Kerr electro-optic measurements for electric field and space charge distributions using similar and dissimilar electrode pairs
Author(s)
Nowocin, John Kendall
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Markus Zahn.
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The electrical breakdown strength of insulating materials is a major limiting factor of reliability in electric power, medical devices, and other high electric field applications. Electrical breakdown strength increase results in increased reliability and energy storage in high voltage capacitors and other devices. If a correlation can be found between the breakdown strength and the electric field distribution when a voltage is applied without electrical breakdown, then this may be a critical step toward non-destructive electrical breakdown tests. The generation and transport of space charge in high voltage stressed dielectric liquids are not well understood or controlled. Electric field distributions, distorted by space charge, cannot be calculated from knowledge of the electrode configuration, dielectric properties, and source excitation alone. In this work, the Kerr effect, an electro-optic method based on field-induced birefringence, is used to measure the electric field and space charge distributions between a pair of high voltage stressed identical or different metal electrodes. The non-uniformities in the electric field can then be mapped to determine the shape of space charge distortion of the electric field distribution for each electrode pair configuration. A large well monitored Kerr cell was built to replace a previously used small Kerr cell, and incorporated many improvements to the systems measurement accuracy and repeatability. The electrode pairs were combinations of similar and dissimilar metals. The similar electrode pairs provided double checks of the testing process with the voltage polarity reversed. Software was written to automate the testing process and collect data for processing. Pre and post processing code was written to determine statistics for data analysis.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013. Cataloged from PDF version of thesis. Includes bibliographical references (p. 97).
Date issued
2013Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.