Laser Ultrasonic Detection and Signal Enhancement of Internal Microdefects in LPBF Ti6Al4V with Anisotropic Microstructure: Simulations and Experiments
Laser Powder Bed Fusion (LPBF) has revolutionized high-end manufacturing, particularly in aerospace and biomedical fields. However, internal defects such as pores, cracks, and inclusions compromise the structural integrity and service reliability of LPBF components. Laser ultrasonics, a non-contact, broadband non-destructive testing (NDT) method, offers a promising solution for detecting and characterizing these defects. This study systematically investigated laser ultrasonic testing technology for LPBF-fabricated Ti6Al4V using a combined approach of physics-driven simulation modeling and experimental validation. To accurately model material anisotropy, a finite element model was developed that integrated Voronoi algorithm-generated polycrystalline microstructures with orientation-dependent elastic tensors, providing a comprehensive representation of the material’s microstructural heterogeneity. Simulation results revealed that while sub-100-μm defects yield weak ultrasonic scattering signals, the Synthetic Aperture Focusing Technique (SAFT) markedly improves the detection and imaging performance for such small-scale defects. Experimental validation using a laser ultrasonic system identified a 90 μm internal defect in the LPBF Ti6Al4V specimen, though a 75 μm defect was undetectable. This highlights the need for enhanced sensitivity. A signal processing method combining time-truncation principal component analysis (PCA) with targeted noise reduction and SAFT was proposed to reduce high-frequency noise and improve high-resolution imaging, enhancing defect detection accuracy. This study provides theoretical foundations and technical support for high-precision defect detection in metal additive manufacturing components, with significant implications for quality control in high-end equipment manufacturing.
Authors
- Xingyu Zhou (ORCID: https://orcid.org/0000-0002-0523-5699)
- Ping Hu (ORCID: https://orcid.org/0000-0003-1115-0189)
- Jia Xie
- Yixuan He
Institutions
- Wuhan University (CN)
- China XD Group (China) (CN)
Publication Details
- Journal
- Micromachines
- Published
- 2026-08-28
- DOI
- https://doi.org/10.3390/mi17091025
- Primary Topic
- Additive Manufacturing Materials and Processes
- Type
- article
- Field-Weighted Citation Impact
- 0.00