Measurement and correlation of displacements on the Severn Suspension Bridge using GPS

Roberts, Gethin Wyn; Tang, Xu; Brown, Christopher J.

doi:10.1007/s12518-018-00251-6

Cited by 8 publications

(7 citation statements)

References 26 publications

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“…The case study of Severn Suspension Bridge can be considered as suitable for the PP method, since the bridge modal frequencies are considered as well-separated. 56 Furthermore, the assessment of the beneficial contribution of multi-GNSS was based on modal frequencies, which were confirmed by previous studies 46,48 and time intervals of known conditions of excitation/loading.…”

Section: Severn Bridge Response-spectral Analysissupporting

confidence: 75%

“…Those frequencies are also confirmed from the frequencies confirmed in previous studies. 46,48 The frequency of 0.147 Hz corresponds to the first vertical mode of the bridge and matches with the first modal frequency of the tower in the longitudinal axis. The frequency of 0.095 Hz corresponds to the first lateral mode of the bridge, which is typical for long-span bridges to be lower than the first vertical modal frequency (i.e., 0.147 Hz), and the frequency of 0.226 Hz which seems to correspond to the second vertical mode of the midspan.…”

Section: Severn Bridge Response-spectral Analysismentioning

confidence: 56%

“…Previous studies of monitoring Severn Suspension Bridge, which were based on both GNSS monitoring campaigns (2010 and 2015), have revealed that the main modal frequencies of the midspan are 0.147 and 0.226 Hz, at the vertical component, and 0.09 Hz at the lateral component, while for the tower, the main modal frequency is 0.147 Hz on the longitudinal component, which reflects the impact of the first mode of the deck on the towers. 46,48 Regarding the vertical response at the midspan, it can reach 10-20 cm, depending on the vehicle loading, and the longitudinal/lateral response of the towers may reach even up to 2 cm. 11,45,46,48…”

Section: Severn Bridge Monitoringmentioning

confidence: 99%

“…46,48 Regarding the vertical response at the midspan, it can reach 10-20 cm, depending on the vehicle loading, and the longitudinal/lateral response of the towers may reach even up to 2 cm. 11,45,46,48…”

Section: Severn Bridge Monitoringmentioning

confidence: 99%

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Monitoring the response of Severn Suspension Bridge in the United Kingdom using multi‐GNSS measurements

Msaewe

Psimoulis

Hancock

et al. 2021

Structural Contr & Hlth

Self Cite

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The application of GPS in bridge monitoring aims to determine accurately and precisely the response of the deck and towers of the bridge and estimate the main response characteristics (amplitude and modal frequencies). The main requirement of GPS monitoring is a high level of accuracy and availability of fixed solutions, which ensure the reliable operation of GPS and result in the precise estimation of the bridge's response. However, the derived GPS time series of bridge monitoring can be contaminated by noise, due to the performance of the GPS satellite(s), the geometry of the GPS satellite constellation and the potential obstructions due to the bridge elements, which can even lead to GPS solution of poor accuracy and/or precision and result in reduced efficiency of the performance of the GPS monitoring. This study investigates the potential contribution of other Global Navigation Satellite Systems (GNSS) constellations for a more robust and reliable displacement time series solution, derived from multi-GNSS records. More specifically, a novel method is developed to derive the optimal combination of GNSS records to determine the GNSS displacement time series based on checks of parameters which reflect the geometry of the satellite constellation and the quality of the GNSS satellites signals. The method is applied in monitoring of the Severn Suspension Bridge, in the United Kingdom, and it is revealed the enhancement in the GNSS monitoring performance of the bridge response for specific time intervals for various locations on the bridge's support towers, suspension cables and deck.

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Section: Severn Bridge Response-spectral Analysissupporting

confidence: 75%

Section: Severn Bridge Response-spectral Analysismentioning

confidence: 56%

Section: Severn Bridge Monitoringmentioning

confidence: 99%

Section: Severn Bridge Monitoringmentioning

confidence: 99%

See 2 more Smart Citations

Monitoring the response of Severn Suspension Bridge in the United Kingdom using multi‐GNSS measurements

Msaewe

Psimoulis

Hancock

et al. 2021

Structural Contr & Hlth

Self Cite

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show abstract

“…Furthermore, reliable traffic measurements and traffic monitoring to prevent network congestion and to prevent the depletion of the capacity of nodes in the transport network are very important. Some scholars have proposed traffic flow monitoring or prediction methods for road network nodes under emergencies [23][24][25][26]. In addition, many scholars have carried out research on traffic emergency disposal measures and methods under urban road network emergencies [27][28][29][30].…”

Section: It Is Necessary To Determine the Classification Parametersmentioning

confidence: 99%

A Grade Identification Method of Critical Node in Urban Road Network Based on Multi-Attribute Evaluation Correction

et al. 2022

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Accurately identifying the key nodes of the road network and focusing on its management and control is an important means to improve the robustness and invulnerability of the road network. In this paper, a classification and identification method of key nodes in urban road networks based on multi-attribute evaluation and modification was proposed. Firstly, the emergency function guarantee grade of road network nodes was divided by comprehensively considering the importance of road network nodes, the consequences of failure, and the degree of difficulty of recovery. The evaluation indexes were selected according to the local attributes, global attributes, and functional attributes of the road network topology. The spatial distribution patterns of the evaluation indexes of the nodes were analyzed. The dynamic classification method was used to cluster the attributes of the road network nodes, and the TOPSIS method was used to comprehensively evaluate the importance ranking of the road network nodes. Attribute clustering of road network nodes by dynamic classification method (DT) and the TOPSIS method was used to comprehensively evaluate the ranking of the importance of road network nodes. Then, combined with the modification of the comprehensive evaluation and ranking of the importance of the road network nodes, the emergency function support classification results of the road network nodes were obtained. Finally, the method was applied to the road network within the second Ring Road of Beijing. It was compared with the clustering method of self-organizing competitive neural networks. The results show that this method can identify the key nodes of the road network more accurately. The first-grade key nodes are all located at the more important intersections on expressways and trunk roads. The spatial distribution pattern shows a “center-edge” pattern, and the important traffic corridors of the road network show a “five vertical and five horizontal” pattern.

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Time Series Analysis of Rapid GNSS Measurements for Quasi-static and Dynamic Bridge Monitoring

Roberts

Meng

Psimoulis

et al. 2019

Geodetic Time Series Analysis in Earth Sciences

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Measurement and correlation of displacements on the Severn Suspension Bridge using GPS

Cited by 8 publications

References 26 publications

Monitoring the response of Severn Suspension Bridge in the United Kingdom using multi‐GNSS measurements

Monitoring the response of Severn Suspension Bridge in the United Kingdom using multi‐GNSS measurements

A Grade Identification Method of Critical Node in Urban Road Network Based on Multi-Attribute Evaluation Correction

Time Series Analysis of Rapid GNSS Measurements for Quasi-static and Dynamic Bridge Monitoring

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