CFRP damage imaging based on MVDR weighted sparse reconstruction

FENG Jiqi; YE Bo; ZOU Yangkun; ZHU Zhizhen; YANG Changchun

doi:10.13801/j.cnki.fhclxb.20240507.002

Volume 41 Issue 10

Sep. 2024

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Acta Materiae Compositae Sinica > 2024 > 41(10): 5673-5686. > DOI: 10.13801/j.cnki.fhclxb.20240507.002

FENG Jiqi, YE Bo, ZOU Yangkun, et al. CFRP damage imaging based on MVDR weighted sparse reconstruction[J]. Acta Materiae Compositae Sinica, 2024, 41(10): 5673-5686. DOI: 10.13801/j.cnki.fhclxb.20240507.002

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CFRP damage imaging based on MVDR weighted sparse reconstruction

FENG Jiqi^{1, 2},
YE Bo^{1, 2, ,},
ZOU Yangkun^{2, 3},
ZHU Zhizhen⁴,
YANG Changchun^{1, 2}

1.
School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650000, China
2.
Yunnan Key Laboratory of Intelligent Control and Application, Kunming University of Science and Technology, Kunming 650000, China
3.
School of Civil Aviation and Aeronautics, Kunming University of Science and Technology, Kunming 650000, China
4.
The First Military Representative Office of the Chongqing Military Representative Bureau of the Army Equipment Department in Kunming, Kunming 650000, China

Funds: National Natural Science Foundation of China (62063012); The Young and Middle-Aged Academic and Technical Leaders Reserve Talents Project of Yunnan Province (202305AC160062)

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Received Date: December 03, 2023
Revised Date: April 13, 2024
Accepted Date: April 25, 2024
Available Online: May 07, 2024

Abstract

Abstract

Carbon fiber reinforced polymer (CFRP) is widely used in aerospace and other fields due to its excellent performance, and it will be damaged in service. Sparse reconstruction (SR) algorithm can be used to image the CFRP damage and locate the damage, but the atomic mismatch problem will cause artifacts and even misjudge the damage. Aiming at the above problems, it was proposed that a sparse reconstruction imaging method weighted by minimum variance distortionless response (MVDR). The CFRP monitoring area was divided into several grids, the dictionary was constructed based on the scattering model of Lamb wave to form the SR model with the scattering signal and the sparse solution variables. Secondly, the MVDR imaging method was used for imaging. Based on the imaging results, the MVDR weighting factor was constructed to weight the sparse solution variables. Finally, the basis pursuit denoising algorithm was adopted to solve the weighted SR model, the optimal sparse solution was obtained and converted into pixel value to realize the damage imaging of CFRP. The experimental results of CFRP damage imaging show that the imaging effect of the proposed method is better than that of the SR imaging method under the same regularization parameters, the localization errors are reduced by 72.9 mm, 77.4 mm and 14.7 mm respectively compared with the SR imaging method under three different regularization parameters. Under four different damage locations, the imaging results of MVDR-SR imaging method have fewer artifacts and the maximum damage localization error is 7.9 mm. Compared with MVDR and SR imaging methods, MVDR-SR imaging method has better imaging performance, which verifies the correctness and effectiveness of the proposed method.
- CFRP,
- sparse reconstruction,
- MVDR weighting factor,
- Lamb wave,
- damage imaging

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References

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CFRP damage imaging based on MVDR weighted sparse reconstruction

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