Adaptive compensated MUSIC beamforming for Lamb wave damage localization under varying temperature

Structural health monitoring based on Lamb waves is significantly challenged by environmental temperature variations, which introduce complex signal distortions that can obscure damage-related features. A Lamb wave damage localization methodology based on a compensated multiple signal classification (MUSIC)-beamforming framework using dual sensor arrays is presented under variable temperature conditions. The methodology is underpinned by a comprehensive array signal propagation model that has been developed to characterize temperature-induced effects on wave propagation, with explicit consideration given to both amplitude and phase variations. An enhanced near-field MUSIC formulation is developed in which temperature-induced amplitude and phase distortions are characterized by a calibrated error matrix; phase compensation restores the angular estimate while amplitude compensation preserves the beamforming gain and imaging quality. The methodology is further augmented through the integration of beamforming techniques, which serve to enhance spatial filtering capabilities and improve imaging resolution under varying temperature conditions. Extensive experimental validation has been conducted on aluminum plates with artificial damages, where temperature conditions were systematically varied from −40 to 80°C. The experimental results have demonstrated that consistent localization accuracy can be achieved with relative errors maintained below 9% across all temperature conditions.