EGU2020-11677
https://doi.org/10.5194/egusphere-egu2020-11677
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Comparative study of steel corrosion characterization by visible and THz imaging techniques

Jean Dumoulin1, Ilaria Catapano2, Jean-Marc Moliard3, Giovanni Ludeno2, Thibaud Toullier1, and Francesco Soldovieri2
Jean Dumoulin et al.
  • 1Univ Gustave Eiffel, Inria, COSYS-SII, I4S Team, F-44344 Bouguenais, France
  • 2Istituto per il Rilevamento Elettromagnetico dell’Ambiente, Consiglio Nazionale delle Ricerche, Napoli, Italy
  • 3Univ Gustave Eiffel, COSYS-SII, IFSTTAR, F-44344 Bouguenais, France

Transport infrastructures play a significant role in the economy of countries. However, in European countries, transport infrastructures aging (>40 years) and traffic increase require to develop in-situ efficient inspection and maintenance solutions. Monitoring of steel and composite structures are important issues for sustainability of existing and new infrastructure. Classical approach relies on large human activities eventually performed in unsafe conditions. To overcome the problem on site contactless global automated measurement methods are to be favoured.

For apparent corrosion, visible imaging coupled with image processing allows to detect and characterize the extension of the defective area. Anyway, characterization of corrosion thickness and nature require complementary measurements. Among imaging techniques, knowing that corrosion acts as a insulating layer, active infrared thermography is a possible approach [1-2]. But here we will focus on the complementary approach based on THz-TDS imaging as investigated and tested for corrosion detection under painting with preliminary corrosion type classification [2].

In the present study, we first performed a measurement campaign on several steel samples at different corrosion stages. Typically, three stages were investigated: from non-corroded with paint coating, to pitting corrosion up to fully corroded sample surface.

Data were gathered by means of the Z-Omega Fiber-Coupled Terahertz Time Domain (FICO) system working in a high-speed reflection mode and were processed by using a properly designed data processing chain recently proposed in [3] and involving a noise filtering procedure based on the Singular Value Decomposition (SVD) of the data matrix. Complementary post-processing approach for quick detection and characterization were added to these filtered data.

The obtained results, which will be presented in detail at the conference, allowed us to state the imaging capabilities offered by the adopted instrumentation and obtain valuable information on the surveyed specimens, such as the corrosion thickness connection with apparent pseudo-intensity images. Finally, perspectives on coupling techniques will be introduced.

Acknowledgments:

Authors wish to thank Research Fund for Coal and Steel for funding part of this work under grant agreement No 800687 in the framework of DESDEMONA project.

 

References

[1] A. Crinière, J. Dumoulin, C. Ibarra-Castanedo and X. Maldague ,” Inverse model for defect characterization of externally glued CFRP on reinforced concrete structures: Comparative study of square pulsed and pulsed thermography “, Quantitative InfraRed Thermography Journal, Taylor & Francis Editor, vol 11, pp 84-114, 2014. DOI: 10.1080/17686733.2014.897512.

[2] T. Sakagami, D. Shiozawa, Y. Tamaki, H. Ito A. Moriguchi, T. Iwama, K. Sekine and T. Shiomi, “Nondestructive detection of corrosion damage under corrosion protection coating using infrared thermography and terahertz imaging, in. Proc AITA 2015 conference, pp. 229-233, 2015.

[3] I. Catapano, F. Soldovieri, “A Data Processing Chain for Terahertz Imaging and Its Use in Artwork Diagnostics".J Infrared Milli Terahz Waves, pp.13, Nov. 2016.

How to cite: Dumoulin, J., Catapano, I., Moliard, J.-M., Ludeno, G., Toullier, T., and Soldovieri, F.: Comparative study of steel corrosion characterization by visible and THz imaging techniques, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11677, https://doi.org/10.5194/egusphere-egu2020-11677, 2020