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8-125 MM KOLEMANİT CEVHERİNİN NIR/CCD OPTİK AYIRICI İLE ZENGİNLEŞTİRİLMESİ

Year 2018, Volume: 6 Issue: 2, 414 - 425, 30.06.2018
https://doi.org/10.29109/http-gujsc-gazi-edu-tr.344767

Abstract

Optik ayırma teknolojisi gıda, maden ve geri
dönüşüm gibi alanlarda yaygın kullanımı olan ve malzemelerin kendine has
özelliklerine göre ayrımını sağlayan bir teknolojidir. Optik ayırma ile
geleneksel yöntemlerle yapılan ayrım işlemlerinden çok daha yüksek verimde ve
kapasitede zenginleştirme yapmak mümkündür. Temelde malzemelerin ürün ve atık
olarak sınıflandırılması veya farklı tür malzemelerin birbirinden
ayrıştırılmasının yapıldığı optik ayırma teknolojisi, insan gücüyle yapılması
olanaksız ayrımların yapılmasını mümkün kılmaktadır. Renksel farklılıkları
belirlenemeyen malzemelerin geniş spektral aralıklarda tanımlanması ile yüksek
kapasitede ayrımının yapılmasında da verimli bir yöntem olarak özellikle tercih
edilmektedir. Bu çalışmada Eti Maden İşletmeleri Genel Müdürlüğü, Bigadiç Bor
İşletme Müdürlüğü ocaklarından kil, tüf, kireç taşı gibi minerallerle birlikte
çıkan 8-125 mm Simav Ana Damar (SAD), Simav Tali Damar (STD) ve Tülü Sarı (TS)
kolemanit cevherleri, yakın kızılötesi (NIR) ve görünür ışık (CCD) kaynakları
kullanılan optik ayıcılarla zenginleştirilmiştir. Çalışmalarda kırma, eleme ve
yıkama işlemlerinden geçirilen cevher 8-25 mm ve 25-125 mm tane boyutlarında
zenginleştirme yapan iki optik ayırıcıya beslenmiş ve %22,10-39,30 B2O3
tenör aralığında beslenen cevherlerde 3,90-9,10 birim zenginleştirme
sağlanmıştır. %93’ün üzerinde verimle yapılan zenginleştirme sonrası
%2,20-11,10 B2O3 tenör aralığında atık açığa çıkmıştır.




