Difference between revisions of "Projects:2016s1-121 Measurement of Transformer Parameters"

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This report is a part of continuing project. The aim of this project is to create a semi-automated method for estimating of the transformer parameters. In this project we use self-resonant frequency to get the best frequency. In addition, we use 1-port device and 2-port device. In order to test some of our calculations, we will disassemble some transformers. We can obtain absolute measurements of the numbers of turns, and core-dimensions. Obviously, we will combine a variety of measurements, with some mathematical methods, to estimate the parameters of transformers. One important method is, Least Square Spectral Analysis (LSSA). If the transformer is operating in a non-linear mode, under conditions of high current, for example the resulting distortion will produce higher-order components in the Fourier series, which can be estimated using a modification of the LSSA method. Previous work has shown that Transmission-Parameters lead to a simple formulation of our problem.
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This project is identifying a semi-automated method to perform best estimate of transformer parameters. The aim of the project is to use two-port network model to estimate the parameters for any transformer model using transmission parameters with less variable. The obtained data are analysed and compared with the corresponding values in different methods. It starts from an ideal and simplified transformer models, which applies one-port network on the transformer to be tested. The method of least squares is applied to obtain the best estimate input variables The optimization techniques, Lagrange Multiplier is also applied to minimise any discrepancy between the observed behaviour of a transformer and the predicted behaviour of the model. Analysis of non-linearity effects on transformer is the rest part of the project which involves identifying the characteristics in terms of magnetic field and current.

Revision as of 13:51, 26 October 2016

topic

Measurement of Transformer Parameters

Student Name

Chen Qiao Rahel Bekele Megersa

Supervisors

Dr. Andrew Alison Dr. Rastko Zivanovic

Summary

This project is identifying a semi-automated method to perform best estimate of transformer parameters. The aim of the project is to use two-port network model to estimate the parameters for any transformer model using transmission parameters with less variable. The obtained data are analysed and compared with the corresponding values in different methods. It starts from an ideal and simplified transformer models, which applies one-port network on the transformer to be tested. The method of least squares is applied to obtain the best estimate input variables The optimization techniques, Lagrange Multiplier is also applied to minimise any discrepancy between the observed behaviour of a transformer and the predicted behaviour of the model. Analysis of non-linearity effects on transformer is the rest part of the project which involves identifying the characteristics in terms of magnetic field and current.

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