Osallistava kasvatus ja opettajankoulutuksen haasteet

Osa kaavioista puuttuu.

Tie tohtoriksi usein arkipäiväistä puurtamista - vailla mystiikkaa

Kirjallisuusarvostelu

Työkaluja esimiehenä kehittymiseksi

Kirjallisuusarvostelu

Autonomian ajan loppupuolen jumaluusopin ylioppilaiden aktiivit kristillis-kansallista paikkaansa jäsentämässä

Kirjallisuusarvostelu

Kirja-arvio

Kirjallisuusarvostelu

Simulating the performance of paper machine control

The topic of this thesis is the simulation of a combination of several control and data assimilation methods, meant to be used for controlling the quality of paper in a paper machine. Paper making is a very complex process and the information obtained from the web is sparse. A paper web scanner can only measure a zig zag path on the web. An assimilation method is needed to process estimates for Machine Direction (MD) and Cross Direction (CD) profiles of the web. Quality control is based on these measurements. There is an increasing need for intelligent methods to assist in data assimilation. The target of this thesis is to study how such intelligent assimilation methods are affecting paper web quality. This work is based on a paper web simulator, which has been developed in the TEKES funded MASI NoTes project. The simulator is a valuable tool in comparing different assimilation methods. The thesis contains the comparison of four different assimilation methods. These data assimilation methods are a first order Bayesian model estimator, an ARMA model based on a higher order Bayesian estimator, a Fourier transform based Kalman filter estimator and a simple block estimator. The last one can be considered to be close to current operational methods. From these methods Bayesian, ARMA and Kalman all seem to have advantages over the commercial one. The Kalman and ARMA estimators seems to be best in overall performance.

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