Application of Image Processing Techniques for Lamb Wave Characterization

Abstract

Characterization of dispersion curves in plate-like structures is possible with guided Lamb waves. In this research, experimental development of dispersion curves relies on the spectrogram, which suffers from the Heisenberg Uncertainty Principle. Reassignment is capable of localizing ill--defined dispersion curves. Unfortunately, reassignment also introduces spurious components, which reduce reassignment performance. This research develops an algorithm that provides both localization of dispersion curves and elimination of spurious components. To achieve this, an alternative formulation of reassignment called differential reassignment is modified and superimposed with nonlinear anisotropic diffusion. This study first examines reassignment and diffusion components individually. Three different versions of differential reassignment are considered, two of which are modifications explicitly derived in this research. The combined algorithm is then applied to reassign experimentally measured spectrograms, leading to a significant increase in clarity and notch detection performance.