Title :
Finding steady-state temperature field of an electrical coil by using cellular neural network
Author :
Krstic, Ivan ; Reljin, Branimir
Author_Institution :
Fed. Inst. for Standardization, Belgrade, Yugoslavia
Abstract :
Finding steady-state operating temperature of electrical coils, which are the constitutive parts of a number of electric devices (transformers, generators, motors etc.) is very important problem in engineer´s every day practice. At the same time this problem belongs both to the heat transfer theory and the electrical engineering. Fortunately, it can be efficiently solved by using obvious analogy between the constitutive equation describing heat transfer in an electrical coil and the state equations of a cellular neural network (CNN). This method is transparently presented and tested by simple problem consisting of finding the steady-state temperature field over the square cross-section of an electrical coil, aiming to check accuracy of measured maximal temperature in its center. Obtained modeling results agree well with (conditionally) exact solutions and satisfy well requirements of engineer´s and researcher´s practice
Keywords :
cellular neural nets; coils; electrical engineering computing; heat transfer; CNN; cellular neural network; constitutive equation; electrical coil; electrical engineering; generators; heat transfer theory; motors; state equations; steady-state operating temperature; steady-state temperature field; transformers; Cellular neural networks; Coils; Electrical engineering; Equations; Heat engines; Heat transfer; Resistance heating; Steady-state; Temperature measurement; Transformers;
Conference_Titel :
Neural Network Applications in Electrical Engineering, 2000. NEUREL 2000. Proceedings of the 5th Seminar on
Conference_Location :
Belgrade
Print_ISBN :
0-7803-5512-1
DOI :
10.1109/NEUREL.2000.902405