Lamb Wave SHM/NDE Using Multidimensional Wavefield Data

Lamb waves are a subset of guided waves that propagate between two parallel surfaces, such as shell and plate structures. They have proven to be useful for structural health monitoring (SHM), nondestructive evaluation (NDE), and detecting damage in plate-like structures due to their ability to propagate long distances with less energy loss compared to bulk waves, and due to their sensitivity to small defects in the structure. In spite of the advancement in Lamb wave based methodologies, there remains many challenging problems for real-world implementation due to the complexity involved with propagating Lamb waves, such as multimodal and dispersive characteristics which makes the interpretation of Lamb wave signals difficult in either the time or frequency domain.

In this presentation, we present our study of Lamb wave based SHM/NDE using multidimensional wavefield data and the subsequent frequency-wavenumber detection algorithms, which are enabled by high spatial resolution laser Doppler vibrometer sensing technique. We demonstrate how to strategically construct an optimized sensing network that can minimize the wiring requirement while maintain a quick and efficient wavefield measurement. The wavefield data that contains both temporal and spatial information regarding the wave propagation reveal additional information beyond the traditional time series. Multi-dimensional Fourier transform is applied to derive alternative frequency-, space-, and/or wavenumber- representations. Several imaging algorithms are then developed using the multidimensional wave data. These methods have shown effectively in revealing wave scattering behaviors in plates as well as detecting defects with complex profiles. Our current effort is to extend the methodologies to remote sensing SHM/NDE