Physics-Informed Guided Wave Modes as Robust Identifiers of Progressive Structural Degradation in Thin-Walled Composite Structures

Ultrasonic guided waves hold significant potential for non-intrusive monitoring of progressive damage in composite structures, contingent on the efficacy of the onboard monitoring system to reliably acquire, process signals. By mapping the extracted signal features with parameterized damage metrics, it is possible to realize an automated framework for the assessment of structural integrity. It is well established that fundamental ultrasonic guided wave modes are sensitive to damage in laminated composite structures and can serve as robust damage identifiers when properly characterized. But there is a gap in understanding of the modified behavior in waveguide dispersion properties due to the presence of damages or deterioration of waveguide properties. Therefore, it is vital to establish a generic, extendable and reproducible wave mode reconstruction methodology so that the fundamental ultrasonic guided wave modes can be investigated for damage signatures. Towards this, The fundamental $S_0$ and $A_0$ modal amplitudes and dispersion characteristics were calibrated using a physics-informed harmonic wave propagation model. This process generated individual mode realizations that were then superimposed to produce accurate reconstructions of experimental signals acquired from a sparse array of piezoelectric transducers. A regularized residual error function was formulated to account for discrepancies from measurement noise, unmodeled higher-order modes, and other sources of error. A probabilistic Bayesian joint parameter estimation approach was employed to minimize this error and calibrate the wave mode characteristics. The calibrated parameters were subsequently used to investigate progressive structural degradation arising from displacement-controlled compressive fatigue loading. A probabilistic Bayesian joint parameter estimation framework effectively captured direction--specific signatures and quantified uncertainty in parameter estimation, revealing distinct directional and modal sensitivities to fatigue damage. This achievement underscores the efficacy and reliability of the calibrated ultrasonic guided wave modes as reliable identifiers of damage with potential for further description, characterization, and sentencing.