reviews research progress in several areas,including energy-consumption modeling for rock fragmentation based on intelligent perception during drilling,three-dimensional information extraction of blasting fragmentation,the use of spatial distribution features of blasting fragmentation to guide loading and ore blending,coupled control of ore crushing efficiency based on differences in blastability,and the developmental characteristics of blasting vibration energy. The results show that:(1) A rock fragmentation energy model constructed from field drilling parameters,combined with energy-time density indices along with efficiency evaluation functions,can effectively characterize rock-mass properties and provide a foundation for the rational regulation of energy consumption among blasting,crushing,and grinding processes.(2) Through integrating three-dimensional laser scanning,3D Gaussian splatting,and machine-learning algorithms,blasting fragmentation is able to be characterized from two-dimensional images to three-dimensional shape features and volume calculations,providing key data support for crushing energy-consumption calculation and crusher parameter refinement.(3) Based on an adaptive layered model of the muckpile,improved path-planning algorithms,and a multi-goal intelligent ore-blending system,a refined operational chain has been established that links the spatial distribution of fragmentation,loading-path optimization,and coordinated ore blending across multiple mining areas,thereby effectively supporting improvements in loading efficiency and stability of ore quality.(4) The matching of explosives and rock based on blastability zoning,together with coupled control of crushing efficiency that accounts for fragmentation characteristics,can improve the utilization efficiency of explosive energy and reduce full-process energy consumption.(5) Blasting vibration energy indicators are sensitive to the structural response of the rock mass,enabling blasting vibration,traditionally regarded as an adverse effect,to be transformed into an effective auxiliary means for inferring rock-mass information in the area to be blasted.Building on this,the paper further discusses key research directions for the field during the 15 th Five-Year Plan period and beyond. Future research ought to focus on the construction of integrated terrain-geology-grade models and refined blastability zoning,intelligent matching of explosives and rock based on blastability zoning and on-site mixed charging technologies,fullprocess coupled control of ore crushing efficiency based on differences in blastability,and characterization of rock-mass structure and damage features using blasting vibration energy indicators. These efforts are expected to add to a systematic solution for full-process energy optimization and stable ore-quality supply,thereby supplying theoretical foundations and technical support for green,efficient,and intelligent mining in large open-pit mines.

     

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