Abstract
Automatic control of fine-coal cleaning circuits has traditionally been limited by a lack of adequate sensors. Although several nuclear-based analyzers are available, none have seen widespread acceptance. In this investigation, image analysis is used for the on-line determination of ash contents in fine-coal slurries. The ash content of a flotation tailings stream is correlated to the mean gray level of the slurry. Based on a 90% prediction interval, an analysis of sensor performance indicates an accuracy of 73 ± 4% ash over a range of from 65% to 90% ash. While the results are comparable, the video-based system costs only a fraction of what a nuclear-based analyzer costs. The sensor is now installed at the Middle Fork preparation plant, which is owned by Pittston Coal Co.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Adel, G.T., Chandler, M.A., Yoon, R.-H., Gutierrez, E.C., and Richardson, J.N., 1993, “Phosphate analysis by optical image processing: Sensor development and in-plant testing,” Emerging Computer Techniques for the Minerals Industry, B.J. Scheiner, D.A. Stanley and C.L. Karr, eds., SME, Littleton, CO, pp. 185–194.
Adel, G.T., Yoon, R.-H., and Ehrich, R.W., 1988, “Image analysis applications in mineral processing,” Proceedings of the Artificial Intelligence in Minerals and Materials Technology Conference, Tuscaloosa, AL, October 20–21, US Department of Interior, Bureau of Mines, NTIS Report 4-25-88, pp. 19–40.
BioScan Inc., 1991, “OPTIMAS User’s Manual,” 4th ed., Edmonds, WA.
Dunn, P.L., 1996, “Development of a Video-Based Slurry Sensor for On-Line Ash Analysis,” M.S. Thesis, Virginia Polytechnic Institute and State University, Blacksburg, VA, 160 pp.
Gebhardt, J.E., and Ahn, J.H., 1992, “Color measurements of minerals and mineralized froths,” Preprint No. 92–232, 1992 SME Annual Meeting, Phoenix, AZ.
Grove, R.D., Elliot, M.F., and Wiegel, R.L., 1993, “Phosphate process stream composition measurement by an image analysis technique,” Preprint 93–130, SME Annual Meeting, Reno, NV.
Kawatra, S.K., 1993, “The theory and development of a Michigan Tech/Outokumpu slurry ash analyzer,” Emerging Computer Techniques for the Minerals Industry, B.J. Scheiner, D.A. Stanley and C.L. Karr, eds., SME, Littleton, CO, pp. 259–270.
Meenan, G.F., and Oblad, H.B., 1993, “The development of optical sensors for coal processing applications,” Emerging Computer Techniques for the Minerals Industry, B.J. Scheiner, D.A. Stanley, and C.L. Karr, eds., SME, Littleton, CO, pp. 195–200.
Moolman, D.W., Aldrich, C, and Van Deventer, J.S.J., 1995, “The monitoring of froth surfaces in industrial flotation plants using connectionist image processing techniques,” Minerals Engineering, Vol.8, Nos. 1/2, pp. 23–30.
Moolman, D.W., Aldrich, C., Van Deventer, J.S.J., and Stange, W.W., 1994, “Digital image processing as a tool for on-line monitoring of froth flotation plants,” Minerals Engineering, Vol. 7, No. 9, pp. 1149–1164.
Nelson, M.G., and Oblad, H.B., 1989, “Fiber Optic Detector for Flotation Cell Processing,” US Patent No. 4.797.550, 5 pp.
Oestrich, J.M., Tolley, W.K., and Rice, D.A., 1994, “The development of a color sensor system to measure mineral compositions,” Minerals Engineering, Vol. 8, Nos. 1/2, pp. 3139.
Wills, B.A., 1992, Mineral Processing Technology, Pergamon Press, 5th ed., pp. 685–694.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Dunn, P.L., Cruz, E.B., Luttrell, G.H. et al. Development of a video-based coal slurry ash analyzer. Mining, Metallurgy & Exploration 15, 1–10 (1998). https://doi.org/10.1007/BF03402790
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/BF03402790