- -

Metodología híbrida para la estimación del nivel de llenado en un molino de bolas

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

  • Estadisticas de Uso

Metodología híbrida para la estimación del nivel de llenado en un molino de bolas

Show full item record

Da Cunha E Silva, LC.; Andrade Romero, JF. (2022). Metodología híbrida para la estimación del nivel de llenado en un molino de bolas. Revista Iberoamericana de Automática e Informática industrial. 19(2):210-220. https://doi.org/10.4995/riai.2021.13064

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/182826

Files in this item

Item Metadata

Title: Metodología híbrida para la estimación del nivel de llenado en un molino de bolas
Secondary Title: Hybrid methodology for filling level estimation in ball mill
Author: da Cunha e Silva, Luiz Carlos Andrade Romero, Jesus Franklin
Issued date:
Abstract:
[EN] This work presents a hybrid modeling methodology based on dynamic response, filtering and identification techniques, in order to determine a ball mill representative model. In essence, we have provided models for ...[+]


[ES] Este trabajo presenta una metodología híbrida de modelado basada en técnicas de respuesta dinámica, filtrado e identificación, considerando el dominio del tiempo y la frecuencia, para determinar el modelo representativo ...[+]
Subjects: System identification and parameter estimation , Mining , Hybrid systems modeling , Monitoring and supervision , Identificación de sistemas y estimación de parámetros , Minería , Modelado de sistemas híbridos , Monitorización y supervisión
Copyrigths: Reconocimiento - No comercial - Compartir igual (by-nc-sa)
Source:
Revista Iberoamericana de Automática e Informática industrial. (issn: 1697-7912 ) (eissn: 1697-7920 )
DOI: 10.4995/riai.2021.13064
Publisher:
Universitat Politècnica de València
Publisher version: https://doi.org/10.4995/riai.2021.13064
Type: Artículo

References

Castaldi, P., Tilli, A., 2005. Parameter estimation of induction motor at standstill with magnetic flux monitoring. IEEE Transactions on Control Systems Technology, v. 13, n. 3, p. 386-400. https://doi.org/10.1109/TCST.2004.841643

Dai, W., Zhou, P., Zhao, D., Lu, S. and Chai, T., 2016. Hardware-in-the-loop simulation platform for supervisory control of mineral grinding process. Powder technology, 288, pp.422-434. https://doi.org/10.1016/j.powtec.2015.11.032

Dell'Aquila, A., Gilibert, V., Lovecchio, F.S, Salvatore, L., 1994. Real-Time Estimation of Induction Motor Parameters by LSE. Proceedings of IECON'94 - 20th Annual Conference of IEEE Industrial Electronics. [+]
Castaldi, P., Tilli, A., 2005. Parameter estimation of induction motor at standstill with magnetic flux monitoring. IEEE Transactions on Control Systems Technology, v. 13, n. 3, p. 386-400. https://doi.org/10.1109/TCST.2004.841643

Dai, W., Zhou, P., Zhao, D., Lu, S. and Chai, T., 2016. Hardware-in-the-loop simulation platform for supervisory control of mineral grinding process. Powder technology, 288, pp.422-434. https://doi.org/10.1016/j.powtec.2015.11.032

Dell'Aquila, A., Gilibert, V., Lovecchio, F.S, Salvatore, L., 1994. Real-Time Estimation of Induction Motor Parameters by LSE. Proceedings of IECON'94 - 20th Annual Conference of IEEE Industrial Electronics.

Eremenko, Y.I., Poleshchenko, D.A., Glushchenko, A.I., 2015. About Ball Mill Fill Level Monitoring System Development and Research on Its Efficiency. In: 2015 International Siberian Conference on Control and Communications (SIBCON), Omsk, p. 1- 4. https://doi.org/10.1109/SIBCON.2015.7147324

Esteves, P. M., Stopa, M. M., Filho, B. J. C., Galery, R., 2015. Charge Behavior Analysis in Ball Mill by Using Estimated Torque. IEEE Transactions on Industry Applications, v. 51, n. 3. https://doi.org/10.1109/TIA.2014.2377372

Franchi, C. M, 2009. Inversores de Frequência - teoria e aplicação. 2ed. Érica: São Paulo.

