Ultra-fast laser ultrasonic imaging method for online inspection of metal additive manufacturing

Abstract

In this paper, an ultra-fast laser ultrasonic imaging method is proposed to provide an efficient online monitoring of additive manufacturing (AM) processing. The innovations of the proposed ultrafast imaging method in this research mainly include two parts. Firstly, multi-circle combined scanning strategy and defect location algorithm is constructed to improve the detection efficiency. Secondly, a surface wave focusing algorithm (SWFA) is established to solve the problem of low SNR induced by rough surface signals. The AM samples containing four types of surface and inner defects are designed and manufactured to verify the detectability and quantitative accuracy of the proposed method. Systematically comparisons between our proposed method with the traditional laser ultrasonic imaging are also discussed. The result indicated that the proposed ultra-fast imaging method is efficient for detecting the surface and sub-surface defects in the condition of low SNR caused by rough surface of AM components. The minimum detectable defect reaches 0.1 mm and the quantitative error could low down to 6.46% when the defect size is larger than 0.2 mm. Compared with the C-scan imaging method, the method proposed in this paper can improve the scanning efficiency of single-layer inspection by more than 300%, which is meaningful to improve the efficiency of metal additive manufacturing.