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Spatial Thickness Mapping in Heterogeneous Plate Using Wave Physics-Informed Regression — arXiv:2610.00944

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.00944
License (as archived): CC0-1.0
Archived: 2026-10-07T12:38:03.385Z
SHA-256 of the archived text: 20b5bf0ed413f498affa463be52801472028c3a37ae445684b29040d61a93568
Stable URL of this page: https://metraipolis.com/documento/dc_4b451cd2ccfc

How to cite

Spatial Thickness Mapping in Heterogeneous Plate Using Wave Physics-Informed Regression — arXiv:2610.00944 — arXiv (en), https://arxiv.org/abs/2610.00944 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_4b451cd2ccfc (Metraipolis archive dc_4b451cd2ccfc, sha256 20b5bf0ed413f498affa463be52801472028c3a37ae445684b29040d61a93568)

BibTeX

@misc{dc4b451cd2ccfc,
  title = {Spatial Thickness Mapping in Heterogeneous Plate Using Wave Physics-Informed Regression — arXiv:2610.00944},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.00944},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_4b451cd2ccfc; sha256 20b5bf0ed413f498affa463be52801472028c3a37ae445684b29040d61a93568},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.00944. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Traditional guided wave methods for structural health monitoring typically assume uniform material properties, which limit their ability to characterize heterogeneous structures with spatially varying thickness, damage, or material properties. These are challenges commonly encountered in corrosion assessment, composite delamination detection, and structural degradation monitoring. This paper presents a wave physics-informed regression approach that enables spatially resolved characterization of material properties by extracting local dispersion curves across a structure. Our approach focuses on a highly interpretable but flexible physics-informed framework that can be solved using fast algorithms and achieve robust numerical solutions. This paper discusses the mathematical design of the framework, the algorithm, and its interpretation. The framework was applied to a guided wave wavefield imaging dataset from a thin aluminum plate with non-uniform thickness around a hole to validate its practicality. The framework creates an accurate thickness map (correlation coefficient 0.94 with x-ray CT validation) as well as extracts the frequency-dependent velocities of waves within those regions.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-10-02 in eess.SP).
Categorie arXiv: Signal Processing (eess.SP).
Pagina del lavoro: https://arxiv.org/abs/2610.00944 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-07T12:10:56.181Z dalla pagina https://arxiv.org/catchup/eess.SP/2026-10-02?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).