Journal of the Computational Structural Engineering Institute of Korea (한국전산구조공학회논문집)

Computational Structural Engineering Institute of Korea (한국전산구조공학회)
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ANN-Based Real-Time Damage Detection Technique Using Acceleration Signals in Beam-Type Structures

보 구조물의 가속도 신호를 이용한 인공신경망 기반 실시간 손상검색기법

  • 박재형 (부경대학교 해양공학과) ;
  • 이용환 (한국유지관리㈜ 유지관리사업부) ;
  • 김정태 (부경대학교 해양공학과)
  • Published : 2007.06.30
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Abstract

In this study, an artificial neural network (ANN)-based damage detection algorithm using acceleration signals is developed for real-time alarming locations of damage in beam-type structures. A new ANN-algorithm using output-only acceleration responses is designed tot damage detection in real time. The cross-covariance of two acceleration-signals measured at two different locations is selected as the feature representing the structural condition. Neural networks are trained lot potential loading Patterns and damage scenarios of the target structure for which its actual loadings are unknown. The feasibility and practicality of the proposed method are evaluated from laboratory-model tests on free-free beams for which accelerations were measured before and after several damage cases.

본 논문에서는 보 구조물의 실시간 손상위치 경보를 위해 가속도 신호를 이용한 인공신경망기반 손상검색기법을 제안하였다. 이를 위해 먼저, 실시간 손상검색을 위해 가속도 응답신호만을 이용하는 새로운 인공신경망 알고리즘을 설계하였다. 구조물의 손상상태를 나타내는 특징으로 서로 다른 두 위치에서 측정된 가속도 신호의 교차공분산 값을 이용하였다. 다음으로 실제 하중조건을 모르는 상황을 고려하여 다양한 하중패턴에 따른 복수 신경망을 구성하였으며, 각각의 신경망 학습을 위한 손상시나리오를 선정하였다. 마지막으로 양단 자유보 모형실험을 통해 제안된 기법의 유용성과 적용성을 평가하였다.

Keywords

References

  1. 박재형, 김정태, 류연선, 이진학(2006) 고유진동수와 모드변형에너지를 이용한 향상된 유전알고리즘 기반 손상검색기법, 한국전산구조공학회 논문집, 19(3), pp.313-322
  2. 이인원, 오주원, 박선규, 김주태(1999) 신경망을 이용한 강박스 거더교의 손상평가, 한국강구조공학회논문집, 11(1), pp.79-88
  3. Barai, S.V., Pandey, P.C.(1995) Vibration signature analysis using artificial neural networks, ASCE, Journal of Computing in Civil Engineering, 9(4), pp. 259-265 https://doi.org/10.1061/(ASCE)0887-3801(1995)9:4(259)
  4. Bendat, J.S., Piersol, A.G.(2000) Random Data Analysis and Measurement Procedures: Third edition, John Wiley & Sons, Singapore, p. 163
  5. Catbas, F.N., AKtan, A.M. (2002) Condition and damage assessment: issues and some promising indices, ASCE, Journal of Structural Engineering, 128(8), pp. 1026-1036 https://doi.org/10.1061/(ASCE)0733-9445(2002)128:8(1026)
  6. Chen, Y., Feng, M.Q.(2005) Condition assessment of bridge sub-structure by vibration monitoring, 2nd International Workshop on Advanced Smart Materials and Smart Structures Technology, pp. 651-676
  7. Doebling, S.W., Farrar, C.R., Prime, M.B.(1998) A summary review of vibration-based damage identification methods, Shock and Vibration Digest, 30(2), pp.91-105 https://doi.org/10.1177/058310249803000201
  8. Kim, J.T., Stubbs, N.(1995) Model uncertainty impact and damage-detection accuracy in plate-girder, ASCE, Journal of Structural Engineering, 121(10), pp. 1409-1417 https://doi.org/10.1061/(ASCE)0733-9445(1995)121:10(1409)
  9. Kim, J.T., Ryu, Y.S., Cho, H.M., Stubbs, N.(2003) Damage identification in beam-type structures: frequency-based method vs mode-shape-based method, Engineering Structures, 25, pp. 57-67 https://doi.org/10.1016/S0141-0296(02)00118-9
  10. Lee, J.J., Lee, J.W., Yi, J.H., Yun, C.B., Jung, J.Y. (2005) Neural networks-based damage detection for bridges considering errors in baseline finite element models, Journal of Sound and Vibration, 280(3), pp. 555-578 https://doi.org/10.1016/j.jsv.2004.01.003
  11. Ni, Y.Q., Wang, B.S., Ko, J.M.(2002) Constructing input vectors to neural networks for structural damage identification, Smart Materials and Structures, 11. pp.825-833 https://doi.org/10.1088/0964-1726/11/6/301
  12. Szewczyk, Z.P., Hajela, P.(1994) Damage detection in structures based on feature-sensitive neural networks, ASCE, Journal of Computing in Civil Engineering, 8(2), pp.163-178 https://doi.org/10.1061/(ASCE)0887-3801(1994)8:2(163)
  13. Wu, X., Ghaboussi, J., Garret Jr., J.H.(2001) Use of neural networks in detection of structural damage, Computers and Structures, 42(4), pp.649-659 https://doi.org/10.1016/0045-7949(92)90132-J
  14. Yun, C.B., Bhang, E.Y.(2001) Joint damage assessment of Framed Structures using Neural Networks Technique, Engineering Structures, 23(5), pp.425-435 https://doi.org/10.1016/S0141-0296(00)00067-5