This paper presents damage imaging and quantification by using the spectral field of Lamb waves. The spectral field is acquired through a piezoelectric transducer (PZT)-scanning laser Doppler vibrometer (SLDV) sensing. A wideband chirp signal is used for PZT excitation in order to generate wideband Lamb waves. With the SLDV, the time-space wavefield is acquired, and transformed into the spectral field representation through Fourier transform. The spectral field, which contains wideband Lamb wave responses of the structure, is further analyzed for damage detection and quantification. Using the spatial wavenumber analysis, the local wavenumber at each location are obtained, and represented as a spatial wavenumber image which can be used for damage detection and evaluation. Moreover, the dispersion curve regression method is developed to quantify the thickness change of a defect. For verification, experiments are performed on aluminum plates with blind holes of different depths. The experimental results show that the blind holes can be detected by both the spatial wavenumber imaging and dispersion curve regression. In addition, the dispersion curve regression can further quantify the depths of the blind holes.
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Damage Imaging and Quantification Using Spectral Field
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Tian, Z, & Yu, L. "Damage Imaging and Quantification Using Spectral Field." Proceedings of the ASME 2015 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 2: Integrated System Design and Implementation; Structural Health Monitoring; Bioinspired Smart Materials and Systems; Energy Harvesting. Colorado Springs, Colorado, USA. September 21–23, 2015. V002T05A013. ASME. https://doi.org/10.1115/SMASIS2015-9091
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