Research Article
Experimental Evaluation of Magnetostrictive Strain of Electrical Steel
@INPROCEEDINGS{10.1007/978-3-030-12950-7_11, author={Ant\^{o}nio Vieira and Jo\"{a}o Esp\^{\i}rito Santo and Cristiano Coutinho and S\^{e}rgio Tavares and Marta Pinto and Cassiano Linhares and H\^{e}lder Mendes}, title={Experimental Evaluation of Magnetostrictive Strain of Electrical Steel}, proceedings={Green Energy and Networking. 5th EAI International Conference, GreeNets 2018, Guimar\"{a}es, Portugal, November 21--23, 2018, Proceedings}, proceedings_a={GREENETS}, year={2019}, month={2}, keywords={Magnetostriction Epstein frame Power transformer Noise}, doi={10.1007/978-3-030-12950-7_11} }- António Vieira
João Espírito Santo
Cristiano Coutinho
Sérgio Tavares
Marta Pinto
Cassiano Linhares
Hélder Mendes
Year: 2019
Experimental Evaluation of Magnetostrictive Strain of Electrical Steel
GREENETS
Springer
DOI: 10.1007/978-3-030-12950-7_11
Abstract
Environmental noise pollution has gained increasing importance, over the past few years. Due to population growth along with a rapid urbanization and the increasing power supply needs, more and more electrical power transformers are set near or inside of urban agglomerations. This fact has generated several complaints regarding the noise produced by this equipment, forcing manufacturers to develop low noise solutions. As it is known, magnetostriction is one of the main sources of electrical machines noise. This research presents an experimental study in which magnetostriction properties of electrical steel are evaluated and analyzed. The magnetic flux density influence on the hysteretic strain behavior of magnetostriction was addressed, as well as the effect of a clamping load on the core joints. This study was addressed by means of an Epstein frame and a data acquisition system, where strain, current and voltage data is obtained and then processed in a data logging software. These measurements gave essential inputs for numerical models which simulate the power transformer core behavior, allowing a faster evaluation of noise mitigation solutions.
