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首页> 外文会议>Second international future mining conference 2011 >Towards Tomorrow's'Smart Mine' - Embedded Sensor Telemetry and Sensor-Based Sorting
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Towards Tomorrow's'Smart Mine' - Embedded Sensor Telemetry and Sensor-Based Sorting

机译：迈向明天的“智能矿山”-嵌入式传感器遥测和基于传感器的分类

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摘要

This paper stems from research and development in sensor and sorting technologies towards future sustainable mining undertaken by the UBC Mine-Mill Integration group in collaboration with MineSense Ltd. Sensors and sensor-based technologies such as ore telemetry and sorting are envisioned to be a significant component in achieving such 'invisible' future sustainable mining. Such technologies offer high flexibility and power in use: delivering valuable information from the very preliminary stages of mining exploration through to final upgrading of the ore preceding the fine comminution stages. This paper reviews sensors and sorting as enabling technologies towards a future smart mining operation and introduces a model in which sensor-based exploration (down-the-hole sensing), ore exploitation (smart-shovels), transportation (smart-conveyors) and preconcentration (sensor-based sorters) are effectively integrated to increase the present value of operations. It is anticipated on the basis of several case studies that an effective use of sensor technologies through tomorrow's 'smart mine model' should lead to several positive impacts ranging from increased mining production, to reductions in transport costs, overall energy use and waste generation. In this way sensors can be used to maximise the profitability and present value of the mining operation from the exploration stage through to mine closure.
机译：本文源自传感器和分选技术的研究与开发，由UBC MineSense Ltd.与UBC MineSense Ltd.合作进行的未来可持续采矿。传感器和基于传感器的技术（例如矿石遥测和分选）被认为是重要的组成部分实现这种“无形”的未来可持续采矿。此类技术提供了高度的灵活性和强大的使用能力：从采矿勘探的最初阶段到精细粉碎阶段之前的矿石最终升级，提供有价值的信息。本文回顾了传感器和分类技术，这些技术是实现未来智能采矿作业的支持技术，并介绍了一个模型，其中基于传感器的勘探（井下传感），矿石开采（智能铲），运输（智能输送机）和预选矿（基于传感器的分类器）被有效地集成以增加操作的现值。根据一些案例研究，可以预期，通过明天的“智能矿山模型”有效使用传感器技术将带来若干积极影响，包括采矿产量增加，运输成本降低，总体能源使用和废物产生。通过这种方式，可以使用传感器来最大化从勘探阶段到矿山关闭的采矿作业的收益率和现值。

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  • 来源
  • 会议地点 Sydney(AU)
  • 作者

    B Klein; A Bamber; N E Altun; M Scoble;

  • 作者单位

    NB Keevil Institute of Mining Engineering, University of British Columbia, Vancouver BC V6T1Z4, Canada;

    MineSense Technologies Ltd, 122 -1857 West 4th Avenue, Vancouver BC V6J 1M4, Canada;

    Mugla University, Mining Engineering Department, Mugla 48000, Turkey;

    NB Keevil Institute of Mining Engineering, University of British Columbia, Vancouver BC V6T 1Z4, Canada;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 地质、矿业;
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