Log in

Debonding Defect Detection by Applying Pulsed, Lock-in and Linear Frequency Modulation Thermal Excitation Methods in the Inspection of Fiber-Reinforced Metal Laminates

  • THERMAL METHODS
  • Published:
Russian Journal of Nondestructive Testing Aims and scope Submit manuscript

Abstract

Fiber-reinforced metal laminates (FMLs) are characterized by excellent fatigue damage tolerance, impact resistance and easy processing, and they have been widely used in the aviation industry. Three active infrared thermography methods, namely, pulsed thermography (PT), lock-in thermography (LT), and linear frequency modulation (LFM) techniques, were used to detect internal debonding defects in FMLs. The application characteristics of the above three techniques were investigated. The simulation analysis was carried out by using the PT, LT, and LFM methods, and the LFM method proved to be optimal. Infrared thermography experiments were performed by applying pulsed, sine, and LFM excitation methods. In order to improve efficiency of defect detection, principal component analysis (PCA) was adopted to process experimental image sequences. The results show that the optimal defect identification results of FMLs can be obtained by the combination of LFM and PCA techniques.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.

REFERENCES

  1. Khoramishad, H., Alikhani, H., and Dariushi, S., An experimental study on the effect of adding multi-walled carbon nanotubes on high-velocity impact behavior of fiber metal laminates, Compos. Struct., 2018, vol. 201, pp. 561–569.

    Article  Google Scholar 

  2. Bu, C., Liu, G., Zhang, X., et al., Debonding defects detection of FMLs based on long pulsed infrared thermography technique, Infrared Phys. Technol., 2020, vol. 104, p. 103074.

    Article  CAS  Google Scholar 

  3. Wang, F., Liu, J., Song, P., et al., Multimodal optical excitation pulsed thermography: Enhanced recognize debonding defects of the solid propellant rocket motor cladding layer, Mech. Syst. Signal Process., 2022, vol. 163, p. 108164.

    Article  Google Scholar 

  4. Wang, F., Liu, J., Liu, L., et al., Quantitative non-destructive evaluation of CFRP delamination defect using laser induced chirp-pulsed radar photothermal tomography, Opt. Lasers Eng., 2022, vol. 149, p. 106830.

    Article  Google Scholar 

  5. Junyan, L., Fei, W., Yang, L., et al., Inverse methodology for identification the thermal diffusivity and subsurfacedefect of CFRP composite by lock-in thermographic phase (LITP) profile reconstruction, Compos. Struct., 2016, vol. 138, pp. 214–226.

    Article  Google Scholar 

  6. Palumbo, D., Tamborrino, R., Galietti, U., et al., Ultrasonic analysis and lock-in thermography for debonding evaluation of composite adhesive joints, NDT E Int., 2016, vol. 78, pp. 1–9.

    Article  Google Scholar 

  7. Laureti, S., Silipigni, G., Senni, L., et al., Comparative study between linear and non-linear frequency-modulated pulse-compression thermography, Appl. Opt., 2018, vol. 57(18), pp. 32–39.

    Article  Google Scholar 

  8. Vesala, G.T., Srinivasarao, G., Ghali, V.S., et al., Non-stationary thermal wave mode decomposition: A comparative study of EMD, HVD, and VMD for defect detection, Russ. J. Nondestr. Test., 2022, vol. 58, no. 6, pp. 521–535.

    Article  Google Scholar 

  9. Montinaro, N., Cerniglia, D., and Pitarresi, G., Detection and characterisation of disbonds on fibre metal laminate hybrid composites by flying laser spot thermography, Compos. B Eng., 2017, vol. 108, pp. 164–173.

    CAS  Google Scholar 

  10. Mabrouki, F., Genest, M., Shi, G., et al., Numerical modeling for thermographic inspection of fiber metal laminates, NDT E Int., 2009, vol. 42, no. 7, pp. 581–588.

    Article  CAS  Google Scholar 

  11. Filho, E.F.S., Souza, Y.N., Lopes, J.L.S., et al., Decision support system for ultrasound inspection of fiber metal laminates using statistical signal processing and neural networks, Ultrasonics, 2013, vol. 53, no. 6, pp. 1104–1111.

    Article  Google Scholar 

  12. Wang, J., Zhang, J., Chang, T., et al., Terahertz nondestructive imaging for foreign object detection in glass fibre-reinforced polymer composite panels, Infrared Phys. Technol., 2019, vol. 98, pp. 36–44.

    Article  CAS  Google Scholar 

  13. Chatterjee, K., Tuli, S., Pickering, S.G., et al., A comparison of the pulsed, lock-in and frequency modulated thermography nondestructive evaluation techniques, NDT E Int., 2011, vol. 44, no. 7, pp. 655–667.

    Article  Google Scholar 

  14. Chandra Sekhar Yadav, G.V.P., Ghali, V.S., and Baloji, N.R., A time frequency-based approach for defect detection in composites using nonstationary thermal wave imaging, Russ. J. Nondestr. Test., 2021, vol. 57, no. 6, pp. 486–499.

    Article  Google Scholar 

  15. Tang, Q.J., Fan, W.M., Ji, J., et al., Defect detection of GFRP/Nomex honeycomb sandwich structure by linear frequency modulation infrared thermal imaging, Thermal Sci., 2021, vol. 25, no. 6, pp. 4611–4619.

    Article  Google Scholar 

  16. Bu, C., Liu, T., Li, R., et al., Infrared image segmentation algorithm based on multi structure morphology-pulse coupled neural network in application to the inspection of aerospace materials, Russ. J. Nondestr. Test., 2021, vol. 57, no. 11, pp. 1018–1026.

    Article  Google Scholar 

  17. Bu, C., Sun, Z., Tang, Q., et al., Thermography sequence processing and defect edge identification of TBC structure debonding defects detection using long-pulsed infrared wave non-destructive testing technology, Russ. J. Nondestr. Test., 2019, vol. 55, no. 1, pp. 80–87.

    Article  Google Scholar 

  18. Liu, K., Ma, Z., Liu, Y., et al., Enhanced defect detection in carbon fiber reinforced polymer composites via generative kernel principal component thermography, Polymers, 2021, vol. 13(825), pp. 1–19.

    Google Scholar 

Download references

ACKNOWLEDGMENTS

The authors would like to thank Professor Qingju Tang for useful suggestions in regard to the manuscript presentation, and thank the editors and reviewers of the journal for their useful English writing suggestions on the revision of the paper.

Funding

This work was supported by ongoing institutional funding. No additional grants to carry out or direct this particular research were obtained.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Weicheng Gao.

Ethics declarations

The authors of this work declare that they have no conflicts of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, G., Gao, W., Liu, W. et al. Debonding Defect Detection by Applying Pulsed, Lock-in and Linear Frequency Modulation Thermal Excitation Methods in the Inspection of Fiber-Reinforced Metal Laminates. Russ J Nondestruct Test 59, 915–922 (2023). https://doi.org/10.1134/S106183092360051X

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S106183092360051X

Keywords:

Navigation