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Laser Ultrasonic Spatially Resolved Acoustic Spectroscopy (SRAS) is a technique used for detecting the grain size of metal surfaces. It involves exciting Surface Acoustic Waves (SAW) using a grated light source and employs optical deflection techniques to detect ultrasound. The differences in sound velocity between different grains are utilized for grain size characterization. However, this technique is susceptible to the influence of sample surface roughness, resulting in issues like low signal-to-noise ratio and waveform distortion. To address these challenges, a study was conducted on grain size characterization using Laser Ultrasonic SRAS based on Improved Variational Mode Decomposition (IVMD). This involved optimizing Variational Mode Decomposition (VMD) by introducing Permutation Entropy (PE), Weighted Spectral Kurtosis (WSK), and Dynamic Time Warping (DTW). Adaptive decomposition and selection of simulated surface wave signals were employed to achieve signal recovery. A comparison with Empirical Mode Decomposition (EMD) demonstrated that the proposed algorithm had higher noise robustness. The Laser Ultrasonic SRAS detection system was used to characterize the grain size of Ti-6Al-4V casting alloys, and the data were processed using the proposed algorithm. The results were consistent with optical microscopy images, further confirming the reliability and effectiveness of the improved algorithm. The research findings indicate that Laser Ultrasonic Spatially Resolved Acoustic Spectroscopy based on IVMD can effectively reduce the impact of noise on detection signals, thereby enhancing the detectability of grain size measurement. • The grain size of Ti-6Al-4V is characterized by a Laser Ultrasonic SRAS system. • An IVMD algorithm is proposed to address the issue of low SNR. • The proposed algorithm can adaptively decompose and select ultrasound signal. • The detectability of grain size detection has been improved by IVMD. [ABSTRACT FROM AUTHOR]

An accurate frequency-domain synthetic aperture focusing technology (F-SAFT) based on 2-D equivalent velocity mapping is proposed for laser ultrasonic testing (LUT) to detect and image internal defects in specimens. The equivalent velocity mapping varies with depth and spatial frequency to match the characteristics of the separated excitation and detection commonly used in LUT. Bulk acoustic waves are non-destructively excited by a line-shaped laser source and are detected by a laser Doppler Vibrometer. By compensating for the distance shift arising from the separation of the laser spots, the imaging defect location is corrected. Several optimisations of the algorithm are carried out: the calculation time of the equivalent velocity is reduced by simplifying its expression, and the imaging quality, especially for defects with a shallow depth, is improved by the 2-D equivalent velocity mapping. The results show that compared with traditional F-SAFT, the optimised F-SAFT algorithm can not only improve the imaging quality but also locate the defect more accurately with separated excitation and detection. • F-SAFT with various velocity mappings for separated excitation and detection. • 2-D velocity mapping with high calculation efficiency. • Improved imaging quality of shallow defects by optimising equivalent velocity. • Corrected defect's horizontal location by compensating imaging shift. [ABSTRACT FROM AUTHOR]