Tuned Lamb-Wave Excitation and Detection with Piezoelectric Wafer Active Sensors for Structural Health Monitoring

Document Type

Article

Subject Area(s)

Engineering, Mechanical Engineering

Abstract

The capability of embedded piezoelectric wafer active sensors (PWAS) to excite and detect tuned Lamb waves for structural health monitoring is explored. First, a brief review of Lamb waves theory is presented. Second, the PWAS operating principles and their structural coupling through a thin adhesive layer are analyzed. Then, a model of the Lamb waves tuning mechanism with PWAS transducers is described. The model uses the space domain Fourier transform. The analysis is performed in the wavenumber space. The inverse Fourier transform is used to return into the physical space. The integrals are evaluated with the residues theorem. A general solution is obtained for a generic expression of the interface shear stress distribution. The general solution is reduced to a closed-form expression for the case of ideal bonding which admits a closed-form Fourier transform of the interfacial shear stress. It is shown that the strain wave response varies like sin a, whereas the displacement response varies like sinc a. Maximum coupling is achieved when the PWAS length equals the half wavelength of a particular Lamb wave mode. Since Lamb wave modes wavelengths vary with frequency, the tuning of certain modes at certain frequencies can thus be achieved. Tuning curves are derived and verified against experimental results. A particular S0 mode ‘sweet spot’ is found at 300 kHz for a 7-mm PWAS attached to a 1.6-mm aluminum plate. Crack detection via the pulse echo technique using the phased array principle and tuned S0 mode Lamb waves is demonstrated as an effective structural health monitoring method.

Rights

© Journal of Intelligent Material Systems and Structures, 2005, SAGE Publications.

Giurgiutiu, V. (2005). Tuned Lamb-Wave Excitation and Detection with Piezoelectric Wafer Active Sensors for Structural Health Monitoring. Journal of Intelligent Material Systems and Structures, 16(4), 291-306.

http://dx.doi.org/10.1177/1045389X05050106

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