Application of imaging spectroscopy to multivariate ore sorting technologies

我们建议使用高光谱成像光谱技术改进目前的矿石分选技术， 从可见光到短波红外区的光。据估计，超过40%的 在非均质存款中，矿场的能量消耗用于岩石的破碎和研磨 包括期望的矿石和不期望的废石。快速客观地辨别变化的能力 在整个采矿过程中，在品位和岩石矿物学方面的改进将允许更大程度地优化采矿 例如，通过将氧化物和硫化物矿石分离成不同的加工流来进行操作。 MineSense Technologies Ltd.是一家B.C.-基于采矿技术公司专业从事多元 在采矿的各个阶段进行矿石遥测。他们的客户是希望优化其 通过对开采的矿石进行预浓缩和分选以及废弃矿石的操作。 高光谱成像光谱技术是一种能够很好地补充和整合超光谱成像技术的技术。 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做出决策尤其具有挑战性。因此，委员会建议， 高光谱遥感在采矿和铣削环境中的应用处于最前沿， 科学和工程，并将大大受益于学术界和工业界的合作。 本项目的主要目标是：（1）以一个具体的矿石存款案例为例，探讨 光谱区域最适用于提高矿石分选能力，（2）发展科学和 为成像光谱技术用于真实的实时多元矿石分选提供了技术基础。研究结果 可以为加拿大矿业提供巨大的优势。

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.