A metal internal microdamage imaging method based on a three-stage laser ultrasonic bulk wave signal processing strategy

Résumé fourni par la source

Abstract To address issues such as wave mode aliasing, severe surface wave interference, and insufficient imaging accuracy in traditional laser ultrasonic testing, this paper presents a three-stage laser ultrasonic imaging method that integrates principal component subtraction (PCS), delay multiply and sum (DMAS), and minimum variance (MV). First, PCS preprocessing is used to suppress common interference, such as surface waves, and highlight bulk wave signals. Then, DMAS nonlinear summation is employed to enhance the contrast of defect echoes. Finally, the MV algorithm is used to optimize the focusing effect and improve imaging resolution. A simulation model of aluminum alloy with hole defects is established in COMSOL to analyze bulk wave propagation characteristics and verify the method’s effectiveness. Additionally, an annular laser excitation is introduced to enhance bulk wave focusing intensity and defect response sensitivity. An experimental platform consisting of a pulsed laser and a laser Doppler vibrometer is used to detect aluminum alloy samples with millimetre-scale through-hole defects. Both simulation and experimental results demonstrate that the proposed method effectively suppresses noise and artifacts, accurately reconstructs the spatial location of defects at varying depths with an average positioning error of 1.75 mm. Furthermore, using a dual-probe synchronized scanning strategy significantly improves data acquisition efficiency compared to traditional full matrix capture (FMC) methods. Results show that the proposed PCS–DMAS–MV pipeline achieves imaging quality comparable to FMC-based processing while significantly improving inspection efficiency. This approach holds significant engineering application value in the high-precision detection of micro-defects in reusable aerospace metallic structures.

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