Coarray Lamb wave damage localization

In Lamb wave-based structural health monitoring methods, both imaging algorithms and array configurations play critical roles in determining imaging quality. However, existing imaging algorithms rely on time-consuming two-dimensional (2D) searches. Meanwhile, the conventional uniform array configurations limit the array aperture and localization accuracy. To reduce the computational burden and improve the localization accuracy, we propose a damage localization method based on a sparse linear array. This method decouples range and angle by constructing a specially designed fourth-order cumulant using virtual global waves, thereby avoiding the time-consuming 2D search caused by the coupling between range and angle in conventional methods. Owing to the use of the cumulant, the designed symmetric sparse linear array can be expanded into a virtual coarray with a larger aperture, thereby enhancing localization accuracy. To effectively utilize phase information, we developed a Lamb wave extrapolation technique that transforms local waveforms into global waves carrying reliable phase information. Numerical simulations and experimental validations were conducted on an aluminum plate with two defects, followed by engineering validation on the A380 flap track fairing. We compared the proposed method with several existing imaging techniques in terms of both localization accuracy and computational time. The results demonstrate that the proposed method achieves significantly higher imaging accuracy with less computational time.