文献类型：期刊文献

中文题名：基于小波变换的扩散焊超声C图像融合算法

英文题名：Ultrasonic C Image Fusion Algorithm for Diffusion Welding Based on Wavelet Transform

作者：常青[1];杨程伟[1];罗彬杰[1];李细峰[2]

机构：[1]华东理工大学信息科学与工程学院,上海200237;[2]上海交通大学塑性成形技术与装备研究院,上海200030

年份：2023

卷号：44

期号：4

起止页码：54

中文期刊名：郑州大学学报（工学版）

外文期刊名：Journal of Zhengzhou University（Engineering Science）

收录：CSTPCD;;北大核心:【北大核心2020】；

基金：国家自然科学基金资助项目(51875350)。

语种：中文

中文关键词：扩散焊;超声C扫描;小波变换;引导滤波;图像融合

外文关键词：diffusion welding;ultrasound C scan;wavelet transform;guided filtering;image fusion

摘要：为了提高钛合金扩散焊界面微小缺陷的检测能力,提出一种基于小波变换的超声C图像融合算法,综合多幅图像中的缺陷信息,重构出包含微小缺陷在内的超声C图像。利用小波变换将待融合的超声C图像分解为低频和高频部分,并根据高、低频系数的不同特征,对高、低频系数进行差异化融合处理,对融合后的系数使用小波逆变换得到融合图像;为了提高图像对比度、丰富图像细节信息,使用改进的同态滤波器对融合图像进行增强,从而获得结果图像。制备不同类型的人工缺陷试样进行测试,并将所提算法和常规超声C扫描检测的缺陷长度进行定量比较。实验结果表明:对于线形微小缺陷和弱结合缺陷,使用所提算法重构的超声C图像的平均误差分别为2 mm和4.2 mm,常规超声C扫描的平均误差分别为8 mm和9.5 mm。所提算法重构的超声C图像能够更为准确地反映出缺陷信息。
In order to improve the detection ability on tiny defects at the interface of diffusion welding of titanium alloys,an ultrasonic C image fusion algorithm based on wavelet transform was proposed.Firstly,the ultrasonic C image to be fused was decomposed into low-frequency and high-frequency parts by wavelet transform,and the high and low frequency coefficients were differentiated and fused according to the different characteristics of the high and low frequency coefficients,and the inverse wavelet transform was used for the fused coefficients to get the fused image.Finally,in order to improve the contrast of the image and enrich the details of the image,the improved homomorphic filter was used to enhance the fusion image,so as to obtain the fusion result image.By preparing different types of artificial defect samples for testing,and quantitatively comparing the length of defects detected by the algorithm in this study and conventional ultrasonic C scan,the experimental results showed that for small linear defects and weak bond defects,the ultrasonic C reconstructed by the algorithm in this study could be used.The average errors of the images were 2 mm and 4.2 mm,respectively,and the average errors of conventional ultrasound C scan was 8 mm and 9.5 mm,respectively.Therefore,the ultrasonic C image reconstructed by the proposed algorithm in this study could reflect the defect information more accurately.