A method for automatic identification of damaged areas of aerospace composite materials

Abstract

The invention discloses an automatic identification method for the damaged area of ​​aerospace composite materials, which includes: extracting the typical transient thermal response of each type of defect; obtaining an infrared reconstruction image; obtaining a low-quality infrared reconstruction image; obtaining noise removal and retaining details 1. Keep the weight coefficients of the three segmentation performances of the edge; construct the infrared image segmentation function; obtain the weight coefficients of the objective functions for each segmentation performance; construct the full-pixel infrared image segmentation objective function, and use the segmentation model to reconstruct the full-pixel infrared image Perform image segmentation; implement infrared full-pixel image segmentation in the image segmentation layer to obtain segmented images. The present invention utilizes multi-objective optimization theory to segment defects in infrared reconstructed images, and constructs objective functions for noise and edge blur problems to improve segmentation accuracy, which not only ensures a high detection rate of defects but also reduces false detection rates, effectively The damaged defect area in the reconstructed image is extracted, which is convenient for quantitative research of complex defects.

Description

technical field [0001] The invention belongs to the technical field of aerospace vehicle damage detection and maintenance support, and more specifically, the invention relates to an automatic identification method for damage areas 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 and honeycomb structure materials, have increasingly become the focus of aerospace research. hotspot. At the same time, composite materials with special functional uses, such as stealth coating materials, carbon-based heat-resistant 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 composite materials, s...

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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