February 3, 2023
Dissertation Title: Eddy current defect response analysis using sum of Gaussian methods
When: 2/22/2023 10:30AM
Where: https://msstate.webex.com/msstate/j.php?MTID=m4e633a3d3c5cb5e49ca4813dcce3695d
Candidate: James Earnest
Degree: Doctor of Philosophy in Electrical and Computer Engineering
Committee Members: Dr. Robert Moorhead, Dr. John Ball, Dr. Ali Gurbuz, Dr. Mehmet Kurum
Abstract: This dissertation is a study of methods to automatedly detect and produce approximations of eddy current differential coil defect signatures in terms of a summed collection of Gaussian functions (SoG). Datasets consisting of varying material, defect size, inspection frequency, and coil diameter were investigated. Dimensionally reduced representations of the defect responses were obtained utilizing common existing reduction methods and novel enhancements to them utilizing SoG Representations. Efficacy of the SoG enhanced representations were studied utilizing common Machine Learning (ML) interpretable classifier designs with the SoG representations indicating significant improvement of common analysis metrics.