Integrated high-frequency coaxial transformer design platform using artificial neural network optimization and FEM simulation
Author(s)
Li, Jeffrey
Water, Wayne
Zhu, Boyuan
Lu, Junwei
Griffith University Author(s)
Year published
2015
Metadata
Show full item recordAbstract
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 ...
View more >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.
View less >
View more >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.
View less >
Journal Title
IEEE Transactions on Magnetics
Volume
51
Issue
3
Subject
Physical sciences
Other physical sciences not elsewhere classified
Engineering