Prediction of induction parameters on toroidal wound cores using neural network

Kucuk, Ilker; Derebasi, Naim

doi:10.1016/j.jmmm.2007.02.135

Prediction of induction parameters on toroidal wound cores using neural network

Atıf İçin Kopyala

Kucuk I., Derebasi N.

JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS, cilt.316, sa.2, 2007 (SCI-Expanded)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 316 Sayı: 2
Basım Tarihi: 2007
Doi Numarası: 10.1016/j.jmmm.2007.02.135
Dergi Adı: JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
Bursa Uludağ Üniversitesi Adresli: Hayır

Özet

This paper presents a new approach based on neural network to predict the induction parameters of the toroidal wound cores. The input parameters were the geometrical dimensions of the toroidal core, frequency and magnetic flux density. A total of 3176 input vector from previously measured 52 varied dimensions and built 27M4 material toroidal samples were available in the training set to a back-propagation feed forward neural network. The sigmoid and hyperbolic tangent transfer functions and full connectivity were used in the hidden layers. The correlation coefficients for the total harmonic distortion and form factor were found to be 0.99 and 0.98, respectively after the network was trained. (C) 2007 Elsevier B.V. All rights reserved.