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Nondestructive wire fault diagnosis using resistance spectroscopy analysis

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Abstract

Wires in field applications, such as aircraft, are often exposed to stress conditions, including overheating, moisture ingress, or inherent defects, which may result in electrical discontinuity, wire insulation breakdown, and system failure. This study proposed a nondestructive and real-time wire fault diagnosis method through resistance spectroscopy to diagnose the health of wires under stress conditions. Wire abrasion tests were conducted by applying cyclic mechanical stress to produce gradual damage to a wire under test. During abrasion testing, a lock-in amplifier generated high-frequency signals and monitored the signals transmitted through the wire to diagnose the wire failure under test. Differences in signal amplitude, and phase shift spectra during wire degradation exhibited specific and distinguishable behavior based on the physical damage progression of the tested wire. Test results implied that resistance spectroscopy analysis could serve as a nondestructive wire fault diagnosis method, providing damage progression in real time.

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Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1 A1B03028604) and Ulsan Metropolitan City (1.190032.01).

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Correspondence to Daeil Kwon.

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Recommended by Guest Editor Maenghyo Cho.

Eunju Park received the B.S. and M.S. from Department of Materials Science and Engineering at Ulsan University, Korea, in 2006 and 2008, respectively. She obtained her Ph.D. in Materials Science and Engineering from the UNIST, Korea, in 2015. She is currently a Senior Researcher in School of Mechanical, Aerospace and Nuclear Engineering at UNIST, Korea. Her research interests focused on the reliability of electronic components and manufacturing technology.

Namhun Kim earned his B.Sc. in 1998 and M.Sc. in 2000 from KAIST. After that, he worked as a Senior Researcher in Samsung Corning, Co., Ltd for five years. Then, he received his Ph.D. in Industrial and Manufacturing Engineering from Penn State University, University Park, PA, USA in 2010. He worked as a Research Associate in Penn State University from January to June 2010. He joined UNIST in 2010 and is currently working as an Associate Professor in the Department of System Design and Control Engineering, acting as the Director of 3D Printing Research Center at UNIST, Korea. His interest is in manufacturing technologies with emphasis on additive manufacturing (3D printing), manufacturing system modeling and agent-based simulation.

Seong-Joon Kim received the B.S. and Ph.D. degrees in industrial engineering, both from Hanyang University, Seoul, South Korea, in 2006 and 2013, respectively. He worked as a Senior Research Engineer in Data Analytics Team at Doosan Heavy Industries & Construction, Seoul, South Korea. He is currently an Assistant Professor in the Department of Industrial Engineering at Chosun University, Gwangju, South Korea. His research interests cover design and reliability analysis of accelerated degradation and life tests. He also has research interests in data science and machine learning applications to large-scale system for PHM (prognostics and health management).

Daeil Kwon received the bachelor’s degree in mechanical engineering from POSTECH, South Korea, and the Ph.D. degree in mechanical engineering from the University of Maryland, College Park, MD, USA. He was a Senior Reliability Engineer with Intel Corporation, Chandler, AZ, USA, where he developed use condition-based reliability models and methodologies for assessing package and system reliability performance. He is currently an Associate Professor with Konkuk University, Seoul, South Korea. His research interests are focused on prognostics and health management of electronics, reliability modeling, and use condition characterization.

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Park, E., Kim, N., Kim, Sj. et al. Nondestructive wire fault diagnosis using resistance spectroscopy analysis. J Mech Sci Technol 33, 3649–3654 (2019). https://doi.org/10.1007/s12206-019-0705-3

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  • DOI: https://doi.org/10.1007/s12206-019-0705-3

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