References

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  • 4. Williams, P., Norris, K., Near-infrared Technology in the Agricultural and Food Industries, American Association of Cereal Chemists, Wisconsin, A.B.D., 1987.
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  • 6. Blasco J., Aleixos N., Gomez J., Molto E., Citrus sorting by identification of the most common defects using multispectral computer vision, J. Food Eng., 83, 384-393, 2007.
  • 7. Razieh P., Hamid R.G., Hadi S., Fariborz Z.N., Mohammad M.V., Study on an automatic sorting system for date fruits, J. Saudi Soc. Agric. Sci., 14, 83-90, 2015. 8. Silvia S., Daniela C., Federico M., Giuseppe B., Classification of oat and groat kernels using NIR hyperspectral imaging, Talanta, 103, 276-284, 2013.
  • 9. Mage I., Wol J.P., Bjerke F., Segtnan V., On-line sorting of meat trimmings into targeted fat categories, J. Food Eng., 115, 306-313, 2013.
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  • 11. Batchelor A.R., Ferrari-John R.S., Katrib J., Udoudo O., Jones D.A., Dodds C., Kingman S.W., Pilot scale microwave sorting of porphyry copper ores: Part 1 – Laboratory investigations, Miner. Eng., 98, 303-327, 2016.
  • 12. Veerendra S., Rao S. M., Application of image processing and radial basis neural network techniques for ore sorting and ore classification, Miner. Eng., 18, 1412-1420, 2005.
  • 13. Tessier J., Duchesne C., Bartolacci G., A machine vision approach to on-line estimation of run-of-mine ore composition on conveyor belts, Miner. Eng., 20, 1129-1144, 2007.
  • 14. Lane G.R., Martin C., Pirard E., Techniques and applications for predictive metallurgy and ore characterization using optical image analysis, Miner. Eng., 21, 568-577, 2008.
  • 15. Snehamoy C., Ashis B., Biswajit S., Samir K.P., Image-based quality monitoring system of limestone ore grades, Comput. Ind., 61, 391-408, 2010.
  • 16. Sophie L., Godefroid D., David B., Eric P., Optical analysis of particle size and chromite liberation from pulp samples of a UG2 ore regrinding circuit, Miner. Eng., 24, 1340-1347, 2011.
  • 17. Joseph L., William S., Kai B., Jesus F., Larry M., Bridging the gap: Understanding the economic impact of ore sorting on a mineral processing circuit, Miner. Eng., 91, 92-99, 2016.
  • 18. Barış, M., Albayrak, S., Metin, F.C., Ünaldı, O., Tektaş, E., “Enrichment of 8-25 mm Colemanite Middlings by Optical Sorting”, XVII. International Boron, Borides and Related Materials, 255, İstanbul-Türkiye, 11-17 Eylül, 2011.
  • 19. Gannouni S., Noamen Rebai N., Abdeljaoued S., A spectroscopic approach to assess heavy metals contents of the mine waste of jalta and bougrine in the north of Tunisia, J. Geog. Inf. Syst, 4, 242-253, 2012.
  • 20. Cutmore N.G., Liu Y., Middleton A.G., Ore characterisation and sorting, Miner. Eng., 10 (4), 421-426, 1997.
  • 21. Cutmore N.G., Liu Y., Middleton A.G., On-line ore characterisation and sorting, Miner. Eng., 11 (9), 843-847, 1998.
  • 22. Derek P., George W.L., Donald L.S., ATR-FTIR spectroscopic studies of boric acid adsorption on hydrous ferric oxide, Geochim. Cosmochim. Acta, 67 (14), 2551–2560, 2003.
  • 23. Budak A., Gonen M., Extraction of boric acid from colemanite mineral by supercritical carbon dioxide, J. Supercrit. Fluids, 92, 183-189, 2014.
Year 2018, Volume: 6 Issue: 2, 414 - 425, 30.06.2018
https://doi.org/10.29109/http-gujsc-gazi-edu-tr.344767

