Application of imaging spectroscopy to multivariate ore sorting technologies

我们建议改进目前的矿石分选技术，使用高光谱成像光谱在 可见光到短波红外光的区域。据估计，超过40%的总人数 矿场的能源消耗用于破碎和研磨非均质矿床中的岩石。 既包括令人满意的矿石，也包括不受欢迎的废石。能够快速、客观地洞察变化 在整个采矿过程中，品位和岩石矿物学都将使矿山得到更大的优化 例如，将氧化物和硫化物矿石分离到不同的加工流程中。 MineSense Technologies Ltd.是一家总部位于不列颠哥伦比亚省的采矿技术公司，专门从事多元 对采矿所有阶段的矿石进行遥测。他们的客户是矿业公司，希望优化他们的 通过对开采出的矿石进行预选和分选以及废弃废石来开展业务。 高光谱成像光谱学是一种技术，它将与 公司现有的传感器。然而，由于高光谱数据的复杂性和恶劣的环境 在这种情况下，以与采矿作业相关的速度进行决策尤其具有挑战性。因此， 高光谱遥感在矿磨环境中的应用处于 科学和工程，并将从学术和行业合作中受益匪浅。 该项目的主要目标是：(1)以一个具体的矿床案例为例，探索 光谱区最适用于提高矿石分选能力，以及(2)发展科学和 成像光谱与实时多元分选相结合的技术基础。研究结果 可以为加拿大采矿业提供显著的优势。

We propose to improve on present-day ore sorting technologies using hyperspectral imaging spectroscopy in the visible to shortwave infrared regions of light. It has been estimated that that more than 40% of the total energy consumption at a mine site is used in crushing and milling of rock, which in a heterogeneous deposit includes both desirable ore and undesirable waste rock. The ability to quickly and objectively discern changes in both grade and rock mineralogy throughout the mining process would allow for greater optimization of mine operations by, for example, separating oxide and sulphide ores into different processing streams. MineSense Technologies Ltd. is a B.C.-based mining technology company specializing in multivariate telemetry of ore at all stages of mining. Their clients are mining companies that want to optimize their operations through pre-concentration and sorting of mined ore rocks as well as the rejection of waste rock. Hyperspectral imaging spectroscopy is a technique that would complement and integrate well with the company's existing sensors. However, due to the complexity of hyperspectral data and the harsh environmental conditions, decision-making at a speed relevant to a mining operation is particularly challenging. Accordingly, the application of hyperspectral remote sensing in the mining and milling environment is at the cutting edge of science and engineering and would benefit greatly from academic-industry collaboration. The main objectives of the project are: (1) to take a specific ore deposit case example and explore which spectral regions are most applicable to enhancing ore sorting capabilities, and (2) to develop the scientific and technical basis for integrating imaging spectroscopy into real time multivariate ore sorting. Results of the study could provide significant advantages for the Canadian mining industry.