Model based Control and Diagnostics strategies for a Continuous Pulp Digester

Authors: Moksadur Rahman, Anders Avelin, Konstantinos Kyprianidis, J.Jansson and Erik Dahlquist. (Mälardalen University, Västeras, Sweden)

Conference: Papercon 2018 in Charlotte, USA (15-18 April)

Abstract: Kappa number, which essentially indicates the amount of lignin left in the pulp after cooking, is the most important physical quantity linked to the quality and economics of a Kraft-pulp mill. Controlling the Kappa number is a difficult task mainly due to the naturally varying feedstock, significant residence time, insufficient measurements and complex nature of the delignification process. Moreover, faults such as screen clogging, hang-ups and channeling in the process often occur and increase the operational costs considerably. In this work, the possibility of feedforwarding the lignin content of incoming wood chips, by a near-infrared spectroscopic measurement of one of the major process disturbances, to a model predictive controller, is investigated by means of modeling and simulation studies. Additionally, a simple Bayesian network based diagnostics approach is proposed to detect the continuous digester faults.

Key words: Pulp and paper, Kraft pulping, soft-sensores, near infrared spectroscopy, pulp digester model, feedforward model predictive control.

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