journal article·2018-05-23Open access

Control strategies for refiners Part I: Soft sensors for CD-refiner control

Anders Karlström, Jan Hill

Abstract

Abstract Internal variables in (C)TMP-refining processes (e. g. temperature, consistency, fiber residence time, backward flowing steam and forces acting upon the chips and pulp) are defined as physical states obtained in different parts of the refining zones. In short, they differ from the traditional external variables (e. g. dilution water feed rate and specific energy) which are not obtained from measurements or physical models of the process in the refining zone. The internal variables are the backbone of physical models and are used in this paper as soft sensors for advanced process control. Besides the shape of the temperature profile, the position of the maximum temperature and the shape of the consistency profiles inside the refining zones are important to control as they are directly linked to the development of different pulp and handsheet properties. To illustrate the capability when using combined modeling and control strategies, the concept is applied on a full scale CD82 refiner. This means both temperature and consistency control in the flat zone and the conical zone, together with an overall estimator for fiber development. Finally, in this paper it is shown that the production can be increased significantly without changing the refiner motor load nor violating the pulp property specification.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Heat Transfer and Numerical Methods · Induction Heating and Inverter Technology · Metallurgical Processes and Thermodynamics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Chalmers University of Technology , Göteborg , Sweden

QualTech AB , Tyringe , Sweden

References (38)

