All Issue

2023 Vol.25, Issue 4 Preview Page

Technical Paper

Performance analysis of tunnel scanning system based on Japanese performance evaluation system

일본 성능평가 제도기반 터널 스캐닝 시스템 성능 분석

Chulhee Lee1
,
Jaemo Kang2
,
Donggyou Kim3*
이 철희1
,
강 재모2
,
김 동규3*
1Senior Researcher, Dept. of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology
2Senior Researcher, Dept. of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology
3Senior Research Fellow, Dept. of Geotechnical Engineering Research, Korea Institute of Civil Engineering and Building Technology
1정회원, 한국건설기술연구원 지반연구본부 수석연구원
2비회원, 한국건설기술연구원 지반연구본부 수석연구원
3정회원, 한국건설기술연구원 지반연구본부 선임연구위원
*Corresponding Author
31 July 2023. pp. 331-344
PDF XML Citation
Abstract

The performance of the existing tunnel scanning system was analyzed through the post-evaluation of NETIS (New Technology Information System) and Inspection Support Technology Performance Catalog. Suggestions for improvement and development direction of the tunnel scanning system were deduced. As new technology of Japan gave priority to providing user-centered information, it was possible to objectively compare and analyze the characteristics of various tunnel scan systems through post-evaluation of NETIS and standard test methods in the Inspection Support Technology Performance Catalog. Construction New Technology of Korea was centered on suppliers of technology certification, making it impossible to objectively compare the performance of tunnel scanning systems. The performance was compared and evaluated indirectly by comparing the specifications of the camera, which is a core device of Japan’s tunnel scanning system. For the future development of tunnel scanning systems, high-resolution and fast exposure performance of cameras and corresponding high-intensity lighting devices are required. For this purpose, it is necessary to make an experimental environment in which the performance of the camera and lighting can be analyzed indoors.

Keywords
Tunnel scanning system
NETIS
Performance evaluation
Standard test method
Scan camera

본 논문은 일본의 성능평가 제도인 NETIS의 사후평가와 점검 지원 기술 성능 카탈로그를 통해 기존 터널 스캐닝 시스템의 성능을 분석하였다. 분석을 통해 터널 스캐닝 시스템의 개선 사항과 개발 방향에 대한 시사점을 도출하였다. 일본의 신기술은 사용자 중심의 정보 제공을 우선시하여 NETIS의 사후평가와 점검 지원 기술 성능 카탈로그의 표준시험방법을 통해 다양한 터널 스캐닝 시스템의 특성을 객관적으로 비교하고 분석할 수 있다. 국내의 건설신기술은 기술인증의 공급자 중심으로 터널 스캐닝 시스템에 대한 객관적인 성능 비교는 불가능하였다. 일본의 터널 스캐닝 시스템의 핵심장치인 카메라의 제원을 비교하여 성능을 간접적으로 비교 평가하였다. 향후 터널 스캐닝 시스템 개발을 위해서는 카메라의 고해상도와 빠른 노출 성능 그리고 이에 부합되는 고휘도의 조명 장치가 요구된다. 실내에서 카메라와 조명의 성능을 분석할 수 있는 실험 환경 조성도 필요할 것으로 판단된다.

