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This study investigates and evaluates the technology of using plate waves to detect the locations and sizes of circular holes and cracks in plates. Piezoelectric ceramic discs surface-mounted on both sides of an aluminum alloy plate were used as narrow-frequency plate wave actuators and sensors, and the antisymmetric plate wave signal was analyzed by wavelet transform in the time-frequency domain. The damage location and frequency spectrum characteristics were identified by the wave through time-of-flight difference and signal analysis of the damage scattered wave group. The plate wave signal of the damaged plate included the scattered wave signal and the plate wave signal transmitted directly between the piezoelectric discs. Under ideal conditions, the plate wave signal indicating damage can be obtained by subtracting the plate wave signal in a plate without damage from the plate wave signal scattered from actuators to sensors. This study established an optimization program based on the simplex algorithm to inversely calculate the location of the plate damage. The developed damage location objective function has a unique global minimum value that can ensure the accuracy of the damage location calculation, and good results were obtained in experiments. The spectral characteristics of the scattered plate wave were related to the type, size, wave propagation path, and incident angle of the damage. Numerical analyses of scattered spectra for various damages are needed as references to compare with experimental results in the future. [ABSTRACT FROM AUTHOR]

Lamb wave-based structural health monitoring techniques have the ability to scan a large area with relatively few sensors. Lamb wave imaging is a signal processing strategy that generates an image for locating scatterers according to the received Lamb waves. This paper presents a Lamb wave imaging method, which is formulated as a weighted structured sparse reconstruction problem. A dictionary is constructed by an analytical Lamb wave scattering model and an edge reflection prediction technique, which is used to decompose the experimental scattering signals under the constraint of weighted structured sparsity. The weights are generated from the correlation coefficients between the scattering signals and the predicted ones. Simulation and experimental results from an aluminum plate verify the effectiveness of the present method, which can generate images with sparse pixel values even with very limited number of sensors. [ABSTRACT FROM AUTHOR]