Physics-Informed Single Atom Matching Pursuit: Guided-Waves Wavenumbers and Propagation Distance Estimation for Damage Localization in Structural Health Monitoring

2026-06-02

AI Summary

In conventional guided-wave-based structural health monitoring, multimodal dispersive waves excited by a single piezoelectric transducer overlap significantly, complicating signal interpretation and degrading damage localization accuracy. To address this challenge, this work proposes a physics-informed sparse signal decomposition method—Physics-Informed Single-Atom Matching Pursuit (PISAMP)—which, for the first time, embeds the guided-wave dispersion relationship into a compact decomposition framework to directly extract interpretable physical features such as modal wavenumbers and propagation distances. By integrating these features with an elliptical localization algorithm, the approach accurately estimates the propagation paths among the source, damage, and sensor from highly aliased signals, thereby substantially improving both damage localization precision and model interpretability.

Abstract

Structural Health Monitoring (SHM) aims at the real-time monitoring of the integrity of engineering structures, with Guided-waves (GWs) providing high sensitivity to damage presence and to ageing effects for thin-walled components. In conventional GW-based SHM, a bonded piezoelectric transducer (PZT) emits a short tone burst that produces an Initial Wave Packet (IWP) propagating through the structure. As this packet interacts with boundaries and potential damages, additional scattered wave packets are produced. A major limitation of such approaches lies in the simultaneous excitation of multiple dispersive GW modes by a single PZT, which significantly complicates signal interpretation and damage monitoring. In this context, this work proposes the Physics-Informed Single Atom Matching Pursuit (PISAMP) method, a signal decomposition method grounded in the physical principles governing wave propagation. In contrast with purely data-driven or numerically intensive techniques, the proposed approach embeds strong physical constraints into a low-dimensional and computationally efficient signal representation. This formulation enables the direct identification of key physically meaningful features, including modal wavenumber functions and propagation distances between actuator, damage and sensors. These extracted features, especially source-damage-sensor distances, allows to subsequently perform damage location using well established Elliptical Localization techniques. The principal novelty of this study lies in integrating wave propagation physics into a compact signal decomposition framework and developing an interpretable damage localization methodology for GW-SHM applications.

Problem

• Guided-waves
• Structural Health Monitoring
• Damage Localization
• Wave Propagation
• Signal Interpretation

Innovation

• Physics-Informed Signal Decomposition
• Guided-Waves
• Damage Localization
• Matching Pursuit
• Wavenumber Estimation