Abstract
The laser ultrasonic (LU) technique has the advantages of a wide frequency band, small non-detection zone, high resolution and non-contact compared to conventional ultrasonic testing, which makes it potential for on-line inspection of the wire arc additive manufacturing (WAAM) process. To investigate the influence of surface profile on the LU inspection of WAAM defects, multiscale analysis was adopted in the mathematical characterization of the sample surface profile. Finite Element (FE) models of LU inspection of WAAM defects with different surface profiles were established using COMSOL software. The propagation of acoustic waves and their interaction with surface profile and defects were numerically analyzed. The LU inspection methods, that is, superficial crack detected by through-transmission of Rayleigh wave and internal hole detected by pulsed-echo of shear wave were put forward. A set of WAAM samples with different surface topographies was manufactured by the robotic gas metal arc welding (GWAM) system through varying the process parameters and filler materials. LU inspection experiments were conducted to obtain B-scan images and A-scan signals of the defects in these samples. The experimental results indicate that surface roughness has a significant effect on the signal-to-noise ratio (SNR) of internal through hole detection, and surface waviness has a significant effect on the sensitivity of superficial crack detection. The experimental results are consistent with the numerical results, which validate the proposed FE model. The proposed FE model can be used for the quantitative study of the influence of WAAM sample profile on the LU inspection. Furthermore, it is also a guidance for the formulation of key process parameters in LU inspection, such as the maximum generating-receiving laser distance and the laser’s layout. At last, a robotic LU inspection system was built and preliminarily achieved the automatic inspection of a WAAM part. This research provides a theoretical basis for the on-line application of LU techniques in WAAM process monitoring.
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