GFRP损伤X射线和超声无损检测的融合方法
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吉林大学仪器科学与电气工程学院长春130061

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TH391;TN06

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吉林省教育厅科研项目(JJKH20231160KJ)、吉林大学大学生创新创业训练计划项目(S202210183473)资助


Fusion method of X-ray and ultrasonic nondestructive detection of GFRP
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College of Instrument Science and Electrical Engineering, Jilin University, Changchun 130061, China

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    摘要:

    针对玻璃纤维复合材料(glass fiber reinforced plastic,GFRP)无损检测中X射线和超声技术检测效果不佳的问题,利用X射线图像的高分辨率和超声图像的高对比度特点进行互补成像融合,通过整合X射线图像的缺陷边缘细节信息和超声图像的高对比度大致轮廓信息,形成新图像以提高缺陷显示效果。将基于十字扇形滤波器的频域算法用于去除X射线图像中的横、竖条纹噪声,采用形态学滤波算法去除超声图像中的椒盐噪声,并提出了基于区域分割和静态小波变换的图像融合算法,用以融合X射线和超声图像特征。测试结果表明,相较于处理前的X射线和超声图像,融合后的图像标准差SD值平均提高154.1%,熵H值平均降低92.2%,缺陷检测图像对比度有所提高且边缘细节清晰。算法有效除去了两种图像中的条纹噪声和椒盐噪声,能改善X射线图像对比度低、超声图像分辨率差的不足,为复合材料缺陷检测提供了新思路。

    Abstract:

    Aiming at the problem of poor effect of X-ray and ultrasonic technologies in non-destructive detection of glass fiber reinforced plastic (GFRP), characteristics of high resolution of Xray images and high contrast of ultrasound images are used for complementary imaging fusion, and by integrating the detail information of the defect edge of X-ray images and the high contrast outline information of ultrasonic images, new images are formed to improve the defect display effect. The frequency domain algorithm based on cross sector filter is used to remove the horizontal and vertical fringe noise of X-ray images, the morphological filtering algorithm is used to remove the salt and pepper noise of ultrasonic images, and the image fusion algorithm based on region segmentation and static wavelet transform is proposed to fuse X-ray and ultrasonic image traits. The test results show that the standard deviation SD of the fused images is increased by 154.1% on average, the entropy H is decreased by 92.2% on average, and the contrast of defect detection images is higher and the edge details are clear. The algorithm can effectively remove the fringe noise and pepper and salt noise in the two kinds of images, and can effectively improve the weakness of low contrast of X-ray images and poor resolution of ultrasonic images, and provide a new idea for the defect damage detection of composite materials.

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张瑾,李洁,魏子璇,王晓璐,张莉. GFRP损伤X射线和超声无损检测的融合方法[J].电子测量与仪器学报,2024,38(8):169-177

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  • 在线发布日期: 2024-10-31
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