• Laser & Optoelectronics Progress
  • Vol. 59, Issue 22, 2210009 (2022)
Wei Lin1, Haihua Cui1、*, Wei Zheng2, Xinfang Zhou2, Zhenlong Xu1, and Wei Tian1
Author Affiliations
  • 1College of Mechanical & Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu, China
  • 2AVIC Xi'an Aircraft Industry Group Co., Ltd., Xi'an 710089, Shaanxi, China
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    DOI: 10.3788/LOP202259.2210009 Cite this Article Set citation alerts
    Wei Lin, Haihua Cui, Wei Zheng, Xinfang Zhou, Zhenlong Xu, Wei Tian. Phase Fringe Pattern Filtering Method for Shearography Using Deep Learning[J]. Laser & Optoelectronics Progress, 2022, 59(22): 2210009 Copy Citation Text show less
    CycleGAN fringe pattern filtering model and loss model. (a) Fringe pattern filtering model; (b) forward cycle-consistency loss; (c) backward cycle-consistency loss
    Fig. 1. CycleGAN fringe pattern filtering model and loss model. (a) Fringe pattern filtering model; (b) forward cycle-consistency loss; (c) backward cycle-consistency loss
    Structure of fringe pattern filtering model based on CycleGAN
    Fig. 2. Structure of fringe pattern filtering model based on CycleGAN
    Schematic of ideal noiseless phase map generation steps
    Fig. 3. Schematic of ideal noiseless phase map generation steps
    Loss change curve when the learning rate is 0.0001
    Fig. 4. Loss change curve when the learning rate is 0.0001
    Model effects obtained under different number of iterations
    Fig. 5. Model effects obtained under different number of iterations
    Loss function curves under different learning rates
    Fig. 6. Loss function curves under different learning rates
    Filtering results of different methods for simulated noise fringe patterns
    Fig. 7. Filtering results of different methods for simulated noise fringe patterns
    Original noise fringe images and filtering results of different methods
    Fig. 8. Original noise fringe images and filtering results of different methods
    Filtering application optimization process. (a) Cropping from the original image; (b) cropping from filtered image; (c) image mosaic
    Fig. 9. Filtering application optimization process. (a) Cropping from the original image; (b) cropping from filtered image; (c) image mosaic
    Filtering results for fringe pattern under different steps
    Fig. 10. Filtering results for fringe pattern under different steps
    GroupSin-cos mean filteringFrequency domain filteringAdaptive total variationProposed method
    Average0.1570.18156.1220.030
    10.1510.18752.2030.028
    20.1640.17654.5420.030
    30.1530.16963.8950.029
    40.1620.19357.0690.034
    50.1550.17953.6240.029
    Table 1. Running time of different filtering methods
    Wei Lin, Haihua Cui, Wei Zheng, Xinfang Zhou, Zhenlong Xu, Wei Tian. Phase Fringe Pattern Filtering Method for Shearography Using Deep Learning[J]. Laser & Optoelectronics Progress, 2022, 59(22): 2210009
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