Journal of the Korea institute for structural maintenance and inspection (한국구조물진단유지관리공학회 논문집)

Korea Institute for Structural Maintenance Inspection (한국구조물진단유지관리공학회)
권호 표지
DOI QR코드

DOI QR Code

Concrete Crack Detection Inside Finishing Materials Using Lock-in Thermography

위상 잠금 열화상 기법을 이용한 콘크리트 마감재 내부 균열 검출

  • Received : 2023.10.10
  • Accepted : 2023.11.03
  • Published : 2023.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

As the number of old buildings subject to safety inspection increases, the burden on designated institutions and management entities that are responsible for safety management is increasing. Accordingly, when selecting buildings subject to safety inspection, appropriate safety inspection standards and appropriate technology are essential. The current safety inspection standards for old buildings give low scores when it is difficult to confirm damage such as cracks in structural members due to finishing materials. This causes the evaluation results to be underestimated regardless of the actual safety status of the structure, resulting in an increase in the number of aging buildings subject to safety inspection. Accordingly, this study proposed a thermal imaging technique, a non-destructive and non-contact inspection, to detect cracks inside finishing materials. A concrete specimen was produced to observe cracks inside the finishing material using a thermal imaging camera, and thermal image data was measured by exciting a heat source on the concrete surface and cracked area. As a result of the measurement, it was confirmed that it was possible to observe cracks inside the finishing material with a width of 0.3mm, 0.5mm, and 0.7mm, but it was difficult to determine the cracks due to uneven temperature distribution due to surface peeling and peeling of the wallpaper. Accordingly, as a result of performing data analysis by deriving the amplitude and phase difference of the thermal image data, clear crack measurement was possible for 0.5mm and 0.7mm cracks. Based on this study, we hope to increase the efficiency of field application and analysis through the development of technology using big data-based deep learning in the diagnosis of internal crack damage in finishing materials.

안전점검 대상 노후 건축물이 증가함에 따라 안전관리 주체인 지정기관 및 관리주체의 부담이 증가하고 있다. 이에 안전점검 대상 건축물 선정에 있어 적절한 안전전검 기준과 그에 따르는 적절한 기술은 필수적이다. 현행 노후 건축물 대상 안전점검 수행 기준은 마감재로 인해 구조 부재 균열 등의 손상 확인이 어려울 경우 낮은 점수를 부여하고 있다. 이는 구조물의 실체 안전상태와 관계없이 평가 결과가 과소평가되어 안전점검 대상 노후화 건축물을 증가시키는 원인이다. 이에 본 연구에서는 마감재 내부의 균열 탐지를 위해 비파괴·비접촉 검사인 열화상 기법을 제안하였다. 열화상 카메라를 이용한 마감재 내부 균열 관측을 위해 콘크리트 시편을 제작하였으며, 콘크리트 표면 및 균열부에 열원을 가진하여 열화상 데이터를 계측하였다. 계측 결과, 너비 0.3mm, 0.5mm, 0.7mm의 마감재 내부 균열 관측이 가능함을 확인하였으나, 표면 박리, 도배지 들뜸으로 인한 불균일한 온도 분포로 인해 균열 판단이 어렵다. 이에 열화상 데이터의 진폭 및 위상 차이를 도출하여 데이터 분석을 수행한 결과, 0.5mm, 0.7mm 균열에 대해 선명한 균열 계측이 가능하였다. 본 연구를 토대로 추후 마감재 내부 균열 손상 진단에 있어 빅 데이터 기반 딥러닝을 이용한 기술개발을 통해 현장적용 및 분석의 효율성을 증대시키고자 한다.

Keywords

Acknowledgement

본 연구는 국토교통부 디지털 기반 건축시공 및 안전감리기술 개발 사업의 연구비지원(1615013081)과 우수신진연구사업의 지원(No. RS-2023-00210317)에 의해 수행되었습니다. 이에 감사드립니다.

