Volume 40 Issue 3
Mar.  2023
Turn off MathJax
Article Contents
WANG Qiang, ZHAO Boyan, LIU Qiuhan, et al. Intelligent detection of delamination defect in curved structural quartz fiber reinforced polymer composites using terahertz technology[J]. Acta Materiae Compositae Sinica, 2023, 40(3): 1785-1796. doi: 10.13801/j.cnki.fhclxb.20220516.001
Citation: WANG Qiang, ZHAO Boyan, LIU Qiuhan, et al. Intelligent detection of delamination defect in curved structural quartz fiber reinforced polymer composites using terahertz technology[J]. Acta Materiae Compositae Sinica, 2023, 40(3): 1785-1796. doi: 10.13801/j.cnki.fhclxb.20220516.001

Intelligent detection of delamination defect in curved structural quartz fiber reinforced polymer composites using terahertz technology

doi: 10.13801/j.cnki.fhclxb.20220516.001
  • Received Date: 2022-03-17
  • Accepted Date: 2022-05-01
  • Rev Recd Date: 2022-04-21
  • Available Online: 2022-05-16
  • Publish Date: 2023-03-15
  • In order to explore an intelligent means of detecting delamination defects in airborne warning and control system radomes made of quartz fiber reinforced polymers (QFRP), a reflective terahertz time-domain spectroscopy system based on fiber coupling was built by combining a cooperative robot. The signal noise ratio dynamic range is about 60 dB after testing. Terahertz nondestructive testing of curved structural QFRP sample with pre-buried simulated delamination defects was performed using the build system. The internal pre-buried defects were visually identified in the reflected terahertz images obtained from different scanning areas. An improved YOLOv4 algorithm was used to obtain 90.18% accuracy and 91.26% recall in automatic defect identification, which were 3.37% and 4.01% higher than the original YOLOv4 algorithm, respectively. The small target defects can also be recognized well. This experiment enriches the design and detection of airborne warning and control system radome sample, explores the detection of curved structural QFRP sample using terahertz imaging method and provides a new intelligent nondestructive testing method of airborne warning and control system radomes detection, which has the value of engineering application.


  • loading
  • [1]
    曹晨. 预警机发展七十年[J]. 中国电子科学研究院学报, 2015, 10(2):113-118, 137. doi: 10.3969/j.issn.1673-5692.2015.02.001

    CAO Chen. Developments of AEW system for 70 years[J]. Journal of CAEIT,2015,10(2):113-118, 137(in Chinese). doi: 10.3969/j.issn.1673-5692.2015.02.001
    王飞, 石佩洛. 树脂基复合材料在雷达天线罩领域的应用及发展[J]. 宇航材料工艺, 2017, 47(2):10-13.

    WANG F, SHI P L. Application and development of resin matric composites for radomes[J]. Aerospace Materials and Technology,2017,47(2):10-13(in Chinese).
    赵云峰. 先进纤维增强树脂基复合材料在航空航天工业中的应用[J]. 军民两用技术与产品, 2010(1):4-6. doi: 10.3969/j.issn.1009-8119.2010.01.002

    ZHAO Y F. Application of advanced fiber reinforced resin matrix composites in aerospace industry[J]. Dual Use Technologies & Products,2010(1):4-6(in Chinese). doi: 10.3969/j.issn.1009-8119.2010.01.002
    方芳. 先进复合材料在雷达上的应用[J]. 电子机械工程, 2013, 29(1):27-31, 54. doi: 10.3969/j.issn.1008-5300.2013.01.007

    FANG F. Application of advanced composite to radar[J]. Electro-Mechanical Engineering,2013,29(1):27-31, 54(in Chinese). doi: 10.3969/j.issn.1008-5300.2013.01.007
    肖卫东, 黄一清, 蔡正燕. 潜用雷达天线罩材料及成型工艺研究[J]. 造船技术, 2013(5):24-25, 29. doi: 10.3969/j.issn.1000-3878.2013.05.006

    XIAO W D, HUANG Y Q, CAI Z Y. Research on materials and forming process of submarine ra-dome[J]. Marine Technology,2013(5):24-25, 29(in Chinese). doi: 10.3969/j.issn.1000-3878.2013.05.006
    SHIN H J, PARK J Y, HONG S C, et al. In situ non-destructive evaluation of an aircraft UHF antenna ra-dome based on pulse-echo ultrasonic propagation imaging[J]. Composite Structures,2017,160:16-22. doi: 10.1016/j.compstruct.2016.10.058
    严罡. 基于介电常数调制的雷达罩蜂窝积水缺陷的检测技术研究[D]. 南京: 南京航空航天大学, 2017.

    YAN G. The Research on detection technology for measuring water in curved surface radome honey-comb based on the dielectric constant modulation[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2017(in Chinese).
    FABIAN F, KARL M, BESSEM B, et al. Terahertz radome inspection[J]. Photonics, 2018, 5(1): 1-10.
    WANG Y, CHEN Z, ZHAO Z, et al. Restoration of te-rahertz signals distorted by atmospheric water vapor absorption[J]. Journal of Applied Physics,2009,105(10):3667.
    许景周, 张希成. 太赫兹科学技术和应用[M]. 北京: 北京大学出版社, 2007.

    XU J Z, ZHANG X C. Terahertz science and technology and applications[M]. Beijing: Peking University Press, 2007(in Chinese).
    WANG Q, LI X, CHANG T, et al. Terahertz spectroscopic study of aeronautical composite matrix resins with different dielectric properties[J]. Optik,2018,168:101-111.
    张瑾. 纤维增强复合材料的太赫兹无损检测研究[D]. 长春: 吉林大学, 2016.

