Leonard T. Krebbers , Natalia Grozmani , Bernd G. Lottermoser , Robert H. Schmitt
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引用次数: 0
摘要
正确的矿石表征对于了解矿床和开发高效的矿物加工流程至关重要。传统的矿物学和化学技术通常用于研究矿石,但它们可能具有破坏性,在某些情况下只能提供二维信息。计算机断层扫描(CT)是原材料领域的一项新兴技术,可对矿石矿物学和微观结构进行非破坏性三维分析。然而,单能量 CT(SECT)在对具有多种衰减特性的多相地质材料进行精确成像和区分方面存在一些局限性。相比之下,双能量 CT(DECT)使用两种不同的 X 射线能量获取数据,可用于区分具有相似衰减特性的材料。本研究探讨了如何应用 DECT 分析多相石墨矿石。研究采用了一种顺序融合方法,将不同 X 射线能量扫描获得的数据在高空间分辨率下进行组合,并应用不同的加权因子来确定每个能级和光谱的最佳贡献。根据对比度-噪声比(CNR)和 Q 因子对 SECT 和 DECT 数据集进行了定量评估。研究结果表明,与 SECT 相比,DECT 显著改善了图像对比度,同时进一步提高了图像清晰度。因此,DECT 可以实现更准确的分割,从而对石墨矿石进行更准确的三维定量分析。
Dual-energy computed tomography for improved contrast on a polyphase graphitic ore
Proper ore characterisation is essential for understanding ore deposits and developing efficient mineral processing flow sheets. Conventional mineralogical and chemical techniques are usually used to study ores, but they can be destructive and, in some cases, provide only 2D information. Computed tomography (CT) is an emerging technology in the raw materials sector enabling the non-destructive 3D analysis of the ore mineralogy and microstructure. However, single-energy CT (SECT) has some limitations concerning the accurate imaging and differentiation of polyphase geomaterials comprising a broad range of attenuation properties. By contrast, dual-energy CT (DECT) uses two different X-ray energies to acquire data, which can be used to distinguish between materials with similar attenuation properties. This study explored the application of DECT for the analysis of a polyphase graphitic ore. A sequential fusion approach was utilized to combine data obtained from different X-ray energy scans at high spatial resolution, and varying weighting factors were applied to determine the optimal contribution of each energy level and spectrum. Both, SECT and DECT datasets were quantitatively evaluated based on the contrast-to-noise-ratio (CNR) and Q factor. The findings demonstrate that DECT significantly improves image contrast compared to SECT while further increases image sharpness. As a result, DECT may enable more accurate segmentation and, therefore, more accurate quantitative 3D analysis of graphite ores.