Enhancing Guided Wave Tomography for Improved DefectDetection in Critical Structures
Containment liner plates are essential for structural safety in critical systems. Detecting defects in these components requires advanced non-destructive testing (NDT) techniques to address challenges such as complex geometries and material properties. Tomographic imaging reconstructs damage p...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | deu |
| Published: |
NDT.net
2025-03-01
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| Series: | e-Journal of Nondestructive Testing |
| Online Access: | https://www.ndt.net/search/docs.php3?id=30814 |
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| Summary: | Containment liner plates are essential for structural
safety in critical systems. Detecting defects in these
components requires advanced non-destructive testing (NDT)
techniques to address challenges such as complex geometries
and material properties. Tomographic imaging reconstructs
damage probability maps by analyzing guided wave
interactions, offering detailed visualizations of defect
locations and enabling precise localization in challenging
scenarios.
This study evaluates two tomographic methodologies: the
Reconstruction Algorithm for Probabilistic Inspection of
Defects (RAPID) and the enhanced Density Clustering-RAPID
(DC-RAPID). RAPID provides a robust framework for defect
localization by leveraging optimized shape factors to
enhance sensitivity and probability mapping. However, it
struggles with achieving precise localization in complex
geometries or under noisy conditions. DC-RAPID overcomes
these limitations by integrating density-based clustering,
which effectively reduces false positives and identifies
high-probability zones. Incorporating adaptive probability
mapping, DC-RAPID significantly enhances imaging quality
and defect resolution. Comparative analysis demonstrates
the superior accuracy and reliability of DC-RAPID in
identifying and characterizing defects. These advancements
highlight the potential of guided wave tomography,
particularly DC-RAPID, for improving NDT in critical
structures.
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| ISSN: | 1435-4934 |