基于EIT的CFRP层合板缺陷可视化检测

Visualization detection of CFRP laminate defects based on EIT

利用碳纤维复合材料(CFRP)的自传感特点及结构损伤的电学敏感特性,提出基于电阻抗断层成像(EIT)的检测方法,以实现非侵入、无辐射、低成本的快速无损结构健康监测。考虑CFRP层合板各向异性电学特点,利用有限元分析软件COMSOL构建实验模型,求解分析不同激励模式,并从多种评价指标进行评估,进而获取适用于开放式环状电极分布的最优激励模式为间三激励。为提高EIT系统的成像质量,对基于L1正则化的成像算法进行研究。实验结果表明:与EIT中常用的Landweber、Tikhonov等算法相比,该算法提高了成像质量和被测物体边缘分辨率。

Based on the self-sensing characteristics of carbon fiber and the electrical sensitivities of structural damage,a testing method based on electrical impedance tomography(EIT)is proposed to realize non-invasive,radiation-free,low-cost,non-destructive structural health monitoring.Considering the anisotropic electrical characteristics of CFRP laminates,the experimental model is constructed by using finite element analysis software COMSOL,and different excitation modes are analyzed and evaluated from various evaluation indexes to obtain the optimal excitation mode suitable for open annular electrode distribution,three incentives.In order to improve the imaging quality of EIT system,the imaging algorithm based on L1 regularization is studied.The experimental results show that compared with the commonly used algorithms such as Landweber and Tikhonov in EIT,the algorithm improves the imaging quality and the edge resolution of the measured object.