GUW-based structural damage detection using WPT statistical features and multiclass SVM |
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| Institution: | 1. Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran;2. Department of Mechanical Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran;1. University of Bordeaux, I2M-APy, UMR 5295, F-33400 Talence, France;2. Arts et Metiers ParisTech, I2M-APy, UMR 5295, F-33400 Talence, France;3. CNRS, I2M-APy, UMR 5295, F-33400 Talence, France;1. Institute of Aeroelasticity, German Aerospace Center (DLR), Bunsenstr. 10, 37073 Göttingen, Germany;2. College of Engineering, Swansea University, Singleton Park, Swansea SA2 8PP, United Kingdom;3. Department of Civil and Environmental Engineering, University of Kassel, Germany;4. Institute for Risk and Uncertainty, University of Liverpool, United Kingdom;1. Zhijiang College, Zhejiang University of Technology, Hangzhou 310024, PR China;2. School of Mathematical Sciences, Inner Mongolia University, Hohehot 010021, PR China;3. College of Science China Agricultural University, Beijing 100083, PR China;1. Institute for Mathematics, Mechanics and Informatics, Kuban State University, Krasnodar, Russia;2. Department of Mechanical Engineering, University of South Carolina, Columbia, SC, United States;1. Department of Civil Engineering, Ahar Branch, Islamic Azad University, Ahar, Iran;2. Center for Engineering Application & Technology Solutions, Ho Chi Minh City Open University, Ho Chi Minh, Vietnam;3. Department of Civil Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran;4. School of Engineering, University of Southern Queensland, Springfield, QLD 4300, Australia;5. Applied Mechanics Laboratory University of Science and Technology of Oran - Mohamed Boudiaf, Algeria;6. Soete Laboratory, Faculty of Engineering and Architecture, Ghent University, Technologiepark Zwijnaarde 903, B-9052 Zwijnaarde, Belgium |
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| Abstract: | Recently, guided ultrasonic waves (GUW) are widely used for damage detection in structural health monitoring (SHM) of different engineering structures. In this study, an intelligent damage detection method is proposed to be used in SHM applications. At first, GUW signal is de-noised by discrete wavelet transform (DWT). After that, wavelet packet transform (WPT) is employed to decompose the de-noised signal and the statistical features of decomposed packets are extracted as damage-sensitive features. Finally, a multiclass support vector machine (SVM) classifier is used to detect the damage and estimate its severity. The proposed method is employed for GUW-based structural damage detection of a thick steel beam. The effects of different parameters on the sensitivity of the method are surveyed. Furthermore, by comparing with some other similar algorithms, the performance of the proposed method is verified. The experimental results demonstrate that the proposed method can appropriately detect a structural damage and estimate its severity. |
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| Keywords: | Damage detection Guided ultrasonic wave (GUW) Structural health monitoring (SHM) Discrete wavelet transform (DWT) Wavelet packet statistical features Support vector machine (SVM) |
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