Науковий вісник НГУ

Ulpa particle separation model in a spiral classifier

• 
• 

User Rating:  / 0

PoorBest 

Details

Category: Content №1 2020

Last Updated on 09 April 2020

Published on 10 March 2020

Hits: 3032

Authors:

O.S.Beshta, Corr. Member of the NAS of Ukraine, Dr. Sc. (Tech.), Prof., orcid.org/0000-0002-4648-0260, Dnipro University of Technology, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

V.M.Kuvaiev, Dr. Sc. (Tech.), Prof., orcid.org/0000-0001-6329-071X, Dnipro University of Technology, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

I.K.Mladetskyi, Dr. Sc. (Tech.), Prof., orcid.org/0000-0002-6159-6819, Dnipro University of Technology, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

M.V.Kuvaiev, Cand. Sc. (Tech.), orcid.org/0000-0002-8560-5433, Dnipro University of Technology, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2020, (1):31-35
https://doi.org/10.33271/nvngu/2020-1/031

 повний текст / full article

Abstract:

Purpose. Development of a model that describes the relationship of parameters characterizing the operating mode of the spiral classifier with the particle size distribution of the ore product in the classifier discharge to increase the efficiency and accuracy of controlling the process of enrichment of iron ore raw materials.

Methodology. Theoretical studies were based on classical models of separation of the classified material and justification of the parameter, characterizing the granulometric composition of the classified material in the classifier discharge, which can be calculated in the framework of the general theoretical model with subsequent control calculations. Methods of analysis, synthesis, systematisation and generalisation, and mathematical model method were used.

Findings. Dependencies are obtained that make it possible to calculate the parameter characterizing the particle size distribution of the product in the spiral classifier discharge by the observed parameters of the enrichment process of the classified product.

Originality. For the first time, a model for the separation of classified material in spiral classifiers is substantiated and the influence of the temperature of the separation medium on the classification process is shown.

Practical value. The results can be used to automatically stabilize the particle size distribution of the product in the discharge of the spiral classifier.

References.

1. The mechanical, rack and pinion and spiral classifier(n.d.). InHandbook of a chemist 21. Chemistry and chemical technology. Retrieved from https://chem21.info/info/1373505/.

2. Mining and processing of iron ore. Information and technical reference on the best available ITS technologies 25-2017 (2017). Moscow: Bureu NTD. Retrieved from https://files.stroyinf.ru/Data2/1/4293740/4293740351.pdf.

3. Matsui, A. M., Kondratets, V. O., & Abashyna, A. A. (2019). System analysis of the operation of a mechanical single-spiral classifier as an object of control. Visnyk Kryvorizkoho Natsionalnoho Universytetu, (48), 8-13.

4.Beybutov, S. B. (2016). Ore grinding process control system. Sovremennye materialy. Tekhnika i tekhnologii, (5), 20-27.

5. AO “Soyuztsvetmetavtomatika” (n.d.). Devices and systems of technological control. Retrieved from http://www.scma.ru/ru/products/2.html.

6. Ulitenko, K. Ya., Sokolov, I. V., Markin, R. P., & Naydenov, A. P. (n.d.). Automation of grinding processes in enrichment and metallurgy. 1-10. Retrieved from https://docplayer.ru/55449268-Avtomatizaciya-processov-izmelcheniya-v-obogashchenii-i-metallurgii.html.

7. Matsui, A. M. (2018) Theoretical study of the identification of the weighted average size of unloading of a ball mill and sand of the spiral classifier. Hirnychyi Visnyk Kryvorizkoho Natsionalnoho Universytetu, (103), 197-203

8. Mladetskyi, I. K., Kuvaiev, Ya. H., & Priadko, N. S. (2019). Control regularities of the useful mineral extraction from ore feed stream with autogenous grinding. Spectral analysis. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (3), 129-137. https://doi.org/10.29202/nvngu/2019-3/17.

9. Markovsky, I. (2015). An application of system identification in metrology. Control Engineering Practice, (43), 85-93.

10. Stoev, J., & Schoukens, J. (2016). Nonlinear system identification – application for industrial hydro-static drive-line. Control Engineering Practice, (54), 154-165.

11. Salikhov, Z. G., & Ginsberg, K. S. (2016). The study of evolution in the field of identification of mathematical models of metallurgical processes in the creation of real automatic control systems. Tsvetnye metally, 11, 105-112.

12. Bublikov, A., & Tkachov, V. (2019). Automation of the control process of the mining machines based on fuzzy logic. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (3), 112-118. https://doi.org/10.29202/nvngu/2019-3/19.

13. Kuvaiev, V.M., & Beshta, D.O. (2017). Dynamic model of interaction of mechanisms on the section between the roll mill stand and the coiler in the process of wire winding by garret reel. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, (4), 61-66.

14. Tekhnomash(n.d.). Spiral classifiers for ore pulps. Retrieved from http://technomach.com.ua/solutions/mechanical-engineering/#1511203723621-fb2a4de3-143c.

• < Prev
• Next >