Improving the signal-to-noise ratio of the laser ultrasonic synthetic aperture focusing technique to detect submillimeter internal defects using echo array similarity.

Laser ultrasonic imaging is a promising technique for structural health monitoring because it is noncontact and nondestructive. However, this technique will only find more industrial applications if it has a high signal-to-noise ratio (SNR) and short data acquisition time. In existing delay-and-sum algorithms, such as the synthetic aperture focusing technique (SAFT) and the total focusing method, a higher SNR requires more A-scan signals, which mean a longer data acquisition time. It is difficult for these algorithms to consider these two aspects simultaneously. Thus, in this study, we propose a post-processing algorithm that extracts neglected information from laser ultrasonic B-scan data to improve the SNR of the SAFT without increasing the data acquisition time. The SNR was increased by multiplying the SAFT image intensity with the echo array similarity defined using the directivity and echo shape information of laser ultrasound. In experiments, SNR was increased from 4.1 dB to 31.3 dB for two submillimeter defects having a diameter of 0.5 mm and depth of 15 mm. Deeper defects can be detected because of the improved SNR. In this study, two submillimeter defects with a depth of 30 mm were detected. Compared with existing delay-and-sum algorithms, the proposed algorithm performs well in terms of both SNR and data acquisition time, which can promote its use in more industrial applications.