A segmentation enhancement method for damage detection images of aerospace composite materials

Abstract

The invention discloses a method for segmentation and strengthening of damage detection images of aerospace composite materials, including: extracting typical transient thermal responses of defects; obtaining infrared reconstruction images; using multi-objective measurement to remove noise, preserve details, and preserve edges. According to the segmentation performance, the weight coefficient of each segmentation performance is obtained; the infrared image segmentation function data is constructed under the guidance of three purposes of noise removal, detail preservation and edge preservation; the weight coefficient of the objective function is obtained; the reconstructed full-pixel infrared image Perform image segmentation; realize infrared full-pixel image segmentation in the image segmentation layer to obtain a segmented image of defects. The invention uses the multi-objective optimization theory to segment the damage defect area in the infrared reconstructed image, constructs objective functions for the noise problem and the edge blur problem respectively, improves the area segmentation accuracy, reduces the false detection rate, and effectively enhances the readability of the damage defect area. , which facilitates the quantitative study of complex defects.

Description

technical field [0001] The invention belongs to the technical field of damage detection and maintenance support for aerospace vehicles, and more particularly, the invention relates to a segmentation and enhancement method for damage detection images of aerospace composite materials. Background technique [0002] With the urgent need for weight reduction of aerospace vehicles, lightweight structural materials with excellent mechanical properties, especially lightweight composite materials represented by high-strength / high-modulus carbon fiber composite materials, honeycomb structural materials, etc., have increasingly become the focus of aerospace research. hot spot. At the same time, composite materials with special functional purposes, such as stealth coating materials, carbon-based heat-proof materials and other functional composite materials are also more widely used in the aerospace field. However, in the process of manufacturing, assembly processing or real-time use of...

AI Technical Summary

Problems solved by technology

On the one hand, if the defect detection rate is improved to a certain extent under the premise of fully satisfying the preservation of details, the noise is also retained, which is easy to cause misjudgment of defect recognition, resulting in an increase in the false detection rate

On the other hand, if only the overall denoising of the image is satisfied, the size of the damage defects caused by the impact of tiny debris is small and the number is large, and these tiny defects similar to the noise will be removed together with the denoising process, reducing the damage of defects. Detection rate and detection accuracy

Therefore, the above-mentioned conventional segmentation method is applied to the object of the present invention, that is, the infrared reconstructed image of the defect. Since the false detection rate and detection rate of the defect cannot be weighed, the segmentation effect is not satisfactory.

Especially considering that the infrared thermal image reflects the thermal radiation information of the test piece, which is easily affected by the environment, imaging links, etc., so that the background noise of the obtained infrared reconstruction image of defects is large.

At the same time, due to the difference in surface thermal radiation capabilities between the defect area and the background area, the edges of the infrared reconstructed image of the defect are not smooth enough, and the division of edge areas is not clear enough, which is not conducive to image segmentation

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