References

  1. Andi, M., and Yohanes, G. R. (2019), Experimental study of crack depth measurement of concrete with ultrasonic pulse velocity (UPV), In IOP conference series: materials science and engineering, (Vol. 673, No. 1, p. 012047), IOP Publishing. https://doi.org/10.1088/1757-899X/673/1/012047
  2. Breitenstein, O., and Langenkamp, M. (2003), Lock-in thermography, Basics and Use for Functional Diagnostics of Electronics Components.
  3. Cho, Y., and Han, S. (2012), Optimization of Lock-in Thermography Technique using Phase Image Processing, Journal of Ocean Engineering and Technology, 26(5), 25-30 (in Korean, with English abstract). https://doi.org/10.5574/KSOE.2012.26.5.025
  4. Chu, S. Y., Kang, C. J., Hu, M. X., and Chang, L. C. (2022), Rapid damage assessment of 1/3 scaled-down two-story reinforced concrete school building models, Journal of Structural Integrity and Maintenance, 7(2), 110-119. https://doi.org/10.1080/24705314.2021.2019178
  5. Colombani, I. A., and Andrawes, B. (2022), A study of multi-target image-based displacement measurement approach for field testing of bridges, Journal of Structural Integrity and Maintenance, 7(4), 207-216. https://doi.org/10.1080/24705314.2022.2088071
  6. Dung, C. V. (2019), Autonomous concrete crack detection using deep fully convolutional neural network, Automation in Construction, 99, 52-58. https://doi.org/10.1016/j.autcon.2018.11.028
  7. Gharehbaghi, V. R., Kalbkhani, H., Noroozinejad Farsangi, E., Yang, T. Y., Nguyen, A., Mirjalili, S., and Malaga-Chuquitaype, C. (2022), A novel approach for deterioration and damage identification in building structures based on Stockwell-Transform and deep convolutional neural network, Journal of Structural Integrity and Maintenance, 7(2), 136-150. https://doi.org/10.1080/24705314.2021.2018840
  8. Jung, J., Yoon, H., Cho, H., and Yang, H. (2018), A Study on Temperature Characteristics of Various Depth using Infrared Thermography, Journal of the Korea Academia-Industrial cooperation Society, 19(3), 83-89 (in Korean, with English abstract).
  9. Kwon, S., and Park, S. (2012), Non Destructive Technique for Steel Corrosion Detection Using Heat Induction and IR Thermography, Journal of Korea Institute for Structural Maintenance and Inspection, 16(2) (in Korean, with English abstract).
  10. Kim, J. C., Jung, J. H., and Lee, K. Y. (2020), Modified safety evaluation method for buildings of class-III establishments, Seoul Institute of Technology, 9791190734325.
  11. Kim, S, Y. (2018), Chosun Media, Available at: https://www.chosun.com/site/data/html_dir/2018/12/14/2018121400303.html
  12. Korea Authority of Land & Infrastructure Safety. (2021), 2021 Facility Statistics Yearn.
  13. Lee, Y., Lee, T., Park, G., Oh, Y., and Cha, C. (2010), A Study on the Decision of Influence Range of External Temperature in the Tunnel Using Thermal Camera, Journal of Korea Institute for Structural Maintenance and Inspection, 14(5) (in Korean, with English abstract).
  14. Ministry of Land Infrastructure and Transport. (2021), Actual Condition Investigation Manual for Class 3 Facility Designation.
  15. Pugliesi, R., and Andrade, M. L. G. (1996), Study of cracking in concrete by neutron radiography, Applied radiation and isotopes, 48(3), 339-344. https://doi.org/10.1016/S0969-8043(96)00229-1
  16. Song, H., Lim, H. J., Lee, S., Sohn, H., Yun, W., and Song, E. (2015), Automated detection and quantification of hidden voids in triplex bonding layers using active lock-in thermography, NDT & E International, 74, 94-105. https://doi.org/10.1016/j.ndteint.2015.05.004
  17. Tashan, J., and Al-Mahaidi, R. (2014), Detection of cracks in concrete strengthened with CFRP systems using infra-red thermography, Composites Part B: Engineering, 64, 116-125. https://doi.org/10.1016/j.compositesb.2014.04.011
  18. FLIR. (2018), Available at: https://www.flirkorea.com/
  19. Usamentiaga, R., Venegas, P., Guerediaga, J., Vega, L., Molleda, J., and Bulnes, F. G. (2014), Infrared thermography for temperature measurement and non-destructive testing, Sensors, 14(7), 12305- 12348. https://doi.org/10.3390/s140712305