• Title/Summary/Keyword: baseline modal model

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Damage Detection in Complex Structures using Pattern Recognition of Modal Sensitivity (모드민감도 패턴인식에 의한 복잡한 구조물의 손상발견)

  • 김정태;류연선;노리스스텁스
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1997.04a
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    • pp.97-105
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    • 1997
  • A methodology to identify a baseline modal model of a complicated 3-D structure using limited structural and modal information is experimentally examined. In the first part, a system's identification theory for the methodology to identify, baseline modal responses of the structure is outlined. Next, an algorithm is designed to build a generic finite element model of the baseline structure and to calibrate the model by using only a set of post-damage modal parameters. In the second part, the feasibility of the methodology is examined experimentally using a field-tested truss bridge far which only post-damaged modal responses were measured for a few vibration modes. For the complex 3-D bridge with many members, we analyzed to identify unknown stiffness parameters of the structure by using modal parameters of the initial two modes of vibration.

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Gaussian mixture model for automated tracking of modal parameters of long-span bridge

  • Mao, Jian-Xiao;Wang, Hao;Spencer, Billie F. Jr.
    • Smart Structures and Systems
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    • v.24 no.2
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    • pp.243-256
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    • 2019
  • Determination of the most meaningful structural modes and gaining insight into how these modes evolve are important issues for long-term structural health monitoring of the long-span bridges. To address this issue, modal parameters identified throughout the life of the bridge need to be compared and linked with each other, which is the process of mode tracking. The modal frequencies for a long-span bridge are typically closely-spaced, sensitive to the environment (e.g., temperature, wind, traffic, etc.), which makes the automated tracking of modal parameters a difficult process, often requiring human intervention. Machine learning methods are well-suited for uncovering complex underlying relationships between processes and thus have the potential to realize accurate and automated modal tracking. In this study, Gaussian mixture model (GMM), a popular unsupervised machine learning method, is employed to automatically determine and update baseline modal properties from the identified unlabeled modal parameters. On this foundation, a new mode tracking method is proposed for automated mode tracking for long-span bridges. Firstly, a numerical example for a three-degree-of-freedom system is employed to validate the feasibility of using GMM to automatically determine the baseline modal properties. Subsequently, the field monitoring data of a long-span bridge are utilized to illustrate the practical usage of GMM for automated determination of the baseline list. Finally, the continuously monitoring bridge acceleration data during strong typhoon events are employed to validate the reliability of proposed method in tracking the changing modal parameters. Results show that the proposed method can automatically track the modal parameters in disastrous scenarios and provide valuable references for condition assessment of the bridge structure.

Damage Identification in Truss Bridges using Damage Index Method (손상지수법을 이용한 트러스 교량의 손상추정)

  • Lee, Bong Hak;Kim, Jeong Tae;Chang, Dong Il
    • Journal of Korean Society of Steel Construction
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    • v.10 no.2 s.35
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    • pp.279-290
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    • 1998
  • An existing Damage Index Method is verified to demonstrate its feasibility for detecting structural damage in truss bridges (1) for which modal parameters are available for a few modes of vibration and (2) for which baseline modal information is not available from its as-built state. The theory of approach to detect locations of damage and to identify baseline modal model is summarized on the basis of system identification theory and modal sensitivity theory. The feasibility of the Damage Index Method is demonstrated using a numerical example of a truss bridge with 11 subsystems of 211 members and for which only two modes of vibration were recorded for post-damaged state.

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Damage Detection in Cracked Model Plate-Girder using Damage Index Method and System Identification Technique (손상지수법과 구조식별(SID) 기법을 통한 균열된 강판형 모형의 손상검색)

  • 백종훈;류연선;김정태;조현만
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2001.10a
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    • pp.109-116
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    • 2001
  • An integrated damage identification system (IDIS) and system identification (SID) technique using modal information to detect damage in structures is presented. The objective is to detect damages in cracked model plate-girder without baseline modal parameters. The theory of damage localization and system identification is outlined. Experiments on a model plate-girder was described and a baseline model representing the experimental modal characteristics of the model plate-girder is updated using the system identification technique. Finally, damage inflicted in the model plate-girder is predicted using the IDIS software.

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Performance Enhancement of System Identification Model for Vibration-Based Damage Detection in Flawed Plate-Girder Bridges (결함이 있는 판형교의 진동기초 손상검색을 위한 구조식별모델의 성능향상)

  • 백종훈;김정태;류연선
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2003.04a
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    • pp.443-450
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    • 2003
  • System identification techniques can be used to build a baseline modal model for a flawed structure that has no modal information on its as-built state. The accuracy of a system identification proposed by Stubbs and Kim is analyzed for plate-girder bridges and its impact on the accuracy of damage detection in those structures is also analyzed. A laboratory-scale model plate-girder is experimentally tested and the initial four bending modes are examined for certain damage scenarios. The performance of individual baseline modal models is assessed by detecting damage in the model structure.

