Pushing the Limits of Ultrasonic Imaging of Solids by Wave Mode Beamforming and GPU Processing

This paper proposes a novel imaging approach for damage identification in structural components. Improvements to conventional Synthetic Aperture Focus (SAF) algorithms are introduced by exploiting multiple wave propagation modes (longitudinal and shear) in the bulk of the material. Significant reduction of artifacts is achieved through the application of adaptive weights based on the wave mode structure and the coherent compounding of longitudinal and shear waves. Further improvement can be achieved by introducing various signal processing techniques, such as baseline subtraction and deconvolution of the point spread function. Finally, utilizing the massively parallel processing structure of a Graphical Processing Unit (GPU) architecture, a considerable increase in speed can be achieved compared to a traditional serial processing technique based on a Central Processing Unit (CPU). A 64-element linear array connected to a data acquisition system was used for experimental validation of the proposed tomographic algorithm steps. Results will be shown from tests performed on rail sections with simulated and natural flaws acquired from the Federal Railroad Administration (FRA) rail defect library. Considerable reduction of side lobes and improvement of image contrast are demonstrated. Future extensions of this work are also investigated, including guided wave inspection in a multi-mode environment and high-speed inspections.