Florian Rötzer

Modeling and Control of Reheating Strategies for Refractory Metals


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ISBN:

978-3-8440-8247-0

Reihe:

Modellierung und Regelung komplexer dynamischer Systeme
Herausgeber: Univ.-Prof. Dr. Andreas Kugi (TU Wien), o. Univ.-Prof. Dr. Kurt Schlacher (JKU Linz) und Prof. Dr.-Ing. Wolfgang Kemmetmüller (TU Wien)
Wien / Linz

Band:

Schlagwörter:

temperature control; reheating processes; refractory metals; chamber furnace; induction heating

Publikationsart:

Dissertation

Sprache:

Englisch

Seiten:

148 Seiten

Abbildungen:

32 Abbildungen

Gewicht:

219 g

Format:

24 x 17 cm

Bindung:

Paperback

Preis:

45,80 € / 57,30 SFr

Erscheinungsdatum:

Oktober 2021

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Zusammenfassung

The production of plates from refractory metals involves several reheating processes that have a critical influence on the quality of the final product. This thesis deals with the application of control engineering methods to two reheating processes in a flat stock production line. The objective in both cases is to save time and energy in the reheating processes, while the quality of the products should not be compromised.

In the first part of the thesis, batch-type chamber furnaces used in a hot rolling plant are considered. Energy saving is achieved by minimizing the residence times for each product that is charged into the furnace. When the product is in the furnace, its temperature cannot be measured. Therefore, a detailed process model of the chamber furnace is derived from first principles and subsequently reduced to a first-order nonlinear system, which is able to capture the time evolution of the discharge temperature of the product with sufficient accuracy. The first-order model is exploited in a learning strategy to improve the estimates of the minimum residence times from one product to the next. Additionally, the products of the plant are assigned to product classes according to their material and surface properties to further improve the estimation results.
Simulation studies are performed with the validated detailed process model and the proposed learning strategy with different product classes. The results show a high accuracy if the product parameters are well known. Uncertainties in the product parameters have a moderate influence on the estimation results that can be mitigated by narrowing the definitions of the product classes. The designed estimator is computationally inexpensive and can be applied to a wide range of similar furnace systems.

The second part of the thesis deals with an induction heating system used in the strip coil production. Thin sheets of refractory metals are reheated along a cutting line to improve the quality of the cutting edges. Flatness defects of the sheet cause fluctuations in the air gap between the inductor and the sheet, which entail strong temperature inhomogeneities. The goal is to bring the temperature along each cutting line above a minimum threshold without unnecessary overheating.
The induction heating problem is formulated as a multiphysics process model, which is subsequently simplified for the controller design. The resulting control-oriented model consists of an advection equation and an equivalent circuit model. Based on the control-oriented model, a cascade controller for the transmitted heating power and a two-degrees-of-freedom temperature controller, comprising a feedforward and a feedback part, are designed to compensate for changes in the mean air gap.
Based on the validated detailed process model, the performance of the designed temperature controller is tested in extensive simulation studies. The results show that the proposed controller performs well for sufficiently homogeneous air gap geometries. The concept allows for further improvements in several directions, depending on the available system inputs and outputs.