Enhancing Kappa Number Control in Downflow Lo-Solidstm Digester Using Diagnosis and Modelling

Abstract

In this study, Kappa number prediction and diagnosis in continuous Downflow Lo-Solids T M cooking application is investigated. Gustafson's Kappa number model is applied for the prediction of the blowline Kappa number. New cooking temperature set point is solved iteratively based on the difference between the predicted and target blow-line kappa numbers. The main active variables for the Kappa number are monitored using self-organizing map (SOM). The diagnosis and Kappa control are combined into a fault tolerant system. The data is collected from industrial continuous Downflow Lo-Solids T M cooking digester. Good results were achieved using the proposed approach.

A Review on the Modeling, Control and Diagnostics of Continuous Pulp Digesters

“…Rantanen [95] proposed an iterative control strategy for Kappa number control of the Downflow Lo-Solids digester wherein set points for chemical charge and cooking temperature are iteratively solved by using a mechanistic digester model. Later, Ahvenlampi and Rantanen [96] extended the approach presented in [95] and tested a fault tolerant control strategy with the combination of diagnosis and control of the Kappa number in the continuous cooking plant. The authors used a self-organizing map (SOM) to monitor the process and the information was used to switch on the controller or switch it off.…”