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

Roberts, Gethin Wyn; Meng, Xiaolin; Psimoulis, Panos; Brown, Christopher J.

doi:10.1007/978-3-030-21718-1_12

Cited by 7 publications

(5 citation statements)

References 63 publications

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“…In addition, some monitored parameters are highly sensitive to environmental and operational conditions, which can mask the changes caused by damage [35,36]. Moreover, the key question remains of whether the SHM system of long-span bridges can be optimised to detect localised damage using global monitored parameters such as displacement and modal frequencies of low-order vibration modes [37].…”

Section: Introductionmentioning

confidence: 99%

Application of GeoSHM System in Monitoring Extreme Wind Events at the Forth Road Bridge

et al. 2019

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Implementation of Structural Health Monitoring systems on long-span bridges has become mandatory in many countries to ascertain the safety of these structures and the public, taking into account an increase in usage and threats due to extreme loading conditions. However, the successful delivery of such a system is facing many challenges including the failure to extract damage and reliability information from monitoring data to assist bridge operators with their maintenance planning and activities. Supported by the European Space Agency under the Integrated Applications Promotion scheme, the project ‘GNSS and Earth Observation for Structural Health Monitoring of Long-span Bridges’ or GeoSHM aims to address some of these shortcomings (GNSS stands for Global Navigation Satellite System). In this paper, the background of the GeoSHM project as well as the GeoSHM sensor system on the Forth Road Bridge (FRB) in Scotland will be briefly described. The bridge response and wind data collected over a two-year period from 15 October 2015 to 15 October 2017 will be analysed to demonstrate the high susceptibility of the bridge to wind loads. Close examination of the data associated with an extreme wind event in 2018—Storm Ali—will be conducted to reveal the relationship between the wind speed and some monitored parameters such as the bridge response and modal frequencies.

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Section: Introductionmentioning

confidence: 99%

Application of GeoSHM System in Monitoring Extreme Wind Events at the Forth Road Bridge

et al. 2019

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“…Global Positioning System (GPS) double differencing (DD) is a well-established method for bridge displacement monitoring (Ashkenazi and Roberts 1997;Roberts et al 2020). High precision can be achieved for structure displacement monitoring as major GPS errors can be largely eliminated or significantly reduced through the DD method.…”

Section: Introductionmentioning

confidence: 99%

PPP-derived tropospheric ZWD augmentation from local CORS network tested on bridge monitoring points

Tang

Liu

Roberts

et al. 2022

Advances in Space Research

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“…When the direct signals, reflected signals and diffracted signals of global positioning system (GPS) satellites reach the receiver antenna simultaneously, the interference will lead to an important error called the multipath error [1]. For carrier phase observations, the maximum error can be as 2 of 18 large as 1/4 the wavelength [2].…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Mitigating the GPS Multipath Effect Based on a Multi-Point Hemispherical Grid Model

et al. 2020

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The multipath effect is a crucial error source caused by the environment around the station and cannot be eliminated or mitigated by differential algorithms. Theoretically, the maximum value for the carrier phase is a quarter the wavelength, i.e., about 4.8 cm for the GPS L1 signal. Considering the increasing demands of high-precision applications, the multipath error has become a major factor affecting the accuracy and reliability of GPS millimeter-level data processing. This paper proposes a multi-point hemispherical grid model (MHGM) to mitigate the multipath effect. In this method, the hemisphere centered on each station is divided into a grid, and the multipath error at the station is estimated based on the parameterization of the grid points. The double-differenced (DD) observed-minus-calculated (OMC) values on some previous days are treated as the observation values to model the present multipath error. Contrary to the present methods which rely much on the platform of data collection and processing, MHGM can be potentially applied to GPS data processing with the existing hardware and software. Experiments in high-multipath and low-multipath environments are designed by mounting a baffle or not. The experimental results show that MHGM is effective in mitigating the multipath effect. When using data from the previous day, an average improvement of about 63.3% in the RMS of DD OMC can be made compared with that without correction, and this is basically consistent with the sidereal filtering (SF) method which is 63.0%. Furthermore, the effectiveness of the above two methods is better than that of the empirical site model (ESM). The kinematic positioning results are also basically consistent with the statistical results of the RMS values of DD OMC. Historical data from more than one day can more explicitly and effectively model the MHGM. Furthermore, compared with the SF method, the MHGM can be used not only to mitigate the multipath error, but also to orientate the sources of the multipath error around the station, and give guidance in the physical elimination of these sources.

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

Cited by 7 publications

References 63 publications

Application of GeoSHM System in Monitoring Extreme Wind Events at the Forth Road Bridge

Application of GeoSHM System in Monitoring Extreme Wind Events at the Forth Road Bridge

PPP-derived tropospheric ZWD augmentation from local CORS network tested on bridge monitoring points

A Novel Method for Mitigating the GPS Multipath Effect Based on a Multi-Point Hemispherical Grid Model

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