Fleury, A. W., 2007. Estudo Comparativo de Técnicas de Estimativa do Fluxo Estatórico de MIT. Dissertação (mestrado). Pós-Graduação em Engenharia Elétrica. Universidade Federal de Uberlândia

Fuerstenau, D.W., Phatak, P.B., Kapur, P.C. and Abouzeid, A.Z., 2011. Simulation of the grinding of coarse/fine (heterogeneous) systems in a ball mill. International Journal of Mineral Processing, 99(1-4), pp.32-38. https://doi.org/10.1016/j.minpro.2011.02.003

Garnier, H., Young, P., 2004. Time-domain approaches to continuous-time model identification of dynamical systems from sampled data. Proceedings of the 2004 American Control Conference. https://doi.org/10.23919/ACC.2004.1383680

Holtz, J., Quan, J., 2003. Drift-and Parameter-Compensated Flux Estimator for Persistent Zero-Stator-Frequency Operation of Sensorless-Controlled Induction Motor. IEEE Transactions on Industry Aplications, v. 39, n. 4. https://doi.org/10.1109/TIA.2003.813726

Johansson, R., 1993. System Modeling and Identification. Prentice Hall: NJ.

Kang, E. S., Guo, Y. G., Du, Y. Y., Zhao, L. H., 2006. Acoustic vibration signal processing and analysis in ball mill. In: 6th World Congress on Intelligent Control and Automation, Dalian, China, p. 6690 - 6693.

King, R. P., 2001. Modeling and simulation of mineral processing systems. 1.ed. Department of Metallurgical Engineering, University of Utah, USA: Butterworth-Heinemann. Great Britain.

Khamehchi, S., 2018. Identification of the Induction Motor Parameters at Standstill Including the Magnetic Saturation Characteristics. Dissertação (Mestrado). Aalto University. School of Electrical Engineering. Department of Electrical Engineering and Automation.

Lee, S. H., Yoo, A., Lee, H. J., Yoon, Y. D, Han, B. M., 2017. Identification of induction motor parameters at standstill based on integral calculation. IEEE Transactions on Industry Applications, v. 53, n. 3, p. 2130-2139. https://doi.org/10.1109/TIA.2017.2650141

Leonhard, W. (2001). Control of Electrical Drives. 3ed. Spring Verlag. https://doi.org/10.1007/978-3-642-56649-3

Liu, Z., Chai, T., Yu, W., Tang, J., 2015. Multi-frequency Signal Modeling using Empirical Mode Decomposition and PCA with Application to Mill Load Estimation. Neurocomputing: Elsevier. https://doi.org/10.1016/j.neucom.2014.08.087

Luz, A. B., Sampaio, J. A., França, S. C. A., 2010. Tratamento de Minérios. 5ª ed. CETEM/MCT. Rio de Janeiro.

Melero, M. G., Cano, J. M., Norniella, J., Pedrayes, F., Cabanas, M. F., 2014. Electric motors monitoring: An alternative to increase the efficiency of ball mills. In: International Conference on Renewable Energies and Power Quality (ICREPQ'14). Cordoba (Spain). https://doi.org/10.24084/repqj12.509

Mihalache, L., 2005. A Flux Estimator for Induction Motor Drives Based on Digital EMF Integration With Pré and Post High Pass Filtering. IEEE Apllied Electronics Conference and Exposition, p. 713-718, v.2.

Nikander, J., 2009. Induction Motor Parameter Identification in Elevator Drive Modernization. Master of Science in Technology. Helsinki University of Technology. Faculty of Electronics, Communications and Automation.

Peng, H., Minping, J., Binglin, Z., 2010. New Method to Measure the Fill Level of the Ball Mill I - Theoretical Analysis and DEM Simulation. Chinese Journal of Mechanical Engineering, v.23, n.3, p.1-8. https://doi.org/10.3901/CJME.2010.04.460

Ranta, M., 2013. Dynamic induction machine models including magnetic saturation and iron losses. Tese de Doutorado. Aalto University, School of Electrical Engineering, Department of Electrical Engineering.

