Modelling of Power Loss in Electrical Steels

• Authors: I. Kucuk , K. Erturk , M. Haciismailoglu , N. Derebasi
• Languages of publication: EN

Abstracts

EN

This paper presents a new artificial neural network approach based on loss separation model to compute power loss on different types of electrical steels. The network was trained by a Levenberg-Marquardt algorithm. The results obtained by using the proposed model were compared with a commonly used conventional model. The comparison has shown that the neural network model is in good agreement with experimental data with respect to the conventional model.

Keywords

EN

75.50.Bb; 84.35.+i

Discipline

• 84.35.+i: Neural networks(for optical neural networks, see 42.79.Ta; see also 07.05.Mh Neural networks, fuzzy logic, artificial intelligence in computers in experimental physics; 87.18.Sn in biological complexity)
• 75.50.Bb: Fe and its alloys

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2008
• Volume: 113
• Issue: 1
• Pages: 147-150

Dates

published

2008-01

received

2007-07-09

Contributors

author

I. Kucuk

• Physics Department, Faculty of Arts and Sciences, Uludag University, Gorukle Campus, 16059 Bursa, Turkey

author

K. Erturk

• Physics Department, Faculty of Arts and Sciences, Uludag University, Gorukle Campus, 16059 Bursa, Turkey

author

M. Haciismailoglu

• Physics Department, Faculty of Arts and Sciences, Uludag University, Gorukle Campus, 16059 Bursa, Turkey

author

N. Derebasi

• Physics Department, Faculty of Arts and Sciences, Uludag University, Gorukle Campus, 16059 Bursa, Turkey

References

• 1. I. Kucuk, N. Derebasi, Physica B, Condens. Matter 372, 260 (2006)
• 2. S. Haykin, A Comprehensive Foundation, Macmillan, New York 1994
• 3. G. Bertotti, IEEE Trans. Magn. 24, 621 (1988)
• 4. N. Tutkun, J. Magn. Magn. Mater. 300, 506 (2006)
• 5. F. Wang, V.K. Devabhaktuni, C. Xi, Q. Zhang, Int. J. RF Microwave Computer-Aided Eng. 9, 216 (1999)

Identifiers

DOI

10.12693/APhysPolA.113.147