Acoustic Emission Source Localization in Fiber-Reinforced Composites based on Multimodal Dispersion Compensation of Guided Waves

Conference paper (2023)

Authors

C. Kassapoglou Group De Breuker
L. Pahlavan Ship and Offshore Structures
Research Group
Group De Breuker
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Published Date

2023

Language

English

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Research Group

Group De Breuker

Abstract

Fiber-reinforced composite materials are widely used in the aviation, civil, and shipbuilding industries. Especially the latter two industries are typically dealing with thicker composites. At the same time, in these industries the need for structural health monitoring, to assess degradation and failure, is becoming more prevalent. Acoustic emission (AE) measurement and analysis for damage source localization and characterization can be a useful method for the assessment of structural integrity for these structures. In the case of composite panels, acoustic emissions can propagate in the form of elastic guided waves. The location of the AE source exposes regions in a structure that are subject to degradation. Typical acoustic emission source localization methods assume that the recorded AE signals consist of a single dominant fundamental wave mode. However, with thicker composites, the acoustic emissions may propagate in a multitude of modes. This will complicate the signal processing operations for accurate source localization. This research assesses experimentally how guided wave multimodality influences acoustic emission localization. An acoustic emission source is excited in a thick glass fiber-reinforced plastic (GFRP) panel. Measurements from this excitation are first assessed for their content of higher modes. Source localization is carried out based on dispersion compensation through time-distance domain migration. Different possibilities and combinations of wave modes are considered. The localization error is assessed for each option. The results highlight the added complexity of multimodality and show how the inclusion of multiple modes into the procedure can improve the accuracy of source localization.