Abstract

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.

Highlights

  • Large-scale bridges are the transport lifeline of a country or region, and they cause significant personnel and economic losses when damage occurs

  • GNSS (Global Navigation Satellite System) technology can overcome all these shortcomings [3,4,5], and it has been widely used in bridge deformation monitoring since 1996 [6]

  • To increase the measurement accuracy of the bridge dynamic displacement, the low-frequency movements extracted from GNSS by the Variational Mode Decomposition (VMD) and the vibration information calculated by speedometer were combined together

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Summary

Introduction

Large-scale bridges are the transport lifeline of a country or region, and they cause significant personnel and economic losses when damage occurs. The above-mentioned devices have great shortcomings, such as large workload, cumbersome testing, being restricted by the observation environment, and inability to continuously observe for a long time This causes the low-frequency displacement of the bridge, which cannot be effectively monitored [2]. Due to the frequency domain non-recursive solution method, the decomposition accuracy is high and the modal aliasing problem can be well avoided It has been widely used for mechanical fault diagnosis [18,19], which is the estimation and mitigation of ionospheric scintillation effects on GNSS signal [20]. To increase the measurement accuracy of the bridge dynamic displacement, the low-frequency movements extracted from GNSS by the VMD and the vibration information calculated by speedometer were combined together.

The Derivation of the VMD Algorithm
The Process of the VMD Algorithm
Decompose the GNSS Displacement Time Series by the VMD
Data Fusion of GNSS Low-Frequency Trend and Speedometer Displacement
;4. Results
Results
The Results of Simulation Data
Signal Without Noise
Signal with Noise
Signal
Discontinuous
The Results of Measured Data
14. Integration
Algorithm Applied in Jiangyin Bridge
18. With the VMD
Discussion
Full Text
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