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Empirical mode decomposition approach for defect detection in non-stationary thermal wave imaging
Affiliation:1. OASIS, Muroran Institute of Technology, 27-1, Muroran, Hokkaido, Japan;2. Graduate School, Muroran Institute of Technology, 27-1, Muroran, Hokkaido, Japan;1. Imperial College London, Department of Mechanical Engineering, Exhibition Road, London SW7 2AZ, UK;2. E.ON Technologies (Ratcliffe) Ltd., Technology Centre, Nottingham NG11 0EE, UK;1. Nondestructive Detection and Monitoring Technology for High Speed Transportation Facilities, Key Laboratory of Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, 211106, China;2. JSPS International Research Fellow, Graduate School of Engineering, Tohoku University, 6-6-01-2, Aramaki Aza Aoba, Aoba-Ku, Sendai, Miyagi, 980-8579, Japan;3. Department of Quantum Science and Energy Engineering, Graduate School of Engineering, Tohoku University, 6-6-01-2, Aramaki Aza Aoba, Aoba-Ku, Sendai, Miyagi, 980-8579, Japan;1. NDE Group, Mechanical Engineering Department, Imperial College London, London SW7 2AZ, United Kingdom;2. Department of Aerospace Engineering and Engineering Mechanics, University of Cincinnati, Cincinnati, OH 45221, USA
Abstract:This paper introduces a novel empirical mode decomposition based anomaly detection in Quadratic frequency modulated thermal wave imaging. Being suited for non-stationary signal analysis, its edge over other contemporary processing modalities in its anomaly detection capability has been verified using experimentation carried over a mild steel specimen with embedded flat bottom holes. It also addresses the effect of size and depth on anomaly detection using the proposed methodology in addition to considering the signal to noise ratio of defects for detection.
Keywords:Thermal wave imaging  Correlation analysis  Phase analysis  Empirical mode decomposition
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