Phenomenological Based Soft Sensor for Online Estimation of Slurry Rheological Properties
This work proposes a soft sensor based on a phenomenological model for online estimation of the density and viscosity of a slurry flowing through a pipe-and-fittings assembly (PFA). The model is developed considering the conservation principle applied to mass and momentum transfer and considering frictional energy losses to include the variables directly affecting slurry properties. A reported proposal for state observers with unknown inputs is used to develop the first block of the observer structure. The second block is constructed with two options for evaluating slurry viscosity, generating two possible estimator structures, which are tested using real data. A comparison between them indicates different uses and capabilities according to available process information.
KeywordsSoft sensor phenomenological based semi-physical model non-Newtonian fluids unknown input observer slurry flow
Unable to display preview. Download preview PDF.
The authors thank Colciencias and SUMICOL (Suministros de Colombia S.A.) for their support and financing for this project.
- M. C. Bourne. Texture, viscosity, and food. Food Texture and Viscosity: Concept and Measurement, 2nd ed., M. C. Bourne, Ed., London, UK: Academic Press, pp. 1–32, 2002. DOI: 10.1016/B978-012119062-0/50001-2.Google Scholar
- R. J. Oglesby, H. J. Moynihan, R. B. Santos, A. Ghosh, P. W. Hart. Does kraft hardwood and softwood pulp viscosity correlate to paper properties? Tappi Journal, vol. 15, no. 10, pp. 643–651, 2016.Google Scholar
- S. Taborda, D. A. Muñoz, H. Alvarez. Snowball effect detection and control proposal for its correction. In Proceedings of IEEE Conference on Control Applications, IEEE, Buenos Aires, Argentina, pp. 1173–1178, 2016. DOI: 10.1109/CCA.2016.7587965.Google Scholar
- M. C. Bourne. Viscosity measurement. Food Texture and Viscosity, 2nd ed., M. C. Bourne, Ed., London, UK: Academic Press, pp. 235–256, 2002. DOI: 10.1016/B978-012119062-0/50006-1.Google Scholar
- R. P. Chhabra, J. F. Richardson. Rheometry for non-Newtonian fluids. Non-Newtonian Flow and Applied Rheology: Engineering Applications, 2nd ed., R. P. Chhabra, J. F. Richardson, Eds., Oxford, UK: Butterworth-Heinemann, pp. 56–109, 2008. DOI: 10.1016/B978-0-7506-8532-0.00002-0.Google Scholar
- K. M. Hangos, I. T. Cameron. Process Modelling and Model Analysis, San Diego, USA: Academic Press, 2001.Google Scholar
- R. B. Bird. Transport Phenomena, Sterling Heights, USA: Wiley, 2007.Google Scholar
- R. Darby. Chemical Engineering Fluid Mechanics, 2nd ed., New York, USA: Marcel Dekker, 2001.Google Scholar
- D. Muñoz, J. L. Diaz, S. Taborda, H. Alvarez. Hydrocyclone phenomenological-based model and feasible operation region. International Journal of Mining, Materials, and Mechanical Engineering, vol. 3, pp. 1–9, 2017.Google Scholar
- K. J. Astrom, B. Wittenmark, Computer-controlled Systems: Theory and Design, 3rd ed., Berlin, Germany: Prentice Hall, 1997.Google Scholar
- H. Alvarez, R. Lamanna, P. Vega, S. Revollar. Methodology for obtaining phenomenological based semiphysical models applied to a sugar cane juice tower. Iberoamericana Journal of Automation and Industrial Information, vol. 6, no. 3, pp. 117–122, 2009.Google Scholar
- D. Castañeda, J. Lorena. The Use of Phenomenological Based Semi-physical Models as Virtual Sensors for Density and Viscosity of Mineral Slurries, Master dissertation, Facultad de Minas, Universidad Nacional de Colombia, Colombia, 2017.Google Scholar
- W. B. Hooper. The two-K method predicts head losses in pipe fittings. Chemical Engineering, vol. 88, pp. 96–100, 1981.Google Scholar
- G. F. Aguilera. Mineral slurry viscosity simulation using neural networks, Master dissertation, Facultad de Minas, Universidad Nacional de Colombia, Colombia, 2005. [Online], Available: https://doi.org/intranet.minas.medellin.unal.edu.co/index.php?option=com_docman&taskdoc_download&gid986&Itemid285 Google Scholar
- D. A. Muñoz, C. J. L. Diaz, H. Alvarez. Unknown input observer to estimate slurry rheological properties. In Proceedings of the 3rd Colombian Conference on Automatic Control, IEEE, Cartagena, Colombia, 2017. DOI: 10.1109/CCAC.2017.8276418.Google Scholar