Show source-provided references
1. Berg, D. (2005): A Comprehensive Approach to Modeling and Control of Thermomechanical Pulping Processes, Lic thesis. Dept. of Signals and Systems, Chalmers.
2. Bird, R. B., Stewart, W. R. and Lightfoot, E. N. (1960): Transport phenomena, John Wiley and Sons Inc., New York.
3. Dahlqvist G. and Ferrari B. (1981): Mill operating experience with a TMP refiner control system based on a true disc clearance measurement, In: Int. Mech. Pulping Conf., Oslo, Norway, Session III, no. 6.
4. Eriksson, K. (2005): An Entropy-based Modeling Approach to Internally Interconnected TMP Refining Processes, Licentiate thesis, Chalmers University of Technology, Göteborg, Sweden. ISSN 1403-266x; nr R034/2005.
5. Eriksson, K. (2009): Towards improved control of TMP refining processes, PhD thesis, Chalmers University of Technology, Göteborg, Sweden.
6. Hägglund, T., (1999): Automatic detection of sluggish control loops, Control Eng. Pract. 13:1383–1390.10.1016/j.conengprac.2004.12.006 ↗
7. Hill, J., Saarinen, K., Stenros, R. (1993): On the control of chip refining systems, Pulp Pap. Can. 94(6):43–47.
8. Hill, J., Westin, H., and Bergström, R. (1979): Monitoring pulp quality for process control, In: Int. Mech. Pulping Conf., Toronto, Canada, p. 111–125.
9. Honkasalo, J. V., Pölkkynen, E. E., Vainio,J. A., (1989): Development of control systems in mechanical pulping (GW, TMP) at Rauma, In: Int. Mech. Pulping Conf., Helsinki, Finland, p. 376–389.
10. Horch, A., (1999): A simple method for detection of stiction in process control loops, Control Eng. Pract. 7(10):1221–1231.10.1016/S0967-0661(99)00100-810.1016/S0967-0661(99)00100-8 ↗
11. Isaksson, A. J., Horch, A., Karlström, A., Allison, B. J., Nilsson, L. (1997): Modelling of mechanical thrust in TMP refiners, Prceedings, In: Int. Mech. Pulping Conf, SPCI, Stckhm., p. 87–93.
12. Johansson B.-L., Karlsson H. and Jung, E., (1980): Experiences with computer control, based on optical sensors for pulp quality, of a two-stage TMP-plant, In: 1980 Process Control Conf., Halifax, Nova Scotia, p. 145–152.
13. Karlström, A., (2013): Multi-scale modeling in TMP-processes, In: 8th Int. Fundamental Mech. Pulp Res. Seminar, Åre, Mid Sweden Univrersity, Sundsvall, Sweden.
14. Karlström, A., Berg, D. and Eriksson, K. (2005): Developments in soft sensors for measurement of refining parameters, In: Scientific and technical advances in refining and mechanical pulping, Barcelona, Spain, 28 Feb.–4 Mar. 2005, Pira International, Leatherhead, UK, Paper 5.
15. Karlström, A. and Eriksson, K. (2014a): Fiber energy efficiency Part I: Extended entropy model. Nord. Pulp Pap. Res. J. 29(2):322–329.10.3183/npprj-2014-29-02-p322-33110.3183/npprj-2014-29-02-p322-331 ↗
16. Karlström, A. and Eriksson, K. (2014b): Fiber energy efficiency Part II: Forces acting on the refiner bars. Nord. Pulp Pap. Res. J. 29(2):332–343.10.3183/npprj-2014-29-02-p332-34310.3183/npprj-2014-29-02-p332-343 ↗
17. Karlström, A. and Eriksson, K. (2014c): Fiber energy efficiency Part III: Modeling of fiber-to-bar interaction. Nord. Pulp Pap. Res. J. 29(3):401–408.10.3183/npprj-2014-29-03-p401-40810.3183/npprj-2014-29-03-p401-408 ↗
18. Karlström, A. and Eriksson, K. (2014d): Fiber energy efficiency Part IV: Multi-scale modeling of refining processes. Nord. Pulp Pap. Res. J. 29(3):409–417.10.3183/npprj-2014-29-03-p409-41710.3183/npprj-2014-29-03-p409-417 ↗
19. Karlström, A., Eriksson, K. and Hill J. (2015b): Refiner Optimization and Control Part IV: Long term follow up of control performance in TMP processes. Nord. Pulp Pap. Res. J. 30(3):426–435.10.3183/npprj-2015-30-03-p426-43510.3183/npprj-2015-30-03-p426-435 ↗
20. Karlström, A., Eriksson, K., Sikter, D. and Gustavsson, M. (2008): Refining models for control purposes, Nord. Pulp Pap. Res. J. 23(1):129.10.3183/npprj-2008-23-01-p129-13810.3183/npprj-2008-23-01-p129-138 ↗
21. Karlström, A. and Hill J. (2014a): Refiner Optimization and Control Part I: Fiber residence time and major dynamic fluctuations in TMP refining processes. Nord. Pulp Pap. Res. J. 29(4):635–652.10.3183/npprj-2014-29-04-p635-65210.3183/npprj-2014-29-04-p635-652 ↗
22. Karlström, A. and Hill J. (2014b): Refiner Optimization and Control Part II: Test procedures for describing dynamics in TMP refining processes. Nord. Pulp Pap. Res. J. 29(4):653–662.10.3183/npprj-2014-29-04-p653-66210.3183/npprj-2014-29-04-p653-662 ↗
23. Karlström, A. and Hill J. (2015a): Refiner Optimization and Control Part III: Natural decoupling in TMP refining processes. Nord. Pulp Pap. Res. J. 30(3):417–425.10.3183/npprj-2015-30-03-p417-42510.3183/npprj-2015-30-03-p417-425 ↗
24. Karlström A., Hill J. (2017a): CTMP process optimization Part I: Internal and external variables impact on refiner conditions. Nord. Pulp Pap. Res. J.. 32(1):35–44.10.3183/npprj-2017-32-01-p035-04410.3183/npprj-2017-32-01-p035-044 ↗
25. Karlström A., Hill J. (2017b): CTMP Process Optimization Part II: Reliability in Pulp and Handsheet Measurements. Nord. Pulp Pap. Res. J. 32(2):253–264.10.3183/npprj-2017-32-02-p253-26510.3183/npprj-2017-32-02-p253-265 ↗
26. Karlström A., Hill J. (2017c): CTMP Process Optimization Part III: On the Predicition of Scott-Bond, Z-strength and Tensile index, Nord. Pulp Pap. Res. J. 32(2:266–279).10.3183/npprj-2017-32-02-p266-27910.3183/npprj-2017-32-02-p266-279 ↗
27. Karlström, A., Hill J., Ferritsius, R. and Ferritsius, O. (2015): Pulp Property Development Part I: Interlacing Undersampled Pulp Properties and TMP Process Data using Piece-wise Linear Functions. Nord. Pulp Pap. Res. J. 30(4):599–608.10.3183/npprj-2015-30-04-p599-60810.3183/npprj-2015-30-04-p599-608 ↗
28. Karlström, A., Hill J., Ferritsius, R. and Ferritsius, O. (2016a): Pulp Property Development Part II: Process Nonlinearities and its Influence on Pulp Property Development. Nord. Pulp Pap. Res. J. 31(2):287–299.10.3183/npprj-2016-31-02-p287-29910.3183/npprj-2016-31-02-p287-299 ↗
29. Karlström, A., Hill J., Ferritsius, R. and Ferritsius, O. (2016b): Pulp Property Development Part III: Fiber Residence Time and Consistency Profile Impact on Specific Energy and Pulp Properties. Nord. Pulp Pap. Res. J. 31(2):300–307.10.3183/npprj-2016-31-02-p300-30710.3183/npprj-2016-31-02-p300-307 ↗
30. Karlström, A., and Isaksson, A. (2009): Multi-rate optimal control of TMP refining processes, In: Int. Mech. Pulping Conf., Sundsvall, Sweden.
31. Lehtonen S., Virtanen P., Lindeberg M. and Fralic G. A. (2014): New TMP optimization approach: using advanced quality control to stabilize tensile strength and reduce power cost. In: International Mechanical Pulping Conference, Helsinki, Finland.
32. Lowe, G. K., Zohdy, M. A. (2010): Modeling nonlinear systems using multiple piecewise linear equations, Nonlinear Anal., Model. Control 15(4):451–458.10.15388/NA.15.4.14317 ↗
33. Miles, K. B. and May, W. D. (1990): The Flow of Pulp in Chip Refiners, J. Pulp Pap. Sci. 16(2):63.
34. Miles, K. B. and May, W. D. (1991): Predicting the performance of a chip refiner: A constitutive approach, Proceedings, In: Int. Mech. Pulping Conf. Tappi, Atlanta, pp. 295–301.
35. Oksum J., (1983): New technology in the Skogn mechanical pulp mill, Proceedings, In: Int. Mech. Pulping Conf., Tappi, Atlanta, USA, pp. 143–153.
36. Sabourin, M., Wiseman, N. and Vaughn, J. (2001): Refining theory considerations for assessing pulp properties in the commercial manufacture of TMP. In: 55th Appita Annual Conference, Appita, Macled, Vic, Austraia, pp. 95–204.
37. Strand, B. C. (1996): Model based control of high consistency refining, Tappi J. 79(10):140–146.
38. Strand, B. C and Grace, B. (2014): Implementation of advanced supervisory control within a TMP refiner quality control system, In: International Mechanical Pulping Conference, Helsinki, Finland.