Ultrasonic imaging methods show significant advantages in detecting internal defects of composite crystalline materials. For polymer-bonded explosives (PBXs) with highly filled crystalline particles, the strong acoustic aenuation caused by their heterogeneous crystalline structure leads to low signal-to-noise ratios (SNRs) in the full matrix capture (FMC) signals and strong background noise in reconstructed images. To realize the high-SNR imaging of defects in PBXs, this paper is the first to schematically reorganize the nonlinear post-process algorithms which have the potential to realize high-SNR imaging of defects in crystalline particle-filled explosives. Six kinds of beamforming algorithms (DAS, F-DMAS, BB-DMAS, DMAS3, L-DMAS, and DS-DMAS) were applied to the same FMC data to reconstruct the images of prefabricated side-drilled holes (SDHs) in PBXs. The image quality in terms of SNR, lateral and axial resolution, and calculation efficiency was compared and evaluated quantitatively. The experimental results show that the nonlinear beamforming algorithms showed significant improvements in SNR and resolution. In particular, L-DMAS and DS-DMAS exhibited excellent imaging capability in SDH defect detection compared to the other algorithms, with effective suppression of crystalline structural noise.
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