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Volume 49 Issue 2
Feb.  2023
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Journal of Beijing University of Aeronautics and Astronautics  > 2023  >  49(2): 265-272.
MA M，YU J，FAN W R. CFRP material detection based on improved joint sparse EIT algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（2）：265-272 （in Chinese） doi: 10.13700/j.bh.1001-5965.2021.0244
Citation: MA M，YU J，FAN W R. CFRP material detection based on improved joint sparse EIT algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（2）：265-272 （in Chinese） doi: 10.13700/j.bh.1001-5965.2021.0244
shu

CFRP material detection based on improved joint sparse EIT algorithm

doi: 10.13700/j.bh.1001-5965.2021.0244

  • College of Electronic Information and Automation，Civil Aviation University of China，Tianjin 300300，China

Funds:  National Natural Science Foundation of China (61871379); Scientific Research Program of Tianjin Education Commission (2020KJ012)
More Information
  • Corresponding author: E-mail：mm5739@163.com
  • Received Date: 10 May 2021
  • Accepted Date: 09 Jul 2021
    • Available Online: 02 Jun 2023
  • Publish Date: 30 Jul 2021
    Abstract

  • Aiming at the highly ill-posed problem of the application of electrical impedance tomography (EIT) to the damage detection of carbon fiber reinforced polymer (CFRP), a joint ${L_1}$ and ${L_2}$ norm sparse regularization functional model was proposed, and a new constraint is constructed to optimize the solution during the iterative process. The simulation results show that, compared with other traditional algorithms, the improved joint sparse EIT algorithm can effectively improve the electrode artifacts of the damage image, improve the clarity of damage edge, and enhance the accuracy of damage identification and location. The experimental results of CFRP laminate detection show that the improved joint sparse EIT algorithm can improve the anti-interference ability of the image reconstruction, and has good robustness and applicability.

     

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