Identification of Potential Superconductor Quench Precursors Using Frequency Domain Feature Analysis
Publication Date
2025
Document Type
Dissertation/Thesis
First Advisor
Fonseca, Benedito
Degree Name
M.S. (Master of Science)
Legacy Department
Department of Electrical Engineering
Abstract
Superconducting magnets are important pieces of technology in the world of particle accelerators, allowing researchers to study atomic and subatomic phenomena, among other things. In some instances, superconductors can lose this non-resistive property in a phenomenon known as quenching, which can cause damage to the magnets. This potential danger prompts the introduction of systems to predict when a quench is imminent; one such implementation is through the use of acoustic sensors that detect vibrations within the magnet. Within these acoustic sensor signals, significantly above-noise disturbances (referred to as ”events”) can be identified. Our research applies the statistical framework of a permutation test to features calculated from the power spectral density (PSD) to distinguish between events far from the quench at the end of the signal to events at the start of the signal. We found that dividing the PSD into frequency bands produced a feature capable of distinguishing between events early in the signal and late in the signal leading up to the quench, providing a promising starting place for future quench prediction systems.
Recommended Citation
Roehrig, Benjamin C., "Identification of Potential Superconductor Quench Precursors Using Frequency Domain Feature Analysis" (2025). Graduate Research Theses & Dissertations. 8085.
https://huskiecommons.lib.niu.edu/allgraduate-thesesdissertations/8085
Extent
45 pages
Language
en
Publisher
Northern Illinois University
Rights Statement
In Copyright
Rights Statement 2
NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.
Media Type
Text