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Structural model updating of the Gageocho Ocean Research Station using mass reallocation method

  • Kim, Byungmo;Yi, Jin-Hak
    • Smart Structures and Systems
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    • v.26 no.3
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    • pp.291-309
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    • 2020
  • To study oceanic and meteorological problems related to climate change, Korea has been operating several ocean research stations (ORSs). In 2011, the Gageocho ORS was attacked by Typhoon Muifa, and its structural members and several observation devices were severely damaged. After this event, the Gageocho ORS was rehabilitated with 5 m height to account for 100-yr extreme wave height, and the vibration measurement system was equipped to monitor the structural vibrational characteristics including natural frequencies and modal damping ratios. In this study, a mass reallocation method is presented for structural model updating of the Gageocho ORS based on the experimentally identified natural frequencies. A preliminary finite element (FE) model was constructed based on design drawings, and several of the candidate baseline FE models were manually built, taking into account the different structural conditions such as corroded thickness. Among these candidate baseline FE models, the most reasonable baseline FE model was selected by comparing the differences between the identified and calculated natural frequencies; the most suitable baseline FE model was updated based on the identified modal properties, and by using the pattern search method, which is one of direct search optimization methods. The mass reallocation method is newly proposed as a means to determine the equivalent mass quantities along the height and in a floor. It was found that the natural frequencies calculated based on the updated FE model was very close to the identified natural frequencies. In conclusion, it is expected that these results, which were obtained by updating a baseline FE model, can be useful for establishing the reference database for jacket-type offshore structures, and assessing the structural integrity of the Gageocho ORS.

Baseline Model Updating and Damage Estimation Techniques for Tripod Substructure (트라이포드 하부구조물의 기저모델개선 및 결함추정 기법)

  • Lee, Jong-Won
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.6
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    • pp.218-226
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    • 2020
  • An experimental study was conducted on baseline model updating and damage estimation techniques for the health monitoring of offshore wind turbine tripod substructures. First, a procedure for substructure health monitoring was proposed. An initial baseline model for a scaled model of a tripod substructure was established. A baseline model was updated based on the natural frequencies and the mode shapes measured in the healthy state. A training pattern was then generated using the updated baseline model, and the damage was estimated by inputting the modal parameters measured in the damaged state into the trained neural network. The baseline model could be updated reasonably using the effective fixity model. The damage tests were performed, and the damage locations could be estimated reasonably. In addition, the estimated damage severity also increased as the actual damage severity increased. On the other hand, when the damage severity was relatively small, the corresponding damage location was detected, but it was more difficult to identify than the other cases. Further studies on small damage estimation and stiffness reduction quantification will be needed before the presented method can be used effectively for the health monitoring of tripod substructures.

Experimental damage identification of cantilever beam using double stage extended improved particle swarm optimization

  • Thakurdas Goswami;Partha Bhattacharya
    • Structural Engineering and Mechanics
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    • v.91 no.6
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    • pp.591-606
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    • 2024
  • This article proposes a new methodology for identifying beam damage based on changes in modal parameters using the Double Stage Extended Improved Particle Swarm Optimization (DSEIPSO) technique. A finite element code is first developed in MATLAB to model an ideal beam structure based on classical beam theory. An experimental study is then performed on a laboratory-scale beam, and the modal parameters are extracted. An improved version of the PSO algorithm is employed to update the finite element model based on the experimental measurements, representing the real structure and forming the baseline model for all further damage detection. Subsequently, structural damages are introduced in the experimental beam. The DSEIPSO algorithm is then utilized to optimize the objective function, formulated using the obtained mode shapes and the natural frequencies from the damaged and undamaged beams to identify the exact location and extent of the damage. Experimentally obtained resultsfrom a simple cantilever beam are used to validate the effectiveness of the proposed method. The illustrated results show the effectiveness of the proposed method for structural damage detection in the SHM field.

A model experiment of damage detection for offshore jacket platforms based on partial measurement

  • Shi, Xiang;Li, Hua-Jun;Yang, Yong-Chun;Gong, Chen
    • Structural Engineering and Mechanics
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    • v.29 no.3
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    • pp.311-325
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    • 2008
  • Noting that damage occurrence of offshore jacket platforms is concentrated in two structural regions that are in the vicinity of still water surface and close to the seabed, a damage detection method by using only partial measurement of vibration in a suspect region was presented in this paper, which can not only locate damaged members but also evaluate damage severities. Then employing an experiment platform model under white-noise ground excitation by shaking table and using modal parameters of the first three modes identified by a scalar-type ARMA method on undamaged and damaged structures, the feasibility of the damage detection method was discussed. Modal parameters from eigenvalue analysis on the structural FEM model were also used to help the discussions. It is demonstrated that the damage detection algorithm is feasible on damage location and severity evaluation for broken slanted braces and it is robust against the errors of baseline FEM model to real structure when the principal errors is formed by difference of modal frequencies. It is also found that Z-value changes of modal shapes also play a role in the precise detection of damage.

Bayesian estimation of tension in bridge hangers using modal frequency measurements

  • Papadimitriou, Costas;Giakoumi, Konstantina;Argyris, Costas;Spyrou, Leonidas A.;Panetsos, Panagiotis
    • Structural Monitoring and Maintenance
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    • v.3 no.4
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    • pp.349-375
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    • 2016
  • The tension of an arch bridge hanger is estimated using a number of experimentally identified modal frequencies. The hanger is connected through metallic plates to the bridge deck and arch. Two different categories of model classes are considered to simulate the vibrations of the hanger: an analytical model based on the Euler-Bernoulli beam theory, and a high-fidelity finite element (FE) model. A Bayesian parameter estimation and model selection method is used to discriminate between models, select the best model, and estimate the hanger tension and its uncertainty. It is demonstrated that the end plate connections and boundary conditions of the hanger due to the flexibility of the deck/arch significantly affect the estimate of the axial load and its uncertainty. A fixed-end high fidelity FE model of the hanger underestimates the hanger tension by more than 20 compared to a baseline FE model with flexible supports. Simplified beam models can give fairly accurate results, close to the ones obtained from the high fidelity FE model with flexible support conditions, provided that the concept of equivalent length is introduced and/or end rotational springs are included to simulate the flexibility of the hanger ends. The effect of the number of experimentally identified modal frequencies on the estimates of the hanger tension and its uncertainty is investigated.