To reduce noise and background distractions, we propose a detection algorithm based of Gaussian curvature filtering (GCF) and partial sum of singular values (PSSV). Above all, aiming at the false alarms caused by noise, using the prior knowledge of natural image have the characteristics of approximate developable, GCF utilizes the variation model to obtain an approximately noise-free image. Secondly, we adopt PSSV to suppress the background by pointing out that the reason why Robust PCA is inaccurate in the background estimation is that the hypothesis at the edge of the background does not match the reality, and we present a model solving algorithm on the ground of imprecise augmented Lagrangian multiplier method (IALM). At last, we use an adaptive threshold segmentation algorithm to segment the target. The model has better noise clutter suppression and detection accuracy than other representative methods.
Thin-wall specimens of near-β titanium alloy Ti-55531 were manufactured by laser melting deposition (LMD), followed by the post-processing using the electroshock treatment (EST). The results show that the microstructure of the as-manufactured alloy is mainly composed of fine columnar grains and equiaxed grains, showing a unique structure of alternating short columnar grains-equiaxed grains-short columnar grains. EST is shown to change the microstructure and grain size of the specimens. Besides phase variation, EST can also reduce the orientation concentration and weaken the texture. Meanwhile, the lattice constant and the microscopic strain were increased after EST. From the tensile test results, the yield strength and tensile strength increased, and the elongation decreased after EST. The results showed that EST is an effective approach for optimizing the microstructure and improving the mechanical properties of LMD near-β titanium alloy.
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