Artificial Neural Network to the Control of the Parameters of the Heat Treatment Process of Casting

• Autorzy: Wróbel J. , Kulawik A. , Bokota A.

Identyfikatory

DOI

10.1515/afe-2015-0022

• Języki publikacji: EN

Abstrakty

EN

In the paper the use of the artificial neural network to the control of the work of heat treating equipment for the long axisymmetric steel elements with variable diameters is presented. It is assumed that the velocity of the heat source is modified in the process and is in real time updated according to the current diameter. The measurement of the diameter is performed at a constant distance from the heat source (Δz = 0). The main task of the model is control the assumed values of temperature at constant parameters of the heat source such as radius and power. Therefore the parameter of the process controlled by the artificial neural network is the velocity of the heat source. The input data of the network are the values of temperature and the radius of the heated element. The learning, testing and validation sets were determined by using the equation of steady heat transfer process with a convective term. To verify the possibilities of the presented algorithm, based on the solve of the unsteady heat conduction with finite element method, a numerical simulation is performed. The calculations confirm the effectiveness of use of the presented solution, in order to obtain for example the constant depth of the heat affected zone for the geometrically variable hardened axisymmetric objects.

Słowa kluczowe

EN

heat treatment; moving heat source; artificial neural network; numerical modelling; control system; heating process

PL

obróbka cieplna; źródło ciepła ruchome; sztuczna sieć neuronowa; modelowanie numeryczne; system sterowania; proces nagrzewania

• Wydawca: Komisja Odlewnictwa Polskiej Akademii Nauk Oddział w Katowicach
• Czasopismo: Archives of Foundry Engineering
• Rocznik: 2015
• Tom: Vol. 15, iss. 1
• Strony: 119--124
• Opis fizyczny: Bibliogr. 9 poz., rys., wykr.

Twórcy

autor

Wróbel J.

• Institute of Computer and Information Sciences, Częstochowa University of Technology, Dąbrowskiego 73, 42-200 Częstochowa, Poland

autor

Kulawik A.

• Institute of Computer and Information Sciences, Częstochowa University of Technology, Dąbrowskiego 73, 42-200 Częstochowa, Poland

autor

Bokota A.

• Institute of Computer and Information Sciences, Częstochowa University of Technology, Dąbrowskiego 73, 42-200 Częstochowa, Poland

Bibliografia

• [1] Canale, L.C.F., Mesquita, R.A., Totten, G.E. (2008). Failure Analysis of Heat Treated Steel Components. United States of America: ASM International.
• [2] Totten, G.E. (2006). Steel Heat Treatment: Equipment and Process Design. United States of America: CRC Press.
• [3] Rutkowski, L. (2005). Computational Intelligence: Methods and Techniques. Berlin: Springer.
• [4] Yegnanarayana, B. (2006). Artificial neural networks. New Delhi: Prentice-Hall of India Learning.
• [5] Bokota, A. (2012). Modelling of hardening tool steels. Thermal phenomena, phase transformations, mechanical phenomena. Częstochowa: Wydawnictwo Politechniki Czestochowskiej.
• [6] Wait, R., Mitchell, A.R. (1985). Finite Element Analysis and Applications. Chichester: John Wiley & Sons.
• [7] Zienkiewicz, O.C., Taylor, R.L. (2000). The finite element method. Butterworth-Heinemann: Oxword.
• [8] Mochnacki, B., Nowak, A., Pocica, A. (2002). Numerical model of superficial layer heat treatment using the TIG method. In K. Świątkowski (Eds.), Polska metalurgia w latach 1998-200, Tom 2 (pp. 229-235). Kraków: WN Akapit.
• [9] Kulawik, A. (2012). Modeling of thermomechnical phenomena of welding process of steel pipe. Archives of Metallurgy and Materials. 57(4), 1229-1238.