MONITORING OF HIGHLY HEATED MATERIAL FLOW FOR INCREASING RELIABILITY AND QUALITY OF PRODUCTION CONTROL SYSTEMS IN METALLURGY

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1 International Carpathian Control Conference ICCC 2002 MALENOVICE, CZECH REPUBLIC May 27-30, 2002 MONITORING OF HIGHLY HEATED MATERIAL FLOW FOR INCREASING RELIABILITY AND QUALITY OF PRODUCTION CONTROL SYSTEMS IN METALLURGY Milan HEGER 1 and Jiří FRANZ 2 1 Department of Control Systems and Instrumentation, VSB - Technical University of Ostrava, Ostrava, Czech Republic, milan.heger@vsb.cz 2 AutoCont CZ a.s. Ostrava, Czech Republic, jiri.franz.@autocont.cz Abstract: The paper deals with possibilities of monitoring manufacturing hall and photos scanned processing with objective to identify chosen technological entities and indicate their position in time. Algorithmes that exploites sensitive colour and shape discrimination enable entity allocation to selected groups. The algorithmes can be supplied with artificial intelligence elements. Key words: scene analyses, colour discrimination, object identification. 1 Introduction The reliability of many technological processes largely depends on correct data about machine operations being just in process and about the flow of processed material. In Metallurgy, these data are many times influenced by human factor. However, nowadays state-of-the-art makes possible to acquire data on time and more precisely. Beside standard measuring techniques, non-traditional methods can come very well into play. Digital scene analysis is one of them. The monitoring of time more-dimensional motion path of casting mould at steelworks is one of the domains, where the digital scene anylysis for acquiring data from technological process could be used. The paper concentrates on metallurgical area because it is a part of GAČR assignment No. 106/02/0086, but the results can be easily applied to another area of use. 341

2 2 Monitoring of ladle movement with molten steel at steelworks Control systems at steelworks dispose of movement ladle s evidence and single melts system within the framework of steelworks and sequent services. Other data needed for production, dispatch and maintenance are recorded in this way except for immediate placement of object under monitoring. But time entries in production are many times charged with human factor errors while optimal supervision and reliability of many technological processes depend to a certain extent just on precise time data of manufactured material flow. However nowadays camera technology enables effectively acquire data directly from workplaces, whereby the accuracy of time data may be highly increased by objectification, respectively scene analysis. For digital scene analysis at steelworks a system of digital record devices may be used which can be a digital camera or camera which is able to transfer scenes to a computer at request. We can identify chosen technological objects by evaluating a graphic record and define their position in time. As a result we can monitor time three-dimensional path of ladles at steelworks. The exploitation of colour analysis seems to be highly effective for selection of suspicious obejcts. Subsequently, shape identification of known ladle pictures after space adjustment may follow. The centre of identified object with utilization of three-dimensional geometric calculation may be exactly localized and the demands on definition of position are not as high as on robot tasks, scene analyses and so on. It is usually enough when the start and end times of single technological operations and transports are defined with a certain accuracy. 2.1 Colour Analysis on Scene For subject insertion to selected groups based on colour tone the computer program was created which exploits synoptical colour discrimination. Various colour models can be used for colour expression. RGB (red, green, blue) model is the most common one where other colours are made out of tyrkysová (0,1,1) zelená (0,1,0) combination.of the three colours. The colour information in this model can be expressed by a cube, which is placed in the outset of R, G and B axis. The principle of the model G 342 modrá (0,0,1) B černá (0,0,0) bílá (1,1,1) žlutá (1,1,0) Figure 1. RGB model fialová (1,0,1) červená (1,0,0) R

3 demonstrates fig. No. 1 [SOCHOR, J, ŽÁRA, J., BENEŠ, B. 1996]. It is an aditive model, in which the intensity of colours are counted up and by that means new shades of colours are created. Because of true computer interpretation, the magnitude of single components, which is in the interval <0,1>, is transfered as a standard into interval (1 Byte) so that it is possible to acquire over 16 millions shades of colour. This model is technically oriented and is suitable for monitors. Human experience with colour assembling comes from blending colour pigments and for that purpose a subtract colour model CMY (cyan, magenta, black) is more suitable. It can be used for drawing and printing, respectively. The models mentioned above are tightly connected to a particular device and that is their great disadvantage. Because of the disadvanage, new models, which are more userfriendly, were created. The new systems HSV and HLS (hue, saturation, value-brightness) jas - V G (120 o ) Y (60 o ) C (180 o ) R (0 o ) B (240 o ) M (300 o ) barva - H sytost - H Figure 2. HSV model. also consist of three colour components. The colour information for this model can be expressed by a six-wall pyramid and is demonstrated in fig.no. 2 [SOCHOR, J, ŽÁRA, J., BENEŠ, B. 1996]. The colour tone H identifies the predominant spectral colour and is an angle data in the interval <0,360 >. Saturation S identifies an admixture of other colours and is demonstrated as a point distance from a pyramid axle. Its value may be in the interval <0,1>. Value (brightness) V is represented by white (colourless) light, it increases in the direction of the pyramid base and its value lies in the interval <0,1>. The pyramid base centre represents white colour. HSV and HLS models enable to change colour features gradually, while other typical colour features stay preserved. That is the reason, why this model is more tabular and userfriendly. 343

