## 1 Introduction
While process signatures may serve as useful proxies for identifying abnormal process conditions, their interpretation often relies on empirical correlations, which are sensitive to parameter variability and lack universal generalizability across different materials and part geometries [19]. In contrast, online NDT methods aim to directly interrogate the evolving material structure during layer-by-layer fabrication, allowing the detection of internal or subsurface defects in real time. Compared to offline techniques, online NDT methods offer critical advantages in terms of immediacy and responsiveness: they enable the dynamic adjustment of processing parameters, timely defect mitigation strategies, and the avoidance of cumulative errors that may compromise final part performance. Among the various online NDT techniques under active investigation, laser-based approaches have demonstrated significant potential due to their non-contact nature and adaptability to the thermally dynamic and often particulate-laden environment of metal AM. In particular, infrared thermography and laser ultrasonics (LU) have gained attention for their applicability in real-time defect detection [20]. While infrared thermography depends on the thermal response of the material surface and enables rapid detection, its depth penetration and sensitivity are inherently limited [21]. In contrast, LU offers a superior penetration capability, allowing for the detection of subsurface and internal defects with a high sensitivity and resolution [22]. As such, LU presents a highly promising solution for the online monitoring of internal defects in metal AM. LU offers notable advantages such as non-contact operation, high spatial resolution, and excellent accessibility, making it well suited for the harsh and complex conditions commonly encountered in AM processes, including high temperatures and dust-laden atmospheres [23]. Extensive experimental studies have demonstrated the potential of LU in this field, and significant progress has been made in recent years [24; 25]. For instance, [PERSON] et al. [26] applied laser-induced phased array detection combined with full matrix capture and the total focusing method (TFM) to inspect aluminum samples manufactured by SLM. Their approach enabled the detection of defects as small as 0.5 mm located at depths up to 26 mm, demonstrating the high sensitivity and spatial resolution achievable with laser ultrasonic techniques. In a related study, [PERSON] et al. [27] employed LU to inspect flat-bottom hole defects artificially embedded in AlSi12 samples fabricated via selective laser melting (SLM). The defects, with radii of 1 mm and depths ranging from 2 to 20 mm, were successfully detected, and their results were validated against X-ray computed tomography and immersion ultrasonic testing, confirming the feasibility of LU for internal defect evaluation in AM parts. Similarly, [PERSON] et al. [28] utilized surface acoustic waves (SAWs) generated by LU to detect embedded internal holes of varying sizes in Ti-6 Al-4V specimens. Their results showed an approximately linear attenuation of surface wave amplitude with increasing pore size and enabled the accurate identification of defects larger than 0.8 mm in both B-scan and C-scan images. However, the conventional LU method based on point- or line-focused sources still face several limitations. In particular, the broadband characteristics of the generated signals can complicate spectral interpretation and make wave velocity extraction challenging, as it requires the precise time-of-flight (TOF) and source-to-detector distance [29]. Furthermore, the relatively low signal-to-noise ratio (SNR) and sensitivity to surface roughness frequently necessitate surface preparation, such as polishing or sandblasting [30], which further hinders the practical implementation of conventional LU in real-time AM process monitoring. In recent years, grating laser ultrasonics have attracted increasing attention as a promising alternative.