Designing a high-frequency power transformer is a complicated task due to its multiple interrelation design procedures, large number of variables, and other relevant factors. Traditional transformer design relies on manual paper work and personal experience, which requires engineering design man-hours and long delivery cycles. In this paper, a developed transformer computer design environment is addressed. It helps engineers to automatically model, simulate, and optimize transformer design using an artificial neural network algorithm and the finite-element method, and delivers a reliable design result. Utilizing the proposed platform, an 8 kW coaxial transformer is successfully designed, tested, and manufactured.Griffith Sciences, School of...
14th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC2010, Chicago, IL, 9-12 May ...
This paper deals with the design, simulation and implementation of the highfrequency transformer for...
The purpose of this research is the evaluation of artificial neural network models in the prediction...
Abstract — Designing a high frequency (HF) power transformer is a complicated task due to its multip...
Transformer design is an important feature to achieve lower cost, lower weight reduced size and bett...
Abstract- A new methodology for designing transformers has previously been developed. This model tak...
Traditionally, magnetic component design has been based on power frequency transform-ers with sinuso...
Abstract. The selection of the winding material in power transformers is an important task, since it...
This paper highlights the transformer design optimization problem. The objective of transformer desi...
Designing power transformers and magnetic components is well recognized as a highly complicated proc...
An efficient, meanwhile simple optimization routine is presented for design of high frequency power ...
Abstract — The aim of the transformer design optimization is to define in detail the dimensions of a...
Switching circuits, operating at high frequencies, have led to considerable reductions in the size o...
The movement towards high density electronics has attached greater significance to high frequency ma...
In this paper, a combined neural network and an evolutionary programming scheme is proposed to impro...
14th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC2010, Chicago, IL, 9-12 May ...
This paper deals with the design, simulation and implementation of the highfrequency transformer for...
The purpose of this research is the evaluation of artificial neural network models in the prediction...
Abstract — Designing a high frequency (HF) power transformer is a complicated task due to its multip...
Transformer design is an important feature to achieve lower cost, lower weight reduced size and bett...
Abstract- A new methodology for designing transformers has previously been developed. This model tak...
Traditionally, magnetic component design has been based on power frequency transform-ers with sinuso...
Abstract. The selection of the winding material in power transformers is an important task, since it...
This paper highlights the transformer design optimization problem. The objective of transformer desi...
Designing power transformers and magnetic components is well recognized as a highly complicated proc...
An efficient, meanwhile simple optimization routine is presented for design of high frequency power ...
Abstract — The aim of the transformer design optimization is to define in detail the dimensions of a...
Switching circuits, operating at high frequencies, have led to considerable reductions in the size o...
The movement towards high density electronics has attached greater significance to high frequency ma...
In this paper, a combined neural network and an evolutionary programming scheme is proposed to impro...
14th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC2010, Chicago, IL, 9-12 May ...
This paper deals with the design, simulation and implementation of the highfrequency transformer for...
The purpose of this research is the evaluation of artificial neural network models in the prediction...