Fusion of GNSS and Speedometer Based on VMD and Its Application in Bridge Deformation Monitoring

被引:28
|
作者
Zhang, Ruicheng [1 ]
Gao, Chengfa [1 ]
Pan, Shuguo [2 ]
Shang, Rui [1 ]
机构
[1] Southeast Univ, Sch Transportat, Nanjing 211189, Peoples R China
[2] Southeast Univ, Sch Instrument Sci & Engn, Nanjing 210096, Peoples R China
关键词
GNSS; speedometer; VMD; dynamic displacement; bridge deformation monitoring; MODE DECOMPOSITION; INTEGRATED GPS;
D O I
10.3390/s20030694
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Real-time dynamic displacement and spectral response on the midspan of Jiangyin Bridge were calculated using Global Navigation Satellite System (GNSS) and a speedometer for the purpose of understanding the dynamic behavior and the temporal evolution of the bridge structure. Considering that the GNSS measurement noise is large and the velocity/acceleration sensors cannot measure the low-frequency displacement, the Variational Mode Decomposition (VMD) algorithm was used to extract the low-frequency displacement of GNSS. Then, the low-frequency displacement extracted from the GNSS time series and the high-frequency vibration calculated by speedometer were combined in this paper in order to obtain the high precision three-dimensional dynamic displacement of the bridge in real time. Simulation experiment and measured data show that the VMD algorithm could effectively resist the modal aliasing caused by noise and discontinuous signals compared with the commonly used Empirical Mode Decomposition (EMD) algorithm, which is guaranteed to get high-precision fusion data. Finally, the fused displacement results can identify high-frequency vibrations and low-frequency displacements of a mm level, which can be used to calculate the spectral characteristics of the bridge and provide reference to evaluate the dynamic and static loads, and the health status of the bridge in the full frequency domain and the full time domain.
引用
收藏
页数:19
相关论文
共 28 条
  • [1] An Improved Multipath Mitigation Method and Its Application in Real-Time Bridge Deformation Monitoring
    Zhang, Ruicheng
    Gao, Chengfa
    Zhao, Qing
    Peng, Zihan
    Shang, Rui
    REMOTE SENSING, 2021, 13 (12)
  • [2] Enhancing GNSS Deformation Monitoring Forecasting with a Combined VMD-CNN-LSTM Deep Learning Model
    Xie, Yilin
    Meng, Xiaolin
    Wang, Jun
    Li, Haiyang
    Lu, Xun
    Ding, Jinfeng
    Jia, Yushan
    Yang, Yin
    REMOTE SENSING, 2024, 16 (10)
  • [3] Vertical Deformation Monitoring of the Suspension Bridge Tower Using GNSS: A Case Study of the Forth Road Bridge in the UK
    Chen, Qusen
    Jiang, Weiping
    Meng, Xiaolin
    Jiang, Peng
    Wang, Kaihua
    Xie, Yilin
    Ye, Jun
    REMOTE SENSING, 2018, 10 (03):
  • [4] Ground Deformation Monitoring for Subway Structure Safety Based on GNSS
    Tan, Dongmei
    Li, An
    Ji, Baifeng
    Duan, Jiayi
    Tao, Yu
    Luo, Hao
    BUILDINGS, 2023, 13 (11)
  • [5] Fusion of INS with GNSS and its application to Mobile Robot Navigation
    Domenech, L.
    Armesto, L.
    Tornero, J.
    6TH INTERNATIONAL INDUSTRIAL SIMULATION CONFERENCE 2008, 2008, : 156 - 160
  • [6] An Improved GNSS and InSAR Fusion Method for Monitoring the 3D Deformation of a Mining Area
    Zhou, Wentao
    Zhang, Wenjun
    Yang, Xinchun
    Wu, Weiqiang
    IEEE ACCESS, 2021, 9 : 155839 - 155850
  • [7] Research on GNSS Deformation Monitoring Based on Multi-baseline Solution
    Wang, Haonan
    Dai, Wujiao
    Yu, Wenkun
    CHINA SATELLITE NAVIGATION CONFERENCE PROCEEDINGS, CSNC 2022, VOL I, 2022, 908 : 219 - 233
  • [8] Displacement detection based on Bayesian inference from GNSS kinematic positioning for deformation monitoring
    Shen, Nan
    Chen, Liang
    Chen, Ruizhi
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2022, 167
  • [9] GNSS/accelerometer integrated deformation monitoring algorithm based on sensors adaptive noise modeling
    Jing, Ce
    Huang, Guanwen
    Li, Xin
    Zhang, Qin
    Yang, Huan
    Zhang, Kai
    Liu, Guolin
    MEASUREMENT, 2023, 218
  • [10] Fusion of numerical meteorological data to mitigate residual tropospheric error in GNSS RTK for large bridge monitoring in mountainous areas
    Liu, Guolin
    Huang, Guanwen
    Li, Xin
    Jing, Ce
    Yang, Huan
    Gao, Yang
    MEASUREMENT, 2025, 243