    ZHANG J. Nondestructive evaluation of fiber-reinforced polymer composite using terahertz technology[D]. Changchun: Jilin University, 2016(in Chinese).
    邢砾云. 航空泡沫芯材及夹层结构的太赫兹无损检测研究[D]. 长春: 吉林大学, 2016.

    XING L Y, Nondestructive testing of aviation foam core materials and sandwich structure using terahertz time domain spectroscopic imaging technology[D]. Changchun: Jilin University, 2016(in Chinese).
    KIM D H, RYU C H, PARK S H, et al. Nondestructive evaluation of hidden damages in glass fiber rein-forced plastic by using the terahertz spectroscopy[J]. International Journal of Precision Engineering and Manufacturing-Green Technology,2017,4(2):211-219. doi: 10.1007/s40684-017-0026-x
    WANG Q, LI X Y, CHANG T, et al. Nondestructive imaging of hidden defects in aircraft sandwich composites using terahertz time-domain spectroscopy[J]. Infrared Physics & Technology, 2019, 97: 326-340.
    张丹丹, 任姣姣, 李丽娟, 等. 玻璃纤维蜂窝复合材料的太赫兹无损检测技术[J]. 光子学报, 2019, 48(2):0212002. doi: 10.3788/gzxb20194802.0212002

    ZHANG D D, REN J J, LI L J, et al. Terahertz non-destructive testing technology for glass fiber honeycomb compo-sites[J]. Acta Photonica Sinica,2019,48(2):0212002(in Chinese). doi: 10.3788/gzxb20194802.0212002
    周桐宇, 李丽娟, 任姣姣, 等. 基于FDTD的玻璃纤维增强复合材料脉冲太赫兹无损检测[J]. 光学学报, 2020, 40(12):196-204.

    ZHOU T Y, LI L J, REN J J, et al. Pulsed terahertz nondestructive testing of glass fiber reinforced plastics based on FDTD[J]. Acta Optica Sinica,2020,40(12):196-204(in Chinese).
    王赫楠, 任姣姣, 张丹丹, 等. 基于连续小波变换的玻璃纤维增强树脂复合材料太赫兹特征增强及缺陷成像[J]. 复合材料学报, 2021, 38(12):4190-4197.

    WANG H N, REN J J, ZHANG D D, GU J, ZHANG J Y, LI L J. Glass fiber reinforced polymer terahertz feature enhancement and defect imaging based on continuous wavelet transform[J]. Acta Materiae Compositae Sinica,2021,38(12):4190-4197(in Chinese).
    李萌, 何明霞, 田震. 太赫兹时域频谱信噪比分析与规范性研究[J]. 光谱学与光谱分析, 2012, 32(3):606-609. doi: 10.3964/j.issn.1000-0593(2012)03-0606-04

    LI M, HE M X, TIAN Z. Studies on signal-to-noise ratio standardization for THz time-domain spectroscopy[J]. Spectroscopy and Spectral Analysis,2012,32(3):606-609(in Chinese). doi: 10.3964/j.issn.1000-0593(2012)03-0606-04
    雷韶. 6 R工业机器人的运动轨迹规划及仿真研究[D]. 太原: 中北大学, 2017.

    LEI S. The motion trajectory planning and simulation of 6 R industrial robot[D]. Taiyuan: North University of China, 2017(in Chinese).
    MITTLEMAN D M, HUNSCHE S, BOIVIN L, et al. T-ray tomography[J]. Optics Letters,1997,22(12):904. doi: 10.1364/OL.22.000904
    赵博研, 王强, 王毅, 等. 改进YOLOv4算法的GFRP内部缺陷检测与识别[J]. 空军工程大学学报(自然科学版), 2021, 22(4):55-62.

    ZHAO B Y, WANG Q, WANG Y, et al. Research on detection and recognition of GFRP internal defect based on modified YOLOv4 algorithm[J]. Journal of Air Force Engineering University (Natural Science Edition),2021,22(4):55-62(in Chinese).
    LIU S, QI L, QIN H, et al. Path aggregation network for instance segmentation[C]//2018 IEEE/CVF Con-ference on Computer Vision and Pattern Recognition (CVPR). Salt Lake City, 2018: 8759-8768.
    杨丽娟, 张白桦, 叶旭桢. 快速傅里叶变换FFT及其应用[J]. 光电工程, 2004(S1):1-3, 7.

    YANG L J, ZHANG B H, TIAN X Z. Fast Fourier transform and its applications[J]. Opto-Electronic Engineering,2004(S1):1-3, 7(in Chinese).
    张存林, 牧凯军. 太赫兹波谱与成像[J]. 激光与光电子学进展, 2010, 47(2):1-14.

    ZHANG C L, MU K J. Terahertz spectroscopy and imaging[J]. Laser & Optoelectronics Progress,2010,47(2):1-14(in Chinese).
    YUN S, HAN D, CHUN S, et al. CutMix: Regularization strategy to train strong classifiers with localizable features[C]//2019 IEEE/CVF International Conference on Computer Vision (ICCV). Seoul, 2019: 6023-6032.
    DOLLAR P, WOJEK C, SCHIELE B, et al. Pedestrian detec-tion: A benchmark[C]//IEEE Conference on Computer Vision and Patten Recognition (CVPR). Miami, 2009: 304-311.
  • 加载中


    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(19)  / Tables(1)

    Article Metrics

    Article views (1070) PDF downloads(40) Cited by()
    Proportional views


    DownLoad:  Full-Size Img  PowerPoint