Laser Ultrasonic Detection: Next-Gen LAM Defect Finder! #Sciencefather #researchawards

Laser Additive Manufacturing (LAM) is an advanced technique that uses high-energy lasers to build complex metal parts layer by layer with high precision, efficiency, and minimal material waste. It has wide applications in industries such as aerospace, medical, and automotive. However, the LAM process faces challenges due to non-equilibrium thermodynamics, which often cause metallurgical defects like cracks and pores. If not detected during printing, these flaws can grow and affect the final part's quality and structural integrity, limiting the broader adoption of LAM.

To ensure quality and reliability, several online nondestructive testing (NDT) methods are used, including X-ray computed tomography, infrared thermography, optical photography, structured light imaging, and ultrasonic detection. Among them, laser ultrasonic testing stands out due to its non-contact, high-temperature resistance, and ability to generate multiple wave modes in one pulse, which helps identify both surface and internal defects. Recent studies have shown the potential of laser ultrasonics in real-time monitoring of mechanical properties and defect detection during LAM processes.

Despite advancements, challenges such as surface roughness and environmental noise reduce the clarity of ultrasonic signals. Post-processing methods like SAFT and TFM improve resolution but are time-consuming and require heavy data storage. To address these issues, this study introduces a novel ultrasonic imaging method—Variable Time Window Intensity Mapping (VTWIM) with adaptive 2σ thresholds. This approach adapts to changing noise levels and enables rapid, accurate detection of submillimeter defects in real time, demonstrating significant promise for improving LAM quality control.

 International Conference on Computer Vision

The International Research Awards on Computer Vision recognize groundbreaking contributions in the field of computer vision, honoring researchers, scientists and innovators whose work has significantly advanced the domain. This prestigious award highlights excellence in fundamental theories, novel algorithms and real-world applications, fostering progress in artificial intelligence, image processing and deep learning.

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