CARACTERIZAÇÃO QUANTITATIVA DE MINÉRIO DE FERRO POR MICROSCOPIA CO-LOCALIZADA
IRON ORE QUANTITATIVE CHARACTERIZATION BY CO-SITE MICROSCOPY
Gomes, Otávio da Fonseca M.; Paciornik, Sidnei
http://dx.doi.org/10.4322/tmm.00602005
Tecnol. Metal. Mater. Min., vol.6, n2, p.91-95, 2009
Resumo
Apesar do progresso nos sistemas de microscopia eletrônica de varredura (MEV), estes instrumentos não são capazes de identificar e discriminar os principais minerais de minérios de ferro (hematita e magnetita). Já a microscopia óptica de luz refletida (MO) pode facilmente distinguir estes óxidos de ferro por suas refletâncias, mas não consegue discriminar quartzo e resina epóxi. Deste modo, a caracterização microestrutural quantitativa dos minérios de ferro ainda é um desafio. No presente trabalho, uma metodologia de microscopia co-localizada que combina imagens adquiridas em MO e em MEV é aplicada na caracterização quantitativa de um minério de ferro itabirítico. A chamada microscopia co-localizada MO-MEV é capaz de discriminar as fases que não são distinguíveis por MO (resina epóxi e quartzo) e por MEV (hematita e magnetita) por meio desta abordagem multimodal, possibilitando a subsequente quantificação mineralógica. A metodologia utilizada emprega uma rotina automática baseada em técnicas de Análise de Imagens e Reconhecimento de Padrões. A quantificação mineralógica realizada por análise de imagens é consistente com os resultados independentemente obtidos pela técnica de Rietveld.
Palavras-chave
Minério de ferro, Caracterização, Microscopia, Análise de imagem
Abstract
Despite progress in Scanning Electron Microscopy (SEM) automatic instruments, these systems are not capable of performing the identification and discrimination of major iron ore minerals (hematite and magnetite). On the other hand, Reflected Light Microscopy (RLM) can easily distinguish these iron oxides by their reflectancies, but it cannot discriminate quartz and epoxy resin, which presents similar color on images. Therefore, iron ore quantitative microstructural characterization is still a challenge. In the present work, a Co-Site Microscopy methodology that combines images obtained by RLM and SEM is applied to perform a quantitative characterization of an itabiritic iron ore. The so-called RLM-SEM Co-site Microscopy can discriminate phases that are not distinguishable with either RLM (epoxy resin and quartz) or SEM (hematite and magnetite) through this multimodal approach, allowing the subsequent mineralogical quantification. The applied methodology employs an automatic routine based on Image Analysis and Pattern Recognition techniques. The mineralogical quantification computed by image analysis was consistent with independently obtained results based on the Rietveld technique.
Keywords
Iron ore, Characterization, Microscopy, Image analysis
Referências
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3 WAGNER, D.T.; ROUCO, H.V.; GOMES, O.D.M; PACIORNIK, S.; VIEIRA, M.B. Iron ore pellet characterization through digital microscopy. In: INTERNATIONAL SYMPOSIUM ON IRON ORE, 2., 2008, São Luís. Proceedings… São Paulo: ABM, 2008. p. 231-6.
4 ALVAREZ, J.C.; WAGNER, D.T.; SCHINAZI, G.; GOMES, O.D.M.; MAURÍCIO, M.H.P.; PACIORNIK, S.; VIEIRA, M.B. Qualitative and quantitative evaluation of iron ore sinters through digital microscopy. In: INTERNATIONAL CONGRESS ON APPLIED MINERALOGY, 9., 2008, Brisbane. Proceedings… Carlton: AusIMM, 2008. p. 669-72.
5 CRIDDLE, A.J.; STANLEY, C.J. Quantitative data file for ore minerals. 3. ed. London: Chapman & Hall, 1993.
6 NEUMANN, R.; STANLEY, C.J. Specular reflectance data for quartz and some epoxy resins: implications for digital image analysis based on reflected light optical microscopy. In: INTERNATIONAL CONGRESS ON APPLIED MINERALOGY, 9., 2008, Brisbane. Proceedings… Carlton: AusIMM, 2008. p. 703-5.
7 GOLDSTEIN, J.I.; NEWBURY, D.E.; ECHLIN, P.; JOY, D.C.; ROMIG Jr., A.D.; LYMAN, C.E.; FIORI, C.; LIFSHIN, E. Scanning electron microscopy and X-ray microanalysis: a text for biologists, materials scientists and geologists. 2. ed. New York: Plenum, 1992.
8 GOMES, O.D.M. Microscopia co-localizada: novas possibilidades na caracterização de minérios. 2007. 103 f. Tese (Doutorado em Engenharia Metalúrgica e de Materiais) – Pontifícia Universidade Católica do Rio de Janeiro, 2007.
9 GOMES, O.D.M.; PACIORNIK, S. Co-site microscopy: combining reflected light and scanning electron microscopy to perform ore mineralogy. In: INTERNATIONAL CONGRESS ON APPLIED MINERALOGY, 9., 2008, Brisbane. Proceedings… Carlton: AusIMM, 2008. p. 695-8.
