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High Resolution Localization with Lamb Wave Sparse Wavenumber Analysis
Abstract
Guided wave structural health monitoring techniques have grown in popularity due to their ability to interrogate large areas at once and their sensitivity to damage in structures. However, guided waves are inherently complex due to their dispersive and multi-modal characteristics. These characteristics also change with variations in environmental conditions. As a result, many sophisticated localization algorithms, which rely on precise knowledge of the medium, fail to successfully locate damage. Alternatively, many current localization approaches preprocess data to simplify the measurements and reduce the adverse effects of dispersion and multiple modes. Often, these approaches only consider the first arriving wave mode across a narrow band of frequencies. They also reduce the effects of dispersion by analyzing the envelope of the received signals rather than the raw data. While these preprocessing steps may help to improve localization accuracy, they significantly degrade the resulting resolution and image quality. In this paper, we integrate a methodology known as sparse wavenumber analysis with current localization algorithms to utilize the multiple modes and dispersive characteristics of Lamb waves in a plate across a wide band of frequencies to localize damage without computing envelopes or performing similar preprocessing steps.