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Proceedings Paper

Enhanced identifiability of nonlinear ultrasonic superharmonics for crack detection using an aluminum-lead composite bandgap meta-surface
Author(s): Yiran Tian; Yanfeng Shen; Danyu Rao; Wu Xu
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Paper Abstract

In this paper, a bandgap meta-surface is carefully designed for enhancing the identifiability of nonlinear ultrasonic superharmonics for fatigue crack detection. In the unit cell design stage, modal analysis with Bloch-Floquet boundary condition is performed to obtain the dispersion features of guided waves in the meta-surface. Then, a finite element model (FEM) for a chain of unit cells is simulated to verify the bandgap effect. In practice, due to the inherent nonlinearity from the electronic instrument and bonding adhesive, the corresponding weak superharmonic components will adversely affect the identifiability of the nonlinear characteristics raised by wave crack interactions. In the current approach, the guided waves generated by the transmitter propagate into the structure, carrying the inherent nonlinearity with them. Immediately afterwards, they pass through the meta-surface with optimized transmission of the fundamental excitation frequency and complete mechanical filtration of the second harmonic component. In this way, the appearance and amplitude of the second harmonic in the sensing signal become evidently indicative of the presence and severity of the fatigue crack along the wave path between the meta-surface and the receiver. The proposed method possesses great potential in future SHM and NDE applications. Nonlinear ultrasonic experiments with the designed meta-surface are conducted to verify the theoretical and numerical investigations as well as to demonstrate the practical application of metamaterial in SHM and NDE. The paper finishes with summary, concluding remarks, and suggestions for future work.

Paper Details

Date Published: 1 April 2019
PDF: 7 pages
Proc. SPIE 10972, Health Monitoring of Structural and Biological Systems XIII, 109721Y (1 April 2019); doi: 10.1117/12.2514040
Show Author Affiliations
Yiran Tian, Univ. of Michigan-Shanghai Jiao Tong Univ. Joint Institute, Shanghai Jiao Tong Univ. (China)
Yanfeng Shen, Univ. of Michigan-Shanghai Jiao Tong Univ. Joint Institute, Shanghai Jiao Tong Univ. (China)
Danyu Rao, Shanghai Jiao Tong Univ. (China)
Wu Xu, Shanghai Jiao Tong Univ. (China)


Published in SPIE Proceedings Vol. 10972:
Health Monitoring of Structural and Biological Systems XIII
Paul Fromme; Zhongqing Su, Editor(s)

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