키워드
터널 스캐닝 시스템
NETIS
성능평가
표준시험방법
스캔 카메라
References
1
Alidoost, F., Austen, G., Hahn, M. (2022), "A multi-camera mobile system for tunnel inspection", iCity. Transformative Research for the Livable, Intelligent, and Sustainable City, Springer, pp. 211-224. 10.1007/978-3-030-92096-8_13
2
Attard, L., Debono, C.J., Valentino, G., Castro, M. (2018), "Tunnel inspection using photogrammetric techniques and image processing: a review", ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 144, pp. 180-188. 10.1016/j.isprsjprs.2018.07.010
3
Bae, S.J., Jung, W., Chamrith, S., Kim, C.J., Kim, Y.M., Hong, S.H., Kim, J.G., Kim, J.Y. (2021), "Performance evaluation method of tunnel scanner for lining crack detection", Journal of the Society of Disaster Information, Vol. 17, No. 1, pp. 39-52. 10.15683/kosdi.2021.3.31.039
4
CNT 887 (2020), Construction New Technology, https://www.kaia.re.kr/portal/newtec/comparelist.do (February 7, 2023).
5
CNT 898 (2020), Construction New Technology, https://www.kaia.re.kr/portal/newtec/comparelist.do (February 7, 2023).
6
CNT 935 (2022), Construction New Technology, https://www.kaia.re.kr/portal/newtec/comparelist.do (February 7, 2023).
7
Hong, S.H., Kim, J.G., Cho, J.Y., Kim, T.H. (2020), "A study on the necessity of verification and certification system of inspection and diagnostic equipment for infrastructure using advanced technologies", Journal of the Society of Disaster Information, Vol. 16, No. 1, pp. 163-177. 10.15683/kosdi.2020.3.31.163
8
Huang, H., Sun, Y., Xue, Y., Wang, F. (2017), "Inspection equipment study for subway tunnel defects by grey-scale image processing", Advanced Engineering Informatics, Vol. 32, pp. 188-201. 10.1016/j.aei.2017.03.003
9
Huang, H.W., Li, Q.T., Zhang, D.M. (2018), "Deep learning based image recognition for crack and leakage defects of metro shield tunnel", Tunnelling and Underground Space Technology, Vol. 77, pp. 166-176. 10.1016/j.tust.2018.04.002
10
JCI (2010), Concrete diagnosis technology, Japan Concrete Institute, Japan.
11
Lee, Y.H., Bae, S.J., Jung, W., Cho, J.Y., Hong, S.H., Nam, W.S., Kim, Y.M., Kim, J.Y. (2020), "Performance evaluation method for facility inspection and diagnostic technologies", Journal of the Society of Disaster Information, Vol. 16, No. 1, pp. 178-191. 10.15683/kosdi.2020.3.31.178
12
Makantasis, K., Karantzalos, K., Doulamis, A., Doulamis, N. (2015), "Deep supervised learning for hyperspectral data classification through convolutional neural networks", Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy, pp. 4959-4962. 10.1109/IGARSS.2015.7326945
13
Medina, R., Llamas, J., Gómez-García-Bermejo, J., Zalama, E., Segarra, M.J. (2017), "Crack detection in concrete tunnels using a Gabor filter invariant to rotation", Sensors, Vol. 17, No. 7, 1670. 10.3390/s1707167028726746PMC5539543
14
MLIT (2023), Inspection support technology performance catalog, Ministry of Land, Infrastructure, Transport and Tourism, Japan.
15
Montero, R., Victores, J.G., Martínez, S., Jardón, A., Balaguer, C. (2015), "Past, present and future of robotic tunnel inspection", Automation in Construction, Vol. 59, pp. 99-112. 10.1016/j.autcon.2015.02.003
16
NETIS (New Technology Information System), https://www.netis.mlit.go.jp/netis/ (April 3, 2023).
17
Nishimura, S., Hara, K., Kimoto, K., Matsuda, H. (2012), "The measurement and draw damaged plans at Gunkan-Island by using 3D laser scanner and digital camera", Journal of the Japan Society of Photogrammetry and Remote Sensing, Vol. 51, No. 1, pp. 46-53. 10.4287/jsprs.51.46
18
RICON (2021), Framework and implication of NETIS (New Technology Information System) in Japan, Korea Research Institute for Construction Policy, Korea.
19
Shen, B., Zhang, W.Y., Qi, D.P., Wu, X.Y. (2015), "Wireless multimedia sensor network based subway tunnel crack detection method", International Journal of Distributed Sensor Networks, Vol. 11, No. 6. 10.1155/2015/184639
20
Ukai, M. (2007). "Advanced inspection system of tunnel wall deformation using image processing", Quarterly Report of RTRI, Vol. 48, No. 2, pp. 94-98. 10.2219/rtriqr.48.94
21
Wang, H., Wang, Q., Zhai, J., Yuan, D., Zhang, W., Xie, X., Zhou, B., Cai, J., Lei, Y. (2022). "Design of fast acquisition system and analysis of geometric feature for highway tunnel lining cracks based on machine vision", Applied Sciences, Vol. 12, No. 5, 2516. 10.3390/app12052516
22
Yoon, T.G., Lee, S. (2008), "A study for tunnel management system development using a tunnel scanner", Journal of the Korea Institute for Structural Maintenance and Inspection, Vol. 12, No. 3, pp. 183-190.
Information
  • Publisher :Korean Tunneling and Underground Space Association
  • Publisher(Ko) :한국터널지하공간학회
  • Journal Title :Journal of Korean Tunnelling and Underground Space Association
  • Journal Title(Ko) :한국터널지하공간학회 논문집
  • Volume : 25
  • No :4
  • Pages :331-344
  • Received Date : 2023-06-12
  • Revised Date : 2023-06-28
  • Accepted Date : 2023-06-28
  • DOI :https://doi.org/10.9711/KTAJ.2023.25.4.331
Journal Informaiton Journal of Korean Tunnelling and Underground Space Association Journal of Korean Tunnelling and Underground Space Association
Online Submission & Review System
  • NRF
  • KOFST
  • KISTI Current Status
  • KISTI Cited-by
  • crosscheck
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close