基于超声导波和Y-Net的复合材料胶接质量检测研究  

Research on bonding quality detection of adhesively bonded structure in composite plates based on guided wave and Y-Net

作　　者：张晓妍 曾周末[1] 李健[1] 陈世利[1] 刘洋[1] ZHANG Xiaoyan;ZENG Zhoumo;LI Jian;CHEN Shili;LIU Yang(School of Precision Instrument and Opto-electronics Engineering,Tianjin University,Tianjin 300072,China)

机构地区：[1]天津大学精密仪器与光电子工程学院,天津300072

出　　处：《复合材料科学与工程》2024年第5期92-99,共8页Composites Science and Engineering

基　　金：国家自然科学基金(61773283)。

摘　　要：为实现复合材料胶接结构界面粘接质量的检测,本文提出了一种基于导波检测技术和Y-Net卷积神经网络的界面弱粘接缺陷反演成像方法。计算了超声导波在复合材料胶接结构中传播的相速度频散曲线和波结构,指出了适于实际检测的导波激励频率和激发模态;创建了基于有限元仿真的数据集,将缺陷导波检测数据及概率损伤成像(RAPID)结果作为输入,真实胶接质量结果作为标签数据,对Y-Net进行了搭建、训练、验证和泛化能力测试,并应用结构相似指数(SSIM)和峰值信噪比(PSNR)定量评估了Y-Net的反演能力;搭建了实验系统,开展了复合材料胶接板检测实验。结果表明,本文所提方法可以弱粘接缺陷反演成像方式实现胶接质量检测,成像结果可准确且高质量地表征弱粘接缺陷的位置、形状、大小和弱粘接程度等多个特性。In order to detect the interface bonding quality of the adhesively bonded structure in composite plates,this paper proposed an inversion imaging method for interface weak bonding defects based on ultrasonic guided wave detection technology and Y-Net convolutional neural network.In this paper,the phase velocity dispersion curve and wave structure of the ultrasonic guided wave propagating in adhesively bonded structure in composite plates were calculated,from which the optimal excitation frequency and excitation mode suitable for detection were selected.A data set based on finite element simulation was created.The Y-Net was built,trained,verified and generalized ability tested,while the defect guided wave detection data and reconstruction algorithm for probabilistic inspection of defects(RAPID) imaging results were used as input,and the real bonding quality results were used as label data.Structural similarity index measure(SSIM) and peak signal-to-noise ratio(PSNR) were used to evaluate the inversion ability of Y-Net quantitatively.The experimental system was built,and the adhesively bonded structure in composite plates detection experiment was carried out.The results show that the method proposed in this paper can realize the bonding quality detection by means of inversion imaging of weak bonding defects,and the imaging results can accurately and high-quality characterize the position,shape,size and degree of weak bonding of weak bonding defects and other characteristics.

关 键 词：复合材料 超声导波 卷积神经网络 弱粘接缺陷 反演成像 

分 类 号：TB332[一般工业技术—材料科学与工程]