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Comparative Study of Iron Ore Characterisation by Optical Image Analysis and QEMSCAN?

机译：利用光学图像分析和QEMSCAN进行铁矿石表征的比较研究？

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In order to develop downstream processing routines for iron ore and to understand the behaviour ofrnthe ore during such processing, extensive mineralogical characterisation is required. To determinernmineral associations, mineral liberation and grain size distribution, imaging techniques have to bernused. There are two main imaging techniques used for the characterisation of iron ore, ie, OpticalrnImage Analysis (OIA) and Scanning Electron Microscopy (SEM). In this article a QEMSCAN?rnsystem is used as an example of SEM methodology and results obtained from it are comparedrnagainst results obtained by the CSIRO 'Recognition3/Mineral3' OIA system.rnBoth OIA and QEMSCAN? systems have advantages and drawbacks. Even though the latestrnQEMSCAN? systems can distinguish between major iron oxides and oxyhydroxides, it is stillrnproblematic for QEMSCAN? to distinguish between iron ore minerals very close in oxygenrncontent, eg haematite and hydroheamatite, or between different types of vitreous goethite.rnQEMSCAN? also can misidentify minerals with close chemical composition, ie haematite asrnmagnetite and vitreous goethite as haematite. In OIA, iron minerals with slight differences in theirrnoxidation or hydration state are more easily and directly recognisable by correlation with theirrnrefl ectivity. In both methods, the presence of microporosity can result in some misidentifi cation,rnbut in SEM methods misidentifi cations due to microporosity can be critical. Low resolution duringrnQEMSCAN? analysis can signifi cantly affect the textural classifi cation of particle sections.rnThe main conclusion of this study is that, for low iron content ores or tailings, QEMSCAN?rncan provide much more detailed information on the gangue minerals than OIA. However, forrnroutine characterisation of iron ores with high iron content and containing a variety of ironrnoxides and oxyhydroxides, OIA is a faster, more cost-effective and more reliable method of ironrnore characterisation. A combined approach using both techniques will provide the most detailedrnunderstanding of iron ore samples being characterised.
机译：为了开发铁矿石的下游处理程序并了解铁矿石在此类处理过程中的行为，需要进行广泛的矿物学表征。为了确定矿物的结合，矿物的释放和粒度分布，必须采用成像技术。用于表征铁矿石的主要成像技术有两种，即光学图像分析（OIA）和扫描电子显微镜（SEM）。在本文中，以QEMSCAN？系统作为SEM方法的示例，并比较了从CSIRO'Recognition3 / Mineral3'OIA系统获得的结果。系统各有利弊。即使最新rnQEMSCAN？系统可以区分主要的氧化铁和羟基氧化铁，对于QEMSCAN还是有问题的吗？区分含氧量非常接近的铁矿石矿物（例如赤铁矿和水赤铁矿）或不同类型的玻璃针铁矿。也可以将化学成分接近的矿物误识别为赤铁矿，磁铁矿和玻璃质针铁矿为赤铁矿。在OIA中，通过氧化铁或水合状态的反射率相关性，可以更容易，直接地识别出氧化或水合状态稍有不同的铁矿物质。在这两种方法中，微孔的存在都会导致某些错误识别，但是在SEM方法中，由于微孔导致的错误识别可能很关键。 QEMSCAN期间分辨率低？这项研究的主要结论是，对于低铁含量的矿石或尾矿，QEMSCAN®可以提供比O煤更详细的O石矿物信息。但是，对于铁含量高且包含多种氧化铁和氢氧化铁的铁矿石进行常规表征，OIA是一种更快，更经济高效且更可靠的表征铁矿石的方法。结合使用这两种技术的方法将最详细地了解所表征的铁矿石样品。

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  • 来源
    《Iron ore 2011》|2011年|p.213-222|共10页
  • 会议地点 Perth(AU)
  • 作者

    E Donskoi; J R Manuel; P Austin; A Poliakov; M J Peterson; S Hapugoda;

  • 作者单位

    Mineral Processing Modelling, CSIRO Process Science and Engineering, PO Box 883, Kenmore Qld 4069. Email: Eugene.Donskoi@csiro.au;

    Ore Characterisation, CSIRO Process Science and Engineering, PO Box 883, Kenmore Qld 4069. Email: James.Manuel@csiro.au;

    Micro-Characterisation Laboratory, CSIRO Process Science and Engineering, PO Box 90, Bentley WA 6982. Email: Peter.Austin@csiro.au;

    SIRO CPSE, PO Box 883, Kenmore Qld 4069. Email: Andrei.Poliakov@csiro.au;

    CSIRO Process Science and Engineering, PO Box 883, Kenmore Qld 4069. Email: Michael.Peterson@csiro.au;

    CSIRO Process Science and Engineering, PO Box 883, Kenmore Qld 4069. Email: Sarath.Hapugoda@csiro.au;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 铁矿石;
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