Possibilities to Use New Measurements to Control LD-KG-converter

Measuring from the converter is demanding. On the project financed by Rautaruukki Oyj and TEKES (the Technology Agency of Finland) the aim of the project was to develop the control of the converter during the blow by improving the usability of current measurements and by testing new measurements. Splashing measurement based on image analysis was found out to be good and it was taken into use. Also test experiment with Agellis-measurement showed promising results to measure levels within the converter

Simulation in pulp and paper industry

Abstract Mathematical models and simulation are used in several areas of systems engineering. In research and development they are used in studies of process internal phenomena like flow, mixing, reactions, heat and mass transfer, etc. to gain a thorough understanding of what is really going on inside the process. In product design models are used in defining effects of variables on product quality and amount. In process design, modelling, simulation and optimization methods are nowadays used in studying alternatives for process equipment and connections, to optimize process operation and to find best ways to utilize raw materials and energy. Equipment sizing also utilizes models and simulation. In control engineering, models and simulation are utilized in determining control strategies for the process. Simulation is also an interesting tool for process operation. It is employed in disturbance and alarm analysis, in start-up and shut-down planning, in real time control and optimization and in operator training. This material was written for the Process Simulation Course given to two graduate schools during winter 1996: Graduate School in Chemical Engineering (GSCE) and International Ph.D. Program in Pulp and Paper Science and Technology

Multiple Property Cross Direction Control of Paper Machines

Cross direction (CD) control in sheet-forming process forms a challenging problem with high dimensions. Accounting the interactions between different properties and actuators, the dimensionality increases further and also computational issues arise. We present a multiple property controller feasible to be used especially with imaging measurements that provide high sampling frequency and therefore enable short control interval. The simulation results state the benefits of multiple property CD control over single property control and single property control using full feedforward compensation. The controller presented may also be tuned in automated manner and the results demonstrate the effect of tuning on input saturation

Analysis of formation and floc size on the basis of optical transmittance

Abstract This work focuses on analysis of optical transmittance images, which are captured at the end of the wire section of a pilot paper machine. The first priority is to evaluate the capability to estimate formation and floc size on the basis of optical transmittance and secondly analyse how process conditions affect them. Basis weight is one of the most important quality parameters in paper manufacturing. Optical transmittance seems to provide information about basis weight. Reliable evaluation of basis weight on the basis of image data would probably mean a new level of CD and MD profile controls. Formation means small-scale basis weight variation. Good formation e.g. improves the tensile strength and printability of produced paper. Camera unit located above and light source under the paper web at the end of the wire section to capture transmittance images, which were used to calculate several image features. Process and laboratory data were combined with image features for data based analysis. An increase in the basis weight, ash content and the dryness of the paper web seem to reduce the value of optical transmittance. On-line measured image features of optical transmittance were rather congruent with off-line defined reference values, especially the illumination corrected standard deviation of optical transmittance, which is connected to paper formation. Increased flow of headbox and lower consistency of pulp seemed to cause better formation as fewer flocs are formed. However, on the basis of analysis it is difficult to determine process conditions which provide with good formation and small floc size, because of the numerous interactions of process variables, the basis weight varied during experiments and it was difficult to keep other variables except the studied one constant

State detection in the biological water treatment process

Abstract This study introduces a theoretical bioprocess of ideally stirred Chemostat. Chemostat models give an insight to real-life bioprocess systems, in particular biological water treatment. The studied process is very nonlinear due to inhibition of desired reactions by high substrate concentration. The aim of this study is to demonstrate the possibilities of modelling and state detection of this system. This report gives some basic knowledge about bioprocesses and reviews the latest work done for modelling and control of biological waste water treatment. Data-based modelling and state detection are studied thoroughly. Also a couple of control designs are proposed. The theoretical bioprocess is described by a set of differential equations. Steady-state and dynamic models were both derived from the differential equations. The steady-state model was used to obtain knowledge about system's behaviour and the dynamic model to generate data for data-based modelling. The dynamic model was also used in testing of developed models and control designs. Two separate operating points were identified from the data and first order models were identified for both operating points. Based on the knowledge from the steady-state model and data analysis a rulebase was defined. The rulebase and operating point models were integrated to form a Takagi-Sugeno-type fuzzy process model. Testing with the dynamic model showed that the developed fuzzy model performed well. The fuzzy model with slight changes was also used in state detection with good results. Two control designs were developed. One utilizes the recycling of the process output back to the reactor while the other is based on the developed process model. The prior control design is of feedback type and the latter is of feed-forward type. Both control designs performed well while tested with the dynamic process model