Sena, A. P. C., 2011. Estratégia para Estimação do conjugado eletromagnético de motores de indução. Dissertação de mestrado. Centro de Tecnologia. Programa de Pós-Graduação em Engenharia Mecânica. Universidade Federal da Paraíba, João Pessoa.

Severino, P.B., 2005. Um Estudo de Estimativa de Fluxo e Conjugado em Motores de Indução Trifásicos - implementação utilizando DSP. Dissertação (mestrado). Pós-Graduação em Engenharia Elétrica. Universidade Federal de Uberlândia.

Seyoum, D., Grantham, C., Rahman, M. F., 2003. Simplified Flux Estimation for Control Application in Induction Machines. In: Electric Machines and Drives Conference, 2003. IEMDC'03. IEEE International, v.2, p. 691-695.

Shen, G., Wang, K., Yao, W., Lee, K., Lu, Z., 2013. DC biased stimulation method for induction motor parameters identification at standstill without inverter nonlinearity compensation. In: 2013 IEEE Energy Conversion Congress and Exposition, p. 5123-5130. https://doi.org/10.1109/ECCE.2013.6647393

Shin, M. H., Hyun, D. S., Cho, S. B., Choe, S. Y., 2000. An Improved Stator Flux Estimation for Speed Sensorless Stator Orientation Control of Induction Motor. IEEE Transactions on Power Eletronics, v. 15, Isse: 2, p. 312-318. https://doi.org/10.1109/63.838104

Tang, J., Zhao, L. J., Zhou, J. W., Yue, H., Chai, T. Y., 2010a. Experimental analysis of wet mill load based on vibration signals of laboratory-scale ball mill shell. Minerals Engineering, n.23, p.720-730: Elsevier. https://doi.org/10.1016/j.mineng.2010.05.001

Tang, J., Yu, W., Zhao, L., Yue, H., Chai, T., 2010b. Modeling of Operating Parameters for Wet Ball Mill by Modified GA-KPLS. In: 3th International Workshop on Advanced Computational Intelligence. August 25-27, p.282 287. Suzhou, Jiangsu, China. https://doi.org/10.1109/IWACI.2010.5585151

Tie, M., Bi, J. and Fan, Y., 2007, June. Hybrid intelligent modeling approach for the ball mill grinding process. In International Symposium on Neural Networks (pp. 609-617). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72383-7_72

Umans, S.D., 2014. Electric machinery. McGrew-Hill Series in Electrical Engineering.

Wang, H., Jia, M. P., Huang, P., Chen, Z. L., 2009. A study on a new algorithm to optimize ball mill system based on modeling and GA. Energy Conversion and Management, n.51, p.846-850: Elsevier. https://doi.org/10.1016/j.enconman.2009.11.020

Wang, K., Yao, W., Chen, B., Shen, G., Lee, K., Lu, Z., 2015. Magnetizing curve identification for induction motors at standstill without assumption of analytical curve functions. IEEE Transactions on Industrial Electronics, v. 62, n. 4, p. 2144-2155. https://doi.org/10.1109/TIE.2014.2354012

Zerbo, M., Sicard, P. and Ba-Razzouk, A., 2005, May. Accurate adaptive integration algorithms for induction machine drive over a wide speed range. In IEEE International Conference on Electric Machines and Drives, 2005. (pp. 1082-1088). IEEE. https://doi.org/10.1109/IEMDC.2005.195856

Zhao, L., Tang, J., Yu, W., Yue, H., Chai, T., 2010. Modeling of Mill Load for Wet Ball Mill via GA and SVM Based on Spectral Feature. IEEE, p.874-879. https://doi.org/10.1109/BICTA.2010.5645241

Zhao, L., Feng, X., Yuan, D., 2012. Soft Sensor Modeling of Mill Load Based on Feature Selection Using Synergy Interval PLS. Journal of Theoretical and Applied Information technology.

Zhao, L., Tang, J., Zheng, W., 2012. Ensemble Modeling of Mill Load Based on Empirical Mode Decomposition and Partial Least Squares. Journal of Theoretical and Applied Information Technology, v.45, n.1, p. 179-191.

[-]

recommendations

 

This item appears in the following Collection(s)

Show full item record