Simulation of hysteresis loops for a superconductor using neural networks with Kalman filtering

• Autorzy: Krok A.
• Konferencja: Polish Conference on Computer Methods in Mechanics (16 ; 21-24.06.2005 ; Częstochowa, Poland
• Języki publikacji: EN

Abstrakty

EN

Kalman filtering is used as a learning method for the training of Feed-forward Layered Neural Networks (FLNN) and Recurrent LNNs (RLNN). These networks were applied to the simulation of hysteresis loops obtained by the experiment on a cable-in-conduit superconductors by the test carried out in a cryogenic press [8]. The training and testing patterns were taken from nine selected, characteristic hysteresis loops. The formulated FLNN: 4-4-5-1 gives the computer simulation of higher accuracy than the standard network FLNN: 4-7-5-1 discussed in [5].

Słowa kluczowe

EN

Kalman filtering; neural network; simulation; conductor; hysteresis loops

PL

sieć neuronowa; symulacja; filtracja Kalmana; przewodnik

• Wydawca: Instytut Podstawowych Problemów Techniki PAN
• Czasopismo: Computer Assisted Mechanics and Engineering Sciences
• Rocznik: 2006
• Tom: Vol. 13, No. 4
• Strony: 575--582
• Opis fizyczny: Bibliogr. 9 poz., rys., tab., wykr.

Twórcy

autor

Krok A.

• Cracow Unwersity of Technology, PhD Course at Faculty of Civil Engineering ul. Warszawska 2A, 31-155 Kraków, Poland

Bibliografia

• [1] U. Galvanetto, V. Naumov, V. Palmov, B.A. Schrefier. Analysis of the mechanical behavior of cable-in-conduit superconductors under transverse cyclic loading. Int. J. Comput. Civ. Struct. Eng, 1(2): 1-10, 2000.
• [2] S. Haykin. Neural Networks, A Comprehensive Foundation, 2nd ed. MacMillan College Publ., Engle-wood Cliffs, NJ, 1999.
• [3] S. Haykin (ed.). Kalman Filtering and Neural Networks. Wiley, New York, 2001.
• [4] A. Krok, Z. Waszczyszyn. Kalman filtering for neural prediction of response spectra from mining tremors. In: T. Burczynski, W. Cholewa, W. Moczulski (eds), Recent Development in Artificial Intelligence Methods, AI METH2001 AI-Meth Series, 157-162, Gliwice, 2004.
• [5] M. Lefik. One-dimensional model of cable-in-conduit supercoductors under cyclic loading using artificial neural networks. In: Fusion Engineering and Design. Elsevier Science Volume, 60/2, 105-117, 2002.
• [6] M. Lefik. Zastosowania sztucznych sieci neuronowych w mechanice i w inżynierii. Zeszyty Nauk. Polit. Łodzkiej, 2005, (in Polish)
• [7] M. Lefik, B.A. Schlefler. Artificial neural networks for parameter identifications for elasto-plastic model of superconductiong cable under cycling loading. Comp. Struct., 80: 1699-1713, 2002.
• [8] A. Nijuhuis, N.H.W. Noordman, H.H.J, ten Kate. Mechanical and Electrical Testing of an ITER CSl Model Coil Conductor under Transverse Loading in a Cryogenic Press. Preliminary Report. Univ. of Twente, March, 1998.
• [9] www.iter.org, official ITER project website.