10 PIRARD, E.; LEBRUN, V.; NIVART, J.F. Optimal Acquisition of Video Images in Reflected Light Microscopy. European Microscopy and Analysis, v. 60, p. 19-21, July 1999.
11 ZITOVA, B.; FLUSSER, J. Image registration methods: a survey. Image and Vision Computing, v. 21, n. 11, p. 977-1000, Oct. 2003.
12 DUDA, R.O.; HART, P.E.; STORK, D.G. Pattern classification. 2 ed. New York: Wiley-Interscience, 2001.
13 Gonzalez, R.C.; Woods, R.E. Digital image processing. 2. ed. Upper Saddle River: Prentice-Hall, 2002.
14 RIETVELD, H.M. Line profiles of neutron powder-diffraction peaks for structure refinement. Acta Crystallographica, v. 22, n. 1, p. 151-2, Jan. 1967.
15 GOMES, O.D.M.; PACIORNIK, S. Iron ore quantitative characterisation through reflected light-scanning electron co-site microscopy. In: INTERNATIONAL CONGRESS ON APPLIED MINERALOGY, 9., 2008, Brisbane. Proceedings… Carlton: AusIMM, 2008. p. 699-702.
2 SANTOS, L.D.; BRANDÃO, P.R.G. LM, SEM and EDS study of microstructure of Brazilian iron ores. Microscopy and Analysis, v. 19, n. 1, p. 17-9, Jan. 2005.
3 WAGNER, D.T.; ROUCO, H.V.; GOMES, O.D.M; PACIORNIK, S.; VIEIRA, M.B. Iron ore pellet characterization through digital microscopy. In: INTERNATIONAL SYMPOSIUM ON IRON ORE, 2., 2008, São Luís. Proceedings… São Paulo: ABM, 2008. p. 231-6.
4 ALVAREZ, J.C.; WAGNER, D.T.; SCHINAZI, G.; GOMES, O.D.M.; MAURÍCIO, M.H.P.; PACIORNIK, S.; VIEIRA, M.B. Qualitative and quantitative evaluation of iron ore sinters through digital microscopy. In: INTERNATIONAL CONGRESS ON APPLIED MINERALOGY, 9., 2008, Brisbane. Proceedings… Carlton: AusIMM, 2008. p. 669-72.
5 CRIDDLE, A.J.; STANLEY, C.J. Quantitative data file for ore minerals. 3. ed. London: Chapman & Hall, 1993.
6 NEUMANN, R.; STANLEY, C.J. Specular reflectance data for quartz and some epoxy resins: implications for digital image analysis based on reflected light optical microscopy. In: INTERNATIONAL CONGRESS ON APPLIED MINERALOGY, 9., 2008, Brisbane. Proceedings… Carlton: AusIMM, 2008. p. 703-5.
7 GOLDSTEIN, J.I.; NEWBURY, D.E.; ECHLIN, P.; JOY, D.C.; ROMIG Jr., A.D.; LYMAN, C.E.; FIORI, C.; LIFSHIN, E. Scanning electron microscopy and X-ray microanalysis: a text for biologists, materials scientists and geologists. 2. ed. New York: Plenum, 1992.
8 GOMES, O.D.M. Microscopia co-localizada: novas possibilidades na caracterização de minérios. 2007. 103 f. Tese (Doutorado em Engenharia Metalúrgica e de Materiais) – Pontifícia Universidade Católica do Rio de Janeiro, 2007.
9 GOMES, O.D.M.; PACIORNIK, S. Co-site microscopy: combining reflected light and scanning electron microscopy to perform ore mineralogy. In: INTERNATIONAL CONGRESS ON APPLIED MINERALOGY, 9., 2008, Brisbane. Proceedings… Carlton: AusIMM, 2008. p. 695-8.
10 PIRARD, E.; LEBRUN, V.; NIVART, J.F. Optimal Acquisition of Video Images in Reflected Light Microscopy. European Microscopy and Analysis, v. 60, p. 19-21, July 1999.
11 ZITOVA, B.; FLUSSER, J. Image registration methods: a survey. Image and Vision Computing, v. 21, n. 11, p. 977-1000, Oct. 2003.
12 DUDA, R.O.; HART, P.E.; STORK, D.G. Pattern classification. 2 ed. New York: Wiley-Interscience, 2001.
13 Gonzalez, R.C.; Woods, R.E. Digital image processing. 2. ed. Upper Saddle River: Prentice-Hall, 2002.
14 RIETVELD, H.M. Line profiles of neutron powder-diffraction peaks for structure refinement. Acta Crystallographica, v. 22, n. 1, p. 151-2, Jan. 1967.
15 GOMES, O.D.M.; PACIORNIK, S. Iron ore quantitative characterisation through reflected light-scanning electron co-site microscopy. In: INTERNATIONAL CONGRESS ON APPLIED MINERALOGY, 9., 2008, Brisbane. Proceedings… Carlton: AusIMM, 2008. p. 699-702.
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