Abstract

References

  • 1. Barry A.W., Tim N.M., Ore Sorting, Wills' Mineral Processing Technology 7th Edition, Burlington, A.B.D., 2006.
  • 2. Çelik C, Cevher zenginleştirmede gelişen teknolojiler: Optik zenginleştirme, Madencilik Türkiye, 4, 40-43, 2010.
  • 3. Petra T., Markus W, Thomas P., Industrial application for inline material sorting using hyperspectral imaging in the NIR range, Real-Time Imaging, 11, 99-107, 2005.
  • 4. Williams, P., Norris, K., Near-infrared Technology in the Agricultural and Food Industries, American Association of Cereal Chemists, Wisconsin, A.B.D., 1987.
  • 5. Sathish P.G., Subrata H., Atul T., A review on automated sorting of source-separated municipal solid waste for recycling, Waste Manage., 60, 56-74, 2017.
  • 6. Blasco J., Aleixos N., Gomez J., Molto E., Citrus sorting by identification of the most common defects using multispectral computer vision, J. Food Eng., 83, 384-393, 2007.
  • 7. Razieh P., Hamid R.G., Hadi S., Fariborz Z.N., Mohammad M.V., Study on an automatic sorting system for date fruits, J. Saudi Soc. Agric. Sci., 14, 83-90, 2015. 8. Silvia S., Daniela C., Federico M., Giuseppe B., Classification of oat and groat kernels using NIR hyperspectral imaging, Talanta, 103, 276-284, 2013.
  • 9. Mage I., Wol J.P., Bjerke F., Segtnan V., On-line sorting of meat trimmings into targeted fat categories, J. Food Eng., 115, 306-313, 2013.
  • 10. Murphy B., Zyl J., Domingo G., Underground preconcentration by ore sorting and coarse gravity separation, Narrow Vein Mining Conference , Perth-West Aust., 26-27 Mart, 2012.
  • 11. Batchelor A.R., Ferrari-John R.S., Katrib J., Udoudo O., Jones D.A., Dodds C., Kingman S.W., Pilot scale microwave sorting of porphyry copper ores: Part 1 – Laboratory investigations, Miner. Eng., 98, 303-327, 2016.
  • 12. Veerendra S., Rao S. M., Application of image processing and radial basis neural network techniques for ore sorting and ore classification, Miner. Eng., 18, 1412-1420, 2005.
  • 13. Tessier J., Duchesne C., Bartolacci G., A machine vision approach to on-line estimation of run-of-mine ore composition on conveyor belts, Miner. Eng., 20, 1129-1144, 2007.
  • 14. Lane G.R., Martin C., Pirard E., Techniques and applications for predictive metallurgy and ore characterization using optical image analysis, Miner. Eng., 21, 568-577, 2008.
  • 15. Snehamoy C., Ashis B., Biswajit S., Samir K.P., Image-based quality monitoring system of limestone ore grades, Comput. Ind., 61, 391-408, 2010.
  • 16. Sophie L., Godefroid D., David B., Eric P., Optical analysis of particle size and chromite liberation from pulp samples of a UG2 ore regrinding circuit, Miner. Eng., 24, 1340-1347, 2011.
  • 17. Joseph L., William S., Kai B., Jesus F., Larry M., Bridging the gap: Understanding the economic impact of ore sorting on a mineral processing circuit, Miner. Eng., 91, 92-99, 2016.
  • 18. Barış, M., Albayrak, S., Metin, F.C., Ünaldı, O., Tektaş, E., “Enrichment of 8-25 mm Colemanite Middlings by Optical Sorting”, XVII. International Boron, Borides and Related Materials, 255, İstanbul-Türkiye, 11-17 Eylül, 2011.
  • 19. Gannouni S., Noamen Rebai N., Abdeljaoued S., A spectroscopic approach to assess heavy metals contents of the mine waste of jalta and bougrine in the north of Tunisia, J. Geog. Inf. Syst, 4, 242-253, 2012.
  • 20. Cutmore N.G., Liu Y., Middleton A.G., Ore characterisation and sorting, Miner. Eng., 10 (4), 421-426, 1997.
  • 21. Cutmore N.G., Liu Y., Middleton A.G., On-line ore characterisation and sorting, Miner. Eng., 11 (9), 843-847, 1998.
  • 22. Derek P., George W.L., Donald L.S., ATR-FTIR spectroscopic studies of boric acid adsorption on hydrous ferric oxide, Geochim. Cosmochim. Acta, 67 (14), 2551–2560, 2003.
  • 23. Budak A., Gonen M., Extraction of boric acid from colemanite mineral by supercritical carbon dioxide, J. Supercrit. Fluids, 92, 183-189, 2014.
There are 22 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Original Articles
Authors

Mustafa Barış

Fazlı Cabbar Metin This is me

Nurtaç Kıymet Karabulut This is me

Fatih ÖZYÜCEL Özyücel This is me

Publication Date June 30, 2018
Submission Date October 17, 2017
Published in Issue Year 2018 Volume: 6 Issue: 2

Cite

APA Barış, M., Metin, F. C., Karabulut, N. K., Özyücel, F. Ö. (2018). 8-125 MM KOLEMANİT CEVHERİNİN NIR/CCD OPTİK AYIRICI İLE ZENGİNLEŞTİRİLMESİ. Gazi University Journal of Science Part C: Design and Technology, 6(2), 414-425. https://doi.org/10.29109/http-gujsc-gazi-edu-tr.344767

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