Comparative study of damage identification algorithms applied to a bridge: I. Experiment

被引:319
|
作者
Farrar, CR
Jauregui, DA
机构
[1] Univ Calif Los Alamos Natl Lab, Engn Anal Grp, Los Alamos, NM 87545 USA
[2] Univ Texas, Dept Civil Engn, Austin, TX 78712 USA
来源
SMART MATERIALS & STRUCTURES | 1998年 / 7卷 / 05期
关键词
D O I
10.1088/0964-1726/7/5/013
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
Over the past 30 years detecting damage in a structure from changes in global dynamic parameters has received considerable attention from the civil, aerospace and mechanical engineering communities. The basis for this approach to damage detection is that changes in the structure's physical properties (i.e., boundary conditions, stiffness, mass and/or damping) will, in turn, alter the dynamic characteristics (i.e., resonant frequencies, modal damping and mode shapes) of the structure. Changes in properties such as the flexibility or stiffness matrices derived from measured modal properties and changes in mode shape curvature have shown promise for locating structural damage. However, to date there has not been a study reported in the technical literature that directly compares these various methods. The experimental results reported in this paper and the results of a numerical study reported in an accompanying paper attempt to fill this void in the study of damage detection methods. Five methods for damage assessment that have been reported in the technical literature are summarized and compared using experimental modal data from an undamaged and damaged bridge. For the most severe damage case investigated, all methods can accurately locate the damage. The methods show varying levels of success when applied to less severe damage cases. This paper concludes by summarizing some areas of the damage identification process that require further study.
引用
收藏
页码:704 / 719
页数:16
相关论文
共 50 条
  • [21] Structural damage identification with output-only strain measurements and swarm intelligence algorithms: a comparative study
    Zhang, Guangcai
    Hou, Jiale
    Feng, Kun
    Wan, Chunfeng
    Xie, Liyu
    Xue, Songtao
    Noori, Mohammad
    Ding, Zhenghao
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2024, 35 (05)
  • [22] Comparative Study of Imputation Algorithms Applied to the Prediction of Student Performance
    Crespo-Turrado, Concepcion
    Luis Casteleiro-Roca, Jose
    Sanchez-Lasheras, Fernando
    Antonio Lopez-Vazquez, Jose
    De Cos Juez, Francisco Javier
    Perez Castelo, Francisco Javier
    Luis Calvo-Rolle, Jose
    Corchado, Emilio
    LOGIC JOURNAL OF THE IGPL, 2020, 28 (01) : 58 - 70
  • [23] Identification of Cola Beverages, I. First Study
    Pronko, N. H.
    Bowles, J. W., Jr.
    JOURNAL OF APPLIED PSYCHOLOGY, 1948, 32 (03) : 304 - 312
  • [24] Comparative Study of Blind Channel Identification and Equalization Algorithms
    Elkassimi, Said
    Safi, Said
    Manaut, Bouzid
    Taj, S.
    PROCEEDINGS OF THE SECOND CONFERENCE OF THE MOROCCAN CLASSIFICATION SOCIETY: NEW CHALLENGES IN DATA SCIENCES (SMC '2019), 2019, : 27 - 34
  • [25] A Comparative Study of Image Classification Algorithms for Foraminifera Identification
    Zhong, Boxuan
    Ge, Qian
    Kanakiya, Bhargav
    Mitra, Ritayan
    Marchitto, Thomas
    Lobaton, Edgar
    2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2017, : 3199 - 3206
  • [26] A Comparative Study of Sequence Identification Algorithms in IoT Context
    Greau-Hamard, P-S
    Djoko-Kouam, M.
    Louet, Y.
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN SIGNAL PROCESSING AND ARTIFICIAL INTELLIGENCE, ASPAI' 2020, 2020, : 137 - 143
  • [27] Lateral dynamics of a SUV on deformable surfaces by system identification. Part I. Identification experiment
    Pytka, J.
    INTERNATIONAL AUTOMOTIVE CONFERENCE (KONMOT2018), 2018, 421
  • [28] Comparative Study of Arabic Stemming Algorithms for Topic Identification
    Naili, Marwa
    Chaibi, Anja Habacha
    Ben Ghezala, Henda Hajjami
    KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KES 2019), 2019, 159 : 794 - 802
  • [29] STRUCTURAL MODELS OF ALGORITHMS IN PROBLEMS OF APPLIED PROGRAMMING. I. FORMAL ALGORITHMIC STRUCTURES
    Shynkarenko, V. T.
    Ilman, V. M.
    Skalozub, V. V.
    CYBERNETICS AND SYSTEMS ANALYSIS, 2009, 45 (03) : 329 - 339
  • [30] Identification and level I damage detection of the Z24 highway bridge
    R. Brincker
    P. Andersen
    R. Cantieni
    Experimental Techniques, 2001, 25 : 51 - 57