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

机译：基于VMD的GNSS与车速表融合及其在桥梁变形监测中的应用

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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.
机译：利用全球导航卫星系统（GNSS）和速度计，计算了江阴大桥中跨的实时动态位移和频谱响应，以了解桥梁结构的动态行为和时间演变。考虑到GNSS的测量噪声较大且速度/加速度传感器无法测量低频位移，因此采用变分分解算法（VMD）提取GNSS的低频位移。然后，结合从GNSS时间序列中提取的低频位移和由速度计计算的高频振动，以实时获得桥梁的高精度三维动态位移。仿真实验和实测数据表明，与常用的经验模态分解（EMD）算法相比，VMD算法能够有效地抵抗噪声和不连续信号引起的模态混叠，保证了获得高精度的融合数据。最后，融合后的位移结果可以识别出毫米级的高频振动和低频位移，可用于计算桥梁的频谱特性，并为评估动，静载荷以及车辆的健康状况提供参考。全频域和全时域中的网桥。

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