Abstract

The identification and localization of small defects are among the main objectives of ultrasonic non-destructive testing (NDT). In particular, the inspection of polycrystalline materials remains a challenge due to ultrasonic attenuation and backscatter noise caused by grain scattering. An adaptive ultrasonic array imaging algorithm is proposed in this paper, which is capable of enhancing the signal-to-noise ratio (SNR) of small subwavelength defects. The proposed approach adopts an iterative optimization procedure based on sequential backward selection, and is termed receiver optimized total focusing method (ROTFM). ROTFM is formulated in a baseline subtraction (BS) setting, and it is shown to achieve higher defect SNRs compared to TFM results obtained by directly applying the BS method to measured array data. More importantly, the performance of the proposed ROTFM is robust to time and spatial misalignments, and hence, it alleviates the need for complex compensation schemes when performing imaging computations. Compared to conventional TFM, ROTFM achieved an average SNR improvement of 3.41 dB and 6.05 dB in experiments for four test defects (cracks and holes of sizes 0.5 mm and 1 mm) at the frequencies of 5 MHz and 7 MHz, respectively.

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