Paper
24 May 2013 Optical-electronic system for express analysis of mineral raw materials dressability by color sorting method
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Abstract
Due to the depletion of solid minerals ore reserves and the involvement in the production of the poor and refractory ores a process of continuous appreciation of minerals is going. In present time at the market of enrichment equipment are well represented optical sorters of various firms. All these sorters are essentially different from each other by parameters of productivity, classes of particles sizes for processed raw, nuances of decision algorithm, as well as by color model (RGB, YUV, HSB, etc.) chosen to describe the color of separating mineral samples. At the same time there is no dressability estimation method for mineral raw materials without direct semi-industrial test on the existing type of optical sorter, as well as there is no equipment realizing mentioned dressability estimation method. It should also be note the lack of criteria for choosing of one or another manufacturer (or type) of optical sorter. A direct consequence of this situation is the "opacity" of the color sorting method and the rejection of its potential customers. The proposed solution of mentioned problems is to develop the dressability estimation method, and to create an optical-electronic system for express analysis of mineral raw materials dressability by color sorting method. This paper has the description of structure organization and operating principles of experimental model optical-electronic system for express analysis of mineral raw material. Also in this work are represented comparison results of the proposed optical-electronic system and the real color sorter.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Artem A. Alekhin, Elena V. Gorbunova, Aleksandr N. Chertov, and Darya B. Petuhova "Optical-electronic system for express analysis of mineral raw materials dressability by color sorting method", Proc. SPIE 8791, Videometrics, Range Imaging, and Applications XII; and Automated Visual Inspection, 87911N (24 May 2013); https://doi.org/10.1117/12.2020460
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Cited by 6 scholarly publications.
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KEYWORDS
Minerals

Raw materials

RGB color model

Statistical analysis

Image processing

Light sources

Optics manufacturing

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