基于梯度阈值的太赫兹时域信号自适应稀疏算法  

Adaptive sparse algorithm for terahertz time domain signals based on gradient threshold

作　　者：秦丽丽 李丽娟 任姣姣[1,2,3] 顾健 熊伟华[1,2] 张丹丹 祝莉莉[1,2] 张霁旸 薛竣文 江柏红[4] 高增华 Qin Lili;Li Lijuan;Ren Jiaojiao;Gu Jian;Xiong Weihua;Zhang Dandan;Zhu Lili;Zhang Jiyang;Xue Junwen;Jiang Baihong;Gao Zenghua(Key Laboratory of Optoelectronic Measurement and Optical Information Transmission Technology,Ministry of Education,School of Opto-Electronic Engineering,Changchun University of Science and Technology,Changchun 130022,China;National Demonstration Center for Experimental Opto-Electronic Engineering Education,School of Opto-Electronic Engineering,Changchun University of Science and Technology,Changchun 130022,China;Zhongshan Research Institute,Changchun University of Science and Technology,Zhongshan 528400,China;Aerospace Special Materials and Processing Technology Institute,Beijing 100074,China)

机构地区：[1]长春理工大学光电工程学院光电测控与光信息传输技术教育部重点实验室,吉林长春130022 [2]长春理工大学光电工程学院光电工程国家级实验教学示范中心,吉林长春130022 [3]长春理工大学中山研究院,广东中山528400 [4]航天特种材料及工艺技术研究所,北京100074

出　　处：《红外与激光工程》2023年第4期313-324,共12页Infrared and Laser Engineering

基　　金：吉林省科技发展计划项目(20220508032RC);中山市第二批社会公益与基础研究项目(2022B2012)。

摘　　要：胶接结构广泛应用于航空航天等国防领域,但在工艺制作及使用过程可能会产生胶接界面脱粘缺陷和损伤,由于太赫兹无损检测技术对非金属材料良好的穿透性能,已被广泛应用于复合材料的无损检测中,太赫兹无损检测技术在多层胶接结构样件胶层内部缺陷的无损检测方面具有较大优势。利用反射式太赫兹时域光谱系统检测多层胶接结构样件,得到的具有样件内部材料信息的太赫兹时域信号,但信号中还包含了大量的冗余特征和噪声等无效信息,这些无效信息大大降低了信号处理和分析效率。针对这一问题,文中提出了基于二阶梯度法提取太赫兹时域信号有效特征,以飞行时间误差为限制条件基于信号的时域特征自适应确定阈值,稀疏太赫兹时域信号,减少信号中冗余无效信息,实现太赫兹时域信号的有效压缩。然后,通过二值化图像分割识别多高斯恢复信号和太赫兹时域光谱系统检测信号的太赫兹图像缺陷区域。最后,制备具有脱粘缺陷的多层胶接结构样件,开展太赫兹无损检测实验。结果表明:文中算法的数据压缩率达到了81%,相比传统压缩算法离散余弦变换提高了59%,相比主成分分析算法提高了75%,相比K-SVD字典学习算法提高了26%,缩短了约80%的数据计算时间,减小了约95%数据存储空间占用,且缺陷识别偏差不超过0.05。文中算法极大地提高了数据处理和分析效率,保证了缺陷识别的精度。Objective Bonding structure is widely used in aviation,aerospace,national defense and other fields.But during service,the bond interface may appear disbonding defects or damage,seriously reducing the bearing capacity of the structure and affecting the structure safety.Terahertz nondestructive testing technology is widely used in the nondestructive test of composite materials.Terahertz time-domain spectroscopy technology can effectively realize the nondestructive test and identification of internal defects of multilayer adhesives.However,the terahertz detection signal carries a large number of invalid redundant features,noise and other invalid information.With the gradual increase of detection data,the redundant and invalid information in the data,and the workload of data processing are also increasing.A large amount of invalid information not only consumes a lot of data processing and analysis time,but also brings great interference to the subsequent signal analysis work such as defect identification.To solve this problem,a gradient threshold adaptive sparse compression algorithm is proposed based on time-domain characteristics of terahertz signals with multi-layer adhesive structures.Methods The gradient threshold adaptive sparse model is established.Effective time-domain features of terahertz signals were extracted using the second-order gradient(Fig.3),and the time-domain features of signals were used as constraints to determine the threshold sparse time-domain signals based on the time-domain features of signals,and the terahertz signals were recovered by the multi-Gaussian fitting function(Fig.4).The compression performance of the algorithm was evaluated according to the compression ratio,relative root mean variance and correlation coefficient,and the data processing time and memory occupied space were used to characterize the compression efficiency of the algorithm.Results and Discussions Terahertz detection signals were divided into normal signals and defective signals(Fig.5),and signal characteristic peak

关 键 词：太赫兹时域光谱 稀疏表示 特征提取 自适应阈值 多层胶接结构 

分 类 号：O433.4[机械工程—光学工程]