COMMERCIAL OPERATION EXPERIENCE OF AUTOMATED MONITORING OF FILLING LEVEL IN BALL MILLS

Automated monitoring system development to control a ball mill filling level is considered. Accelerometers installed to both trunnions are used to obtain and estimate indirectly the ball mill state. The data from these sensors are processed by a proposed system on the basis of software and hardware by National Instruments. It is applied in real technological process of ore reduction at JSC Stoilensky GOK to conduct experiments.
The software part of the mentioned system contains a special criterion developed by us to process vibration acceleration signals in order to estimate the ball mill state. This criterion has shown high correlation to technological process parameters values. The most informative frequency range characterizing the mill state is determined. Its bandwidth is 1950–2200 Hz. The speed of and ability to response to external disturbances are chosen as efficiency criteria. Influence of these disturbances can be found in both proposed criterion and current signals of classifier spirals as the main indicator of the ball mill drum filling level for an operator. The proposed monitoring system makes it possible to detect changes in the mill filling level more rapidly (approximately 5–6 min) and with greater sensitivity (approximately 2.5 to 3 times) comparing to the current assessment procedure conducted by the operator. The results of the conducted experiments prove the expediency of the developed method usage.

The study was conducted with financial support of applied scientific research by the Ministry of education and science of the Russian Federation, agreement № 14.575.21.0133 (RFMEFI57517X0133).

Keywords

Mill feeling degree, acceleration gage, spectral analysis, ball mill, vibroacceleration.

Issue number: 12
Year: 2017
ISBN:
UDK: 004.042, 622.73
DOI: 10.25018/0236-1493-2017-12-0-153-160
Authors: Poleshchenko D. A.

About authors: Poleshchenko D.A., Candidate of Technical Sciences, Assistant Professor, e-mail: po-dima@yandex.ru, Stary Oskol Technological Institute named after A.A. Ugarov, National University of Science and Technology «MISiS» branch, 309530, Stary Oskol, Russia.

REFERENCES: 1. Pryadko N. S., Muzyka L. V. Zbagachennya korisnikh kopalin. 2014, issue 58(99)-59(100), 6 p.
2. Jian Tang, Li-jie Zhao, Jun-wu Zhou, Heng Yue, Tian-you Chai. Experimental analysis of wet mill load based on vibration signals of laboratory-scale ball mill shell. Minerals Engineering. Volume 23, Issue 9, August 2010, Pp. 720-730.
3. Andreev S. E. Droblenie, izmel'chenie i grokhochenie poleznykh iskopaemykh (Crushing, grin-
ding and screening of minerals), Moscow, Nedra, 1980, 320 p.
4. Alekseev M. A. Naukoviy vіsnik NGU. 2014, no 4, pp. 13-19.
5. Sibirtseva N. B., Potapenko A. N., Semiletov N. A. Izvestiya Samarskogo nauchnogo tsentra Rossiyskoy akademii nauk. 2010. t. 12, no 4(3), pp. 694-697.
6. Ulitenko K. Ya., Markin R. P., Sokolov I. V. Gornyy zhurnal. 2009, no 10, pp. 72-76.
7. Leonov R. E. Izvestiya vuzov. Gornyy zhurnal. 2012, no 3, pp. 111-113.
8. Jian Tang, Tianyou Chaia, Lijie Zhaoa, etc. Soft sensor for parameters of mill load based on multi-spectral segments PLS sub-models and on-line adaptive weighted fusion algorithm. Neurocomputing. 2012. No.78. Pp. 38-47.
9. Gugel K., Moon R. M. Automated mill control using vibration signal processing. IEEE Cement Industry Technical Conference, 2007. Pp. 17-25.
10. Gugel K., Palcios G., Ramirez J., Parra M. Improving ball mill control with modern tools based on digital signal processing technology. IEEE Cement Industry Technical Conference. Dallas, United States. 2003. Pp. 311-318.
11. Yukio Sato. Bez paniki! Tsifrovaya obrabotka signalov. Per. s yap. T. G. Selinoy (No need to panic! Digital signal processing. Japan-Russian translation Selina T. G.), Moscow, Dodeka-XXI, 2010, 176 p.
12. Pozharskiy Yu. M., Poleshchenko D. A., Podkovyrov I. Yu. Gornyy zhurnal. 2013, no 2, pp. 115-118.
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