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2024 Vol.37, Issue 4 Preview Page

Research Paper

Comparison of the Applicability of Bayesian Filters for System Identification of Sudden Structural Damage

급격한 구조손상탐지를 위한 베이지안 필터 적용가능성 비교 검토 연구

Se-Hyeok Lee1†
,
Minkyu Kim2
,
Sang-ri Yi3
이 세혁1†
,
김 민규2
,
이 상리3
1Senior Researcher, Department of Structural Engineering Research, Korea Institute of Civil Engineering and Building Technology, Goyang, 10223, Korea
2Postdoctoral Researcher, Structural and Seismic Safety Research Division, Korea Atomic Energy Research Institute, Daejeon, 34057, Korea
3Assistant Project Scientist, Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
1한국건설기술연구원 구조연구본부 수석연구원
2한국원자력연구원 구조･지진안전연구부 박사후연구원
3University of California, Berkeley 박사후연구원
†Corresponding Author
31 August 2024. pp. 283-293
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Abstract

In this study, advanced unscented Kalman filter (UKF) and particle filter (PF) implementations are introduced and applied to perform system identification (SI) for sudden structural damage induced by seismic loading. These two methods are then compared to validate their applicability to SI tasks. For this validation, the Bouc– Wen model is used to simulate the nonlinear shear-building response, and an adaptive rule (i.e., an adaptive tracking method) is applied to the two filter methods to improve their tracking performance during sudden changes in system properties. When the original UKF and PF are applied to an earthquake scenario, both methods fail to estimate the damage initiation time and post-damage parameter values. After applying the adaptive tracking method, it is found for both methods that although the occurrence time is identified, the estimation of the damage state is still not accurate. To improve the accuracy, an adjusted adaptive tracking method is applied, and the two methods then derive accurate estimates. Finally, when considering the computation time, UKF is promoted as a better choice for practical applications, provided that a proper adaptive tracking method is implemented.

Keywords
unscented kalman filter
particle filter
system identification
sudden structural damage
bouc-wen model

본 논문에서는 지진 하중으로 인한 급격한 구조손상탐지를 수행하기 위해 분산점 칼만필터(Unscented Kalman Filter, UKF)와 파티클 필터(Particle Filter)를 소개하고 지진 손상 시나리오에 적용 및 비교･검토하였다. 이때, 비선형 전단 빌딩을 모사하기 위해 Bouc-Wen 모델을 사용하였고, 급격한 변화를 추정하기 위해 추가적으로 적응형 기법(Adaptive rule)인 Adaptive Jumping Method를 두 필터 모두에 적용하였다. 적용 결과 두 오리지날 필터 모두 급격한 손상 시점과 정도를 파악하지 못하였고, 적응형 기법을 반영하였을 경우에만 시점 파악이 가능하였다. 하지만, 여전히 손상 정도를 정확히 파악하지 못하였고, 두 방법 모두 제안된 적응형 기법을 새로이 조정하였을 경우에 정확한 추정이 가능함을 확인하였다. 최종적으로 계산시간을 고려하였을 때, 새로운 형태의 적응형 기법을 적용한 UKF 사용을 제안하는 것으로 비교 검토를 수행하였다.

키워드
분산점 칼만필터
파티클 필터
구조손상탐지기법
급격한 구조 손상
Bouc-Wen 모델
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Information
  • Publisher :Computational Structural Engineering Institute of Korea
  • Publisher(Ko) :한국전산구조공학회
  • Journal Title :Journal of the Computational Structural Engineering Institute of Korea
  • Journal Title(Ko) :한국전산구조공학회 논문집
  • Volume : 37
  • No :4
  • Pages :283-293
  • Received Date : 2024-07-22
  • Revised Date : 2024-08-05
  • Accepted Date : 2024-08-06
  • DOI :https://doi.org/10.7734/COSEIK.2024.37.4.283
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