Ultrasonic guided wave imaging for damage characterization

Guided wave imaging with a sparse array of inexpensive transducers offers a fast, reliable, and cost-efficient means for damage detection and localization in plate-like structures such as aircraft and spacecraft skins. As such, this technology is a natural choice for inclusion in condition-based maintenance and integrated structural health management programs. One of the implementation challenges results from the complex interaction of propagating ultrasonic waves with both the interrogation structure and potential defects or damage. For example, a guided wave interacts with a surface or sub-surface defect differently depending on the angle of incidence, defect orientation, and ultrasonic frequency. Fortunately, however, this complex interaction also provides a mechanism for guided wave imaging algorithms to perform damage characterization in addition to damage detection and localization. Damage characterization provides a mechanism to help discriminate between actual damage (e.g. fatigue cracks) and benign changes, and can be used with crack propagation models to characterize the stress state. This work proposes the combined use of two guided wave imaging techniques to perform both damage localization and characterization. The robustness of conventional delay-and-sum imaging to errors in a priori assumptions make it ideal for use in locating potential damage locations. Minimum variance imaging, which is highly sensitive to errors in a priori assumptions, can then be leveraged to characterize the potential damage location by determining which scattering assumptions best match the measured data. Scattering assumptions are obtained through finite element modeling (FEM). Experimental data from an in situ sparse array are used to demonstrate feasibility of this approach using two through-thickness notches of different orientations, one inside and one outside the array bounds, to simulate damage in an aluminum plate.