Crystallizer’s Desks Surface Diagnostics with Usage of Robotic System

Abstract

Discussed problems are solved in Arcelor Mittal Ostrava a.s. company. VSB-TU Ostrava has its share on this solution in the frame of grant project TIP. The project has several goals, which relate with primary cooling system area in CSCD (Continuous Steel Casting Device). One target is concerned about surface quality of crystallizer's desks, also from point of view of its quality evaluation.in terms of project solution was solved a crystallizer's desks defects catalogue and methodology of their evaluation. Also was made methodology for quality evaluation of narrow crystallizer's desks, which are dismantled in maintenance area. There were proposed a laser scanning of the crystallizer's desks surface with usage of Laser sensor. In cooperation with DASFOS CZ, s.r.o. was proposed new method of inner crystallizer's chamber measuring. In this paper are presented partial results of this solution, including first results from prototyped measuring device.Keywords: steel, casting, crystallizer, quality, laserOmawiany problem został rozwiązany przez firmę Arcelor Mittal Ostrava. VSB-TV Ostrava posiada swój udział w tym rozwiązaniu będący wynikiem realizacji projektu TIPFR-TI1/319 finansowanego częściowo przez Ministerstwo Handlu i Przemysłu Republiki Czech. Projekt skupia się na kilku celach związanych z maszyną COS (ciągłego odlewania stali). Jeden z celów projektu dotyczy jakości powierzchni płyt krystalizatora z punktu widzenia oceny tej jakości. W rezultacie powstał katalog wad płyt krystalizatora wraz z metodologią ich oceny. Zaproponowana została metoda oceny jakości wąskich płyt krystalizatora zdemontowanych na czas konserwacji. Zaproponowano skanowanie powierzchni płyt krystalizatora z wykorzystaniem czujnika laserowego. We współpracy z DASFOC CZ. S.r.o. została zaproponowana nowa metoda pomiaru wewnętrznej przestrzeni krystalizatora. W pracy przedstawiono wybrane wyniki tego rozwiązania wraz z wstępnymi wynikami uzyskanymi przy pomocy prototypowego urządzenia pomiarowego.

Austempered Ductile Iron Manufacturing Data Acquisition Process with the Use of Semantic Techniques

“…The data collected and the conclusions drawn can be used in the design of technological process, but they can equally well serve the task of building intelligent systems, as has already been demonstrated in previous works of the authors using rough set theory [12] and the logic of plausible reasoning [13] and others related with diagnostics [14] or [15].…”

Methodology for the Construction of a Rule-Based Knowledge Base Enabling the Selection of Appropriate Bronze Heat Treatment Parameters Using Rough Sets

“…Based on the obtained rules, an error-free classification of appropriate variant of heat treatment parameters to achieve the required properties of bronze can be made. The problem of classification, although known in the industrial issues [10,11], is sensitive to the type, number and characteristics of the learning data. It should be noted, however, that testing proceeded in the space of results based on the stored measurement data.…”

Comparative analysis of the properties of the nodular cast iron with carbides and the austempered ductile iron with use of the machine learning and the support vector machine

“…The reasoning models based on one of logic knowledge representationslogic of plausible reasoning-were widely described in [23,24]. An artificial intelligence was successfully applied in the systems of pattern recognition and diagnostics-an important domain of industry processes [25][26][27].…”