| Article |
|---|
| Article name |
DEVELOPMENT AND COMPARISON OF THE REGRESSION MODELS OF GOLD-BEARING MATERIAL SEPARATION USING A CENTRIFUGAL JIGGING MACHINE |
| Authors |
Luchko M.. leading engineer, maxuse@gmail.comFedotov P.. doctor of technical sciences, professor, fedotovpavel @yandex.ruLukyanov N.. candidate of engineering sciences, associate professor, lukyanov.n@gmail.com |
| Bibliographic description |
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| Category |
Earth science |
| DOI |
622.772 |
| DOI |
10.21209/2227-9245-2022-28-1-31-39 |
| Article type |
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| Annotation |
Decreasing ore grades is a common challenge for every gold mining country in the world. Deposits of low-grade and complex ores are increasingly brought into production. These ores are typically treated by hydrometallurgical methods, for example, heap leaching. Meanwhile, the use of cyanide and its alternatives poses a risk for the environment. Thus, the development of gravity methods including jigging in a centrifugal-field is becoming an attractive option of low-grade and complex ore processing.
Two mathematical models have been developed using the regression method to predict grade and recovery characteristics of the products of a centrifugal jigging machine (CJM) with variable process parameters including jig chamber rotational speed, pulsation frequency and vibration amplitude of a movable cone, underscreen-water flow rate. The models are based on the results of the field trials of a pilot centrifugal jigging machine designed by JSC Irgiredmet at existing gold-processing plants.
Mathematical modelling provided a means of the process parameters ranking according to their impact on the separation process. A model has been identified that ensures a more accurate prediction of the separation process variables (metal recovery in concentrate) when the CJM’s adjustable parameters are changed.
The object of the study is the centrifugal jigging method of gold-bearing ore separation.
The scope of the study is mathematical modelling of gold-bearing ore separation using CJM.
The objective of the study is the determination and ranking of the CJM’s process parameters according to their impact on the separation process, identification of a model that ensures a more accurate prediction of the separation process variables.
The methodology of the study involves finding the correlation between gold grade/gold recovery into the separation products and the CJM’s adjustable parameters.
The method of the study is regression analysis
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| Key words |
Keywords: mathematical model, regression analysis, method of least squares, gravity separation, centrifugal jigging machine, gold-bearing material separation, separation process intensification |
| Article information |
Luchko М., Fedotov Р., Lukyanov N. Development and comparison of the regression models of Gold-bearing material separation using a centrifugal jigging machine // Transbaikal State University Journal, 2022, vol. 28, no. 1, pp. 31-39. DOI: 10.21209/2227-9245-2022-28-1-31-39. |
| References |
1. Agabalyan A. Yu. Vestnik Natsionalnogo politehnicheskogo universiteta Armenii. Metallurgiya, materialovedeniye, nedropolzovaniye (Bulletin of the National Polytechnic University of Armenia. Metallurgy, materials science, subsoil use). 2016. No. 2. P. 97–108.
2. Dreyper N., Smit G. Prikladnoy regressionnyy analiz (Applied regression analysis: in 2 books. Book 1). Moscow: Finance and statistics, 1986, 366 p.
3. Korolev I. A., Udovitskiy V. I. Sovremennye tendentsii i innovatsii v nauke i proizvodstve: materialy III mezhdunar. nauch.-prakt. konf. (02‒04 aprelya 2014 g.) (Modern trends and innovations in science and production: Materials of III Intern. scientific-practical. conf. (02–04 April 2014). Mezhdurechensk: Kuzbass State Technical University, 2014, pp. 38–39.
4. Luchko M. S., Fedotov P. K. Innovatsionnye protsessy kompleksnoy pererabotki prirodnogo i tehnogennogo mineralnogo syriya: materialy mezhdunar. konf. «Plaksinskiye chteniya – 2020» (Innovative processes of complex processing of natural and technogenic mineral raw materials: materials of the international. conf. \"Plaksin Readings - 2020\" (September 21-26, 2020)). Apatity: FRC KSC RAS, 2020, р. 250.
5. Pelikh V. V., Salov V. M., Burdonov A. Ye., Lukiyanov N. D. Izvestiya Tomskogo politehnicheskogo universiteta. Inzhiniring gosresursov (Bulletin of the Tomsk Polytechnic University. Engineering of public resources), 2020, vol. 331, no. 2, рр. 139–150.
6. Samylin N. A., Pochinok V. V., Zolotko A. A. Otsadka (Jig). Moscow: Nedra, 1976, 320 p.
7. Strizhova V. V., Krymova Ye. A. Metody vybora regressionnyh modeley (Methods for choosing regression models). Moscow: Computing Center of the Russian Academy of Sciences, 2010, 60 p.
8. Chmykhalova S. V. Gorny informatsionno-analiticheskiy byulleten (Mining information and analytical bulletin), 2018. no. 2, рр. 73–80.
9. Shumilova L. V., Kostikova O. S. Vestnik Zabaykalskogo gosudarstvennogo universiteta (Bulletin of the Transbaikal State University), 2015, no. 5, рр. 46–55.
10. Chanturiya V. A. IMPC 2018. 29th International Mineral Processing Congress (IMPC 2018. 29th International Mineral Processing Congress). Moscow, Russia, 2019, рр. 2–12.
11. Gibson B., Wonyen D. G., Chehreh Chelgani S. Minerals Engineering (Minerals Engineering), 2017, no. 114, рр. 64–73.
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