Mold level control of a continuous casting plant by switching control strategies

Thomas Ernst Passenbrunner

Research output: ThesisMaster's / Diploma thesis

Abstract

Although the technique of casting has been in use for many hundred years, a dramatic reduction of the costs to produce steel was only possible through a variety of developments especially in the 19th and 20th century. Only since the fifties of the last century steel is cast by continuous casting plants. Afore it was usual to cast the molten steel via ingots. Nowadays steel is used in virtually all industries starting by the automotive industry through to the machine and plant engineering to the production of sheet steel. This results in the claim to operate the plant at a high casting speed to achieve a corresponding productivity. However, dynamic bulging and mold level hunting bring to bear even when operating at high casting speeds. One speaks about dynamic bulging, if there is a variation of the magnitudes of the bulges between consecutive rolls due to the ferrostatic pressure within the strand. These variations also lead to fluctuations of the heigth of molten steel in the mold. A high quality of the final product must be ensured on the other hand. The aim of this thesis is to increase the performance of continuous casting plants. A point to start for achieving this goal are switching control strategies. In further consequence the averaged motor current signal of the electric motors actively driving the strand serves as a basis for decision, to activate which mode. The development and conception of these strategies is not possible on real plants or on the on the institute available simulator. Two simplified models have been developed at the beginning of this work: The first model structure describes the averaged motor current. It is about one model of fourth order for each of the three casting speeds. The second structure represents the commutated and lowpass filtered averaged motor current signal. These models form the basis for the development of appropriate switching laws.
Original languageEnglish
Publication statusPublished - Jun 2009

Fields of science

  • 202 Electrical Engineering, Electronics, Information Engineering
  • 202027 Mechatronics
  • 202034 Control engineering
  • 203027 Internal combustion engines
  • 206001 Biomedical engineering
  • 206002 Electro-medical engineering
  • 207109 Pollutant emission

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