Defect detection method of aircraft engine parts based on X-ray images

By sub-region segmentation and optimal gamma value calculation on the X-ray images of aircraft engine components, gamma transformation is performed to improve image contrast, which solves the problem of poor X-ray image enhancement effect in the prior art and improves the accuracy of defect detection.

CN119693369BActive Publication Date: 2025-04-18SHAANXI YINHAN AEROSPACE TECH CO LTD
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Patent Information

Application Number
CN202510205984.5
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-02-25
Publication Date
2025-04-18
Estimated Expiration
2045-02-25

AI Technical Summary

Technical Problem

When the prior art enhances the X-ray image of aircraft engine components, it cannot satisfy the enhancement effect of different edges and details at the same time, resulting in poor enhancement effect of the X-ray image and affecting the accuracy of defect detection.

Method used

By segmenting the X-ray image into multiple sub-regions, gamma transformation is calculated and used for the optimal gamma value of each sub-region, the feature contrast of the image is improved, thereby improving the accuracy of defect detection.

Benefits of technology

By calculating the optimal gamma value of each sub-region and performing gamma transformation, the characteristic contrast of the X-ray image is significantly improved, and the accuracy of aircraft engine component defect detection is further improved.

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Abstract

The present invention relates to the field of defect detection, and in particular to an aerospace engine component defect detection method based on X-ray images, the method comprising: obtaining an X-ray image of a component, dividing the X-ray image into a plurality of sub-regions; calculating an optimal gamma value of each sub-region, performing a gamma transformation on each sub-region using the optimal gamma value to obtain an optimal X-ray image, and inputting the optimal X-ray image into a preset detection model to obtain the type of component defect. The present invention can improve the accuracy of component defect detection results.
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Citation Information

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