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

Abstract

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.

Feasibility Analysis of the Performance of Low-Cost Gnss Receivers in Monitoring Dynamic Motion

“…This approach was tested successfully with a dense array of low-cost GNSS receivers, where averaging their measurements reduced the GNSS noise level [16]. (b) Application of high-pass filter independently to the GNSS timeseries of the two low-cost receivers aiming to limit the impact of low-frequency noise of the GNSS data, such as multipath; an approach broadly applied in GNSS time-series analysis [7,28,40].…”

“…The cut-off frequency of 0.1 Hz was adopted by the highpass and low-pass aforementioned, since most low-frequency errors including multipath correspond to frequency band lower than 0.1 Hz [63,64,65]. Furthermore, the main modal frequencies of flexible structures are usually higher than 0.1 Hz, which is why cut-off frequency of 0.1 Hz has been applied in high-pass filterers of GNSS structural monitoring studies [3,7,62]. The u-blox 1 and u-blox 3 high-pass filtered time-series were then averaged to limit the potential impact of the highfrequency noise of the two receivers.…”

“…GNSS technology is a method which provides accurate, continuous, and reliable measurements in independent global coordinate system, reflecting the overall response of the structure and not the locally relative behaviour of structure components [1]. For the last two decades, geodetic GNSS receivers/antennas have been deployed for geodetic monitoring purposes achieving millimetre accuracy [2,3,4,5], with bridge SHM being one of the major areas [6,7]. GNSS technology has been applied in permanent monitoring systems of bridges, such as the Tsing Ma Bridge [8] and Forth Road Bridge [6].…”

“…The continuous development and advancements of satellite systems (i.e., Galileo, Bei-Dou, etc.) have led to the enhanced accuracy of GNSS measurements and the development of methodologies for efficient estimation of bridge response [7,9]. However, the high deployment cost restricted its broader application, especially when multiple locations in a monitoring network are of interest and when the monitoring equipment is subjected to adverse monitoring conditions.…”

Assessment of the accuracy of low-cost multi-GNSS receivers in monitoring dynamic response of structures

“…To investigate the consistency between the two closely coupled low-cost GNSS receivers for the low-frequency component and consequently model their potential common lowfrequency biases due to error sources such as multipath, the E/N/U component of the low-cost GNSS time series were filtered. A low-pass Chebyshev filter of 0.1-Hz cut-off frequency was applied in E/N/U GNSS time series, which is a common approach applied in previous GNSS studies of similar applications (Msaewe et al 2021). Then, the derived low-frequency component GNSS time series of the two lowcost GNSS receivers were analysed using cross-correlation.…”