4 Because majority of nowadays scanning apparatus utilize colour information with exploitation of RGB model, it is recommended for colour selection purpose to transfer taken scenes with assistence of suitable subroutine to HSV or HLS system. This can be done with computer program that has been created in Delphi language. Thus, the picture record taken by a digital camera is transfered to HSV system. The computer program enables to set colour parameters of the object under supervision that means tone magnitude, saturation and brightness. According to the set of values, the computer program picks out those colour objects which accomplish preset conditions. Screen copy of computer program with scanned picture of regular colour objects is illustrated in fig.no. 3. Segment of monitored scene is copied to a small picture on the left. In this case part of colour palette from orange, red and magenta to blue in various saturation Figure 3. Output screen for determination given colours by HSV model 344

5 and brightness. The preset elements H, S and V are used for presetting colour tone, saturation and brightness. The value H can be set for higher variability in the range of 100 to 360, values S and V in percentage from 0 to 100%. In upper right-hand picture, the result of the operatiuon is displayed with found objects cut out. The found objects are contrastly displayed in the lower right-hand picture, which is better for further machine processing. In this case the computer program chose those red objects, which fully satisfied preset criteria. H lies in interval <-4,9>, S in <96;100> and V in <35,74>. If the expected movement path of ladle at steelworks is known, from picture scene it is possible to define where the examined object is and define its exact time. The example of display of inquired colour objects at simplified steelworks model is in fig. No.4. From various objects such as convertor, crane and rail traffic and station for steel modification those objects are chosen whose colour correspond with colour of molten steel in the ladle. Figure 4. Output screen with the result of displayed searched colour objects at simplified steelwork model. 345

6 2.2 Shape object identification For verification of inquired object is suitable to verify the shape of the object and rule out possible unwanted objects. At steelworks it may be tipped ladle, cast trunk, flames of burner and so on. These objects will have different shape or size compared to the object under investigation. Most powerful criterion is impossibility of such an object in the identified place. The task of shape verification of the found objects is greatly simplified by an unique shape of sought object. It will be generally an ellipse in case of ladle with molten steel, whose parameters will be function of its aspect in space. In this case, it is possible to compare computed ellipse axis with displayed ellipse in a certain spot of space. Thus, the object which were identified by colour identification can be rule out because they do not fit with expected parameters of ellipse in given place based on geometric computation. 3 Conclusion The presented method was developed for movement observing of molten steel in ladle but it can be easily applied to another area of use where the colour plays the decisive roll for object identification in space. Identification of objects of various colour is possible by automatic change of computer program parameters. The elements of artificial intelligence may be used for consistent shape identification (e.i. in cases when part of the identified object is hidden). References VROŽINA, M., ET. AL Systémy pro algoritmizaci rozhodovacích procesů při řízení plynulého odlévání oceli. Zpráva GAČR 106/96/K032. Ostrava, SKALA,V Světlo, barvy a barevné systémy v počítačové grafice. Academia Praha 1993 HORNÝ,S Počítačová grafika-teorie a praxe. VŠE SOCHOR, J, ŽÁRA, J., BENEŠ, B Alogoritmy počítačové grafiky. ČVUT JANČÍKOVÁ, Z., HEGER, M., VROŽINA, M., KOBĚRSKÝ, J. & DAVID, J Neuronové sítě a jejich možnosti využití v metalurgii. Sborník konference Proceedings of International Scientific Conference of FME. VŠB-TU Ostrava : Ostrava, ISBN JANČÍKOVÁ Z., HEGER M Exploitation of artificial intelligence elements for steel thermal treatment modeling. Sborník přednášek mezinárodní konference Process Control 99, Tatrianské Matliare, HEGER, M., DAVID, J Neuronek program pro výuku neuronových sítí. In Sborník semináře XXVI. ASŘ 2001 Instrumets and Control, Ostrava : 2001, ISBN VROŽINA, M., OVČÁČÍKOVÁ, R., DAVID, J., HEGER, M., JANČÍKOVÁ, Z Podpora operativního řízení na ocelárnách využitím expertního systému. In Sborník konference Inteligentní systémy pro praxi, AD&M., Ostrava : 2001, str