Use of combined physical and statistical models for online applications in the pulp and paper industry

• This paper discusses the accuracy of different types of models. Statistical models are based on process data and/or observations from lab measurements. This class of models are called black box models. Physical models use physical relationships to describe a process. These are called white box models or first principle models. The third group is sometimes called grey box models, being a combination of black box and white box models. Here we discuss two examples of model types. One is a statistical model where an artificial neural network is used to predict NOx in the exhaust gases from a boiler at Mlarenergi AB in Vsters, Sweden. The second example is a grey box model of a continuous digester. The digester model includes mass balances, energy balances, chemical reactions and physical geometrical constraints to simulate the real digester. We also propose that a more sophisticated model is not required to increase the accuracy of the predicted measurements.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Energiteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Energy Engineering (hsv//eng)

Nyckelord

statistical models; physical models; pulp digester

Energy- and Environmental Engineering

energi- och miljöteknik

Publikations- och innehållstyp

ref (ämneskategori)

art (ämneskategori)