A model-informed approach to robust calibration of experimental guided wave modes with cyberphysical systems

Gullapalli, Anirudh, Aburakhis, Taha, Featherston, Carol ORCID: https://orcid.org/0000-0001-7548-2882, Pullin, Rhys ORCID: https://orcid.org/0000-0002-2853-6099 and Kundu, Abhishek ORCID: https://orcid.org/0000-0002-8714-4087 2025. A model-informed approach to robust calibration of experimental guided wave modes with cyberphysical systems. Presented at: AIAA SCITECH 2025 Forum, Orlando, Florida, 6-10 January 2025. Proceedings AIAA SCITECH 2025 Forum. American Institute of Aeronautics and Astronautics, Inc, 10.2514/6.2025-1219 Item availability restricted.

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Abstract

The multilayered, and anisotropic nature of composite structures presents challenges in monitoring the initiation and progression of damage. Non-intrusive inspection methods are vital to the continuous monitoring regime and facilitate the transition to a predictive maintenance regime for these structures. The effectiveness of this transition relies on the efficacy of the onboard monitoring system to acquire signals and extract essential features on the edge. These signal features, when correlated with parameterized damage metrics, enable the characterization of damages, and help to realize an automated framework for assessment of structural integrity and determining optimal maintenance intervention points. This study presents a model-informed and acousto-ultrasonic experimental data driven approach for isolation and reconstruction of fundamental guided wave modes in a 12-layered carbon fiber reinforced composite panel. A daisy chained edge device along with a sparse transducer array captured structural-acoustic responses to a monotonic frequency-swept user-defined sinusoidal actuation pulse. A combined data-driven and model-informed reconstruction algorithm integrated the acquired experimental data, the derived semi-analytical composite waveguide dispersion characteristics and the point-to-point system transfer function at each transducer location, to reconstruct the ultrasonic guided wave modes. Initial deterministic optimization regimes, based on the Euclidean norm of the difference between experimental and reconstructed signal Hilbert envelopes, generated high-fidelity reconstructions, validated by strong concordance with empirical data. This method was further extended using a Bayesian inference-based probabilistic joint parameter estimation framework to quantify uncertainties associated with both experimental measurements and model predictions. The joint parameter distribution results demonstrated the model's efficacy in assigning a statistical dependence between the posterior predictive estimates that closely resembles the underlying physics governing the model. Hilbert envelopes generated using the samples from the posterior distributions of mode amplitudes and model parameters showed high concordance with the experimental acousto-ultrasonic signals, reinforcing the model's ability in capturing the true signal characteristics within a reasonable range of uncertainty. Future work will focus on investigating changes in the modal properties of the guided waves as a function of parameterized structural degradation. The estimated damage signatures will help to quantify the uncertainties of the experimental measurements and model predictions. This will facilitate the development of a physics-informed, robust and non-intrusive structural health monitoring system with real-time decision making capabilities.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Schools > Engineering
Publisher:	American Institute of Aeronautics and Astronautics, Inc
ISBN:	9781624107238
Funders:	EPSRC
Date of First Compliant Deposit:	3 March 2025
Date of Acceptance:	2 December 2024
Last Modified:	03 Mar 2025 11:15
URI:	https://orca.cardiff.ac.uk/id/eprint/176251

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