A Novel Acceleration-Based Approach for Monitoring the Long-Term Displacement of Bridge Cables

被引:12
|
作者
Zhang, Han [1 ]
Mao, Jianxiao [1 ]
Wang, Hao [1 ]
Zhu, Xiaojie [1 ]
Zhang, Yiming [1 ]
Gao, Hui [1 ]
Ni, Youhao [1 ]
Hai, Zong [1 ]
机构
[1] Southeast Univ, Minist Educ, Key Lab Concrete & Prestressed Concrete Struct, Nanjing 211189, Peoples R China
基金
中国国家自然科学基金;
关键词
Bridge cables; displacement estimation; acceleration-based approach; long-term; monitoring; DOUBLE INTEGRATION; INDUCED VIBRATIONS; SYSTEM; GPS; IDENTIFICATION; ACCELEROMETER; RELIABILITY; RECORDINGS;
D O I
10.1142/S0219455423500530
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The cables of the long-span bridge are usually featured as ultra-low frequency, hence making the acceleration unable to accurately capture the information, e.g. damping ratios, for assessing the cable state assessment and mitigating the excessive structural vibration. The displacement was approved to be more sensitive to the low-frequency vibration than the acceleration. However, there is still a lack of effective method to accurately monitor the long-term displacements of bridge cables using reference-free methods. To address this issue, this paper develops a novel acceleration-based approach for monitoring the long-term displacements of the cables of long-span bridges. In the monitoring scheme, recursive least squares method is utilized to conduct baseline correction in the time domain integration of acceleration. An adaptive band-pass filtering method considering cable vibration characteristics is used to eliminate noise, thus avoiding the difficulty of selecting the cut-off frequency by experience in traditional methods. A numerical test of an analytical cable model and a field experiment of the hanger of a full-scale suspension bridge are applied to the applicability and robustness of the developed method. Result shows that adaptive band-pass filter considering the vibration characteristics is suitable for estimating the displacements of the cables. The estimated displacements using the developed method agree well with the background truth in both time and frequency domains.
引用
收藏
页数:23
相关论文
共 50 条
  • [31] Fusion Estimation of Structural Dynamic Displacement Based on Vision- and Acceleration-Based Measurements
    Chunbao, Xiong
    Changbao, Sun
    Yanbo, Niu
    Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/Journal of Tianjin University Science and Technology, 2024, 57 (09): : 891 - 901
  • [32] Unsupervised adaptation for acceleration-based activity recognition: robustness to sensor displacement and rotation
    Ricardo Chavarriaga
    Hamidreza Bayati
    José del R. Millán
    Personal and Ubiquitous Computing, 2013, 17 : 479 - 490
  • [33] Unsupervised adaptation to on-body sensor displacement in acceleration-based activity recognition
    Bayati, Hamidreza
    Millan, Jose del R.
    Chavarriaga, Ricardo
    2011 15TH ANNUAL INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS (ISWC), 2011, : 71 - 78
  • [34] Deep learning-based reconstruction of missing long-term girder-end displacement data for suspension bridge health monitoring
    Wang, Zhi-wei
    Lu, Xiao-fan
    Zhang, Wen-ming
    Fragkoulis, Vasileios C.
    Beer, Michael
    Zhang, Yu-feng
    COMPUTERS & STRUCTURES, 2023, 284
  • [35] Unsupervised adaptation for acceleration-based activity recognition: robustness to sensor displacement and rotation
    Chavarriaga, Ricardo
    Bayati, Hamidreza
    Millan, Jose del R.
    PERSONAL AND UBIQUITOUS COMPUTING, 2013, 17 (03) : 479 - 490
  • [36] A bridge displacement monitoring method by fusing acceleration and tilt photogrammetry-based measurement
    Tang L.
    Wu T.
    Liu Y.
    Li X.
    Yu K.
    Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, 2022, 43 (10): : 152 - 164
  • [37] Long-term monitoring of a hybrid cable-stayed bridge
    Zhang, GY
    Sensing Issues in Civil Structural Health Monitoring, 2005, : 485 - 494
  • [38] Instrumentation system performance for long-term bridge health monitoring
    Farhey, Daniel N.
    STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2006, 5 (02): : 143 - 153
  • [39] Long-term structural health monitoring for Tamar Suspension Bridge
    Koo, K. Y.
    Brownjohn, J. M. W.
    Carden, P.
    List, D. I.
    Cole, R.
    Wood, T.
    BRIDGE MAINTENANCE, SAFETY, MANAGEMENT AND LIFE-CYCLE OPTIMIZATION, 2010, : 348 - +
  • [40] The Rail Bridge Bearing Long-term Online Monitoring and Analysis
    Liu, Jun
    ADVANCES IN INDUSTRIAL AND CIVIL ENGINEERING, PTS 1-4, 2012, 594-597 : 1153 - 1156