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Pulp quality estimation using the soft sensor concept
After reading this article you will..
- understand the principles of building and using software sensors in pulp refiner environment.
Process control and automation
- Introduction to process control and automation
- Development of process automation
- Fibre process automation
- Chemical recovery as a control object
- Advances in paper machine automation
- Paper machine as a dynamical system
- Tasks in paper machine control and management
- Control of stock flow concentration and quality
- Machine direction control
- Cross-directional control – The static optimisation
- Cross-directional control – Dynamics
- Cross-directional control – further aspects
- Controlling functional paper properties
- Managing grade chances in the paper machine
- Managing disturbances caused by broke and recovered solids
- Millwide systems
- Modelling and control methods
Authors & references
Authors:
Anders Karlström, Chalmers University of Technology
References:
- Bengtsson, F., Karlström, A., Hill, J. and Johansson, L. 2019. Refining models for optimization and control – How to use such models for pulp and handsheet properties estimation. 11th Fundamental Mechanical Pulp Research Seminar, Norrköping.
- Lowe, G.K. and Zohdy, M.A. 2010. Modeling nonlinear systems using multiple piecewise linear equations. Nonlinear Analysis: Modelling and Control, 15(4):451–458.
- Karlström A. and Hill J. 2017. CTMP Process Optimization Part II: Reliability in Pulp and Handsheet Measurements. Nordic Pulp & Paper Research Journal 32(2):253–265.
- Karlström A. and Hill J. 2017. CTMP Process Optimization Part III: On the Prediction of Scott-Bond, Z-strength and Tensile index. Nordic Pulp & Paper Research Journal 32(2):266–279.
- Ljung, L., 1999. System identification, Theory for the user, Prentice Hall, New Jersey, USA.
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This page has been updated 05.11.2021