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Eddy Current #2

Tracks
Room 411/412
Friday, June 28, 2024
10:00 AM - 11:40 AM
411-412

Overview

Chairs: Jiming Song & Yuan Ji


Speaker

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Prof. Jiming Song
Professor
Iowa State University

Application of Machine Learning for Model-Assisted Probability of Detection in Eddy Current Non-destructive Testing Systems

Paper or Abstract

Biography

Jiming Song received the Ph.D. in electrical engineering from Michigan State University and was the principal author of Fast Illinois Solver Code. Now he is a professor in Electrical Engineering, Iowa State University, Ames, Iowa. He has co-edited one book and published seven book chapters, 104 journal papers and 186 conference papers. Dr. Song received the NSF Career Award in 2006. He was selected as a National Research Council/Air Force Summer Faculty Fellow in 2004 and 2005. Dr. Song is an IEEE Fellow and ACES Fellow and an associate editor for Research in Nondestructive Evaluation (RNDE), Nondestructive Testing and Evaluation.
Kyle Rose
Student
Iowa State University CNDE

Applicability of Published Eddy Current Experimentation for Digital Twinning in Industry 4.0.

Paper or Abstract

Biography

Kyle Rose is a PhD student in Electrical Engineering at Iowa State University (ISU) as a Science Mathematics and Research for Transformation (SMART) Retention Scholar for the US Army Combat Capabilities Development Command Armaments Center (DEVCOM-AC) Evaluation Methodologies Laboratory. Kyle holds two B.S. and one M.S. degrees in various engineering fields. His research at the ISU Center for Nondestructive Evaluation (CNDE) involves eddy current inspections in the fourth industry revolution (Industry 4.0).
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Trevor Watt
AVID R&D LLC

Progress Towards Inversion Techniques for Low Frequency Eddy Current Non-Destructive Inspections

Paper or Abstract

Biography

Dr. Xuhui Huang
Research Assisstant
Michigan State University

A Novel Data-driven Auto Compensation Algorithm for Pulsed Eddy Current Inspection with Internal Cable Effects

Paper or Abstract

Biography

Xuhui Huang is a Ph.D. candidate in Electrical and Computer Engineering at Michigan State University, with a focus on enhancing Nondestructive Testing (NDT) through novel electromagnetic compensation models and deep learning techniques. With significant experience at ARIX Technology and collaboration with ConEdison, Xuhui has developed novel methods for pulsed eddy current inspections and pipe thickness measurement. His work, underpinned by rigorous research and innovative algorithm development, is at the forefront of integrating AI with traditional NDT methods, promising substantial advancements in industrial safety and reliability.
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