Smart DIC-3D: towards full-automatic, user-independent, accurate and precise 3D shape and displacement measurement

被引:0
|
作者
Pan, Bing [1 ]
Zhao, Jianhui [1 ]
Jia, Liang [1 ,2 ]
Yu, Liping [1 ]
机构
[1] Beihang Univ, Sch Aeronaut Sci & Engn, Natl Key Lab Strength & Struct Integr, Beijing 100191, Peoples R China
[2] Beijing Inst Struct & Environm Engn, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
3D digital image correlation; deformation measurement; self-adaptive optimization; DIGITAL IMAGE CORRELATION; SYSTEMATIC-ERRORS; SUBSET SIZE; STRAIN; MOTION;
D O I
10.1088/1361-6501/adb5ad
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Existing three-dimensional digital image correlation (3D-DIC) for surface 3D shape and deformation measurement requires the users to input key calculation parameters (e.g. subset size) to proceed with stereo and temporal matching. However, the lack of clear guidelines for optimal parameter selection often leads to ambiguity and uncertainty in the final measurements. To eliminate the ambiguity and realize full-automatic, user-independent, accurate and precise 3D-DIC measurements, we present a simple yet effective Smart DIC-3D. By fully considering local speckle quality and deformation, Smart DIC-3D automatically selects the optimal subset size for each calculation point in both stereo and temporal matching. Additionally, a fully automated initial value estimation method, combining speeded-up robust features with a reliability-guided displacement tracking strategy, ensures automatic reliable initial value estimation for both matching processes. Both numerical experiments with simulated stereo speckle images and practical applications including complex shape reconstruction and non-uniform deformation measurement were conducted to verify the effectiveness and accuracy of Smart DIC-3D. The experimental results show that Smart DIC-3D has lower random and under-matched systematic errors than regular 3D-DIC, enabling high-fidelity 3D shape reconstruction and deformation measurement independent of the practitioners' input.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Smart DIC: User-independent, accurate and precise DIC measurement with self-adaptively selected optimal calculation parameters
    Zhao, Jianhui
    Pan, Bing
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2025, 222
  • [2] Accurate 3D Shape, Displacement and Deformation Measurement Using a Smartphone
    Yu, Liping
    Tao, Ran
    Lubineau, Gilles
    SENSORS, 2019, 19 (03)
  • [3] Deep 3D-DIC using a coarse-to-fine network for robust and accurate 3D shape and displacement measurements
    Liu, Yanzhao
    Qian, Kemao
    Pan, Bing
    OPTICS EXPRESS, 2025, 33 (02): : 2031 - 2046
  • [4] 3D Shape and Displacement Measurement of Diffuse Objects by DIC-Assisted Digital Holography
    Yan, H.
    Chen, L. Y.
    Long, J.
    Li, K. P.
    Cai, P.
    Su, Y.
    Lei, L. H.
    Pan, B.
    EXPERIMENTAL MECHANICS, 2022, 62 (07) : 1119 - 1134
  • [5] 3D Shape and Displacement Measurement of Diffuse Objects by DIC-Assisted Digital Holography
    H. Yan
    L.Y. Chen
    J. Long
    K.P. Li
    P. Cai
    Y. Su
    L.H. Lei
    B. Pan
    Experimental Mechanics, 2022, 62 : 1119 - 1134
  • [6] Using Convolutional 3D Neural Networks for User-Independent Continuous Gesture Recognition
    Camgoz, Necati Cihan
    Hadfield, Simon
    Koller, Oscar
    Bowden, Richard
    2016 23RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2016, : 49 - 54
  • [7] Combined use of confocal microscopy and DIC for 3D displacement vector measurement
    Bruno, Luigi
    AIAS 2018 INTERNATIONAL CONFERENCE ON STRESS ANALYSIS, 2018, 12 : 567 - 577
  • [8] 2D and 3D Wires Formability for Car Seats: A Novel Full-Automatic Equipment Concept towards High Productivity and Flexibility
    Gaspar, Manuel
    Silva, Francisco J. G.
    Pinto, Arnaldo G.
    Campilho, Raul D. S. G.
    MACHINES, 2023, 11 (03)
  • [9] An accurate 3D edge measurement method for guided precise modification
    Hou, Dongxiang
    Mei, Xuesong
    Wang, Gaocai
    Li, Jiang
    Wang, Chunjie
    Huang, Wang
    Chen, Cheng
    Liu, Rui
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2021, 32 (02)
  • [10] Novel Full-Automatic Approach for Segmentation of Epiretinal Membrane from 3D OCT Images
    Stankiewicz, Agnieszka
    Marciniak, Tomasz
    Dabrowski, Adam
    Stopa, Marcin
    Rakowicz, Piotr
    Marciniak, Elzbieta
    2017 SIGNAL PROCESSING: ALGORITHMS, ARCHITECTURES, ARRANGEMENTS, AND APPLICATIONS (SPA 2017), 2017, : 100 - 105