Qusen Chen

Design and Implementation of a New System for Large Bridge Monitoring—GeoSHM

Structural Health Monitoring (SHM) is a relatively new branch of civil engineering that focuses on assessing the health status of infrastructure, such as long-span bridges. Using a broad range of in-situ monitoring instruments, the purpose of the SHM is to help engineers understand the behaviour of structures, ensuring their structural integrity and the safety of the public. Under the Integrated Applications Promotion (IAP) scheme of the European Space Agency (ESA), a feasibility study (FS) project that used the Global Navigation Satellite Systems (GNSS) and Earth Observation (EO) for Structural Health Monitoring of Long-span Bridges (GeoSHM) was initiated in 2013. The GeoSHM FS Project was led by University of Nottingham and the Forth Road Bridge (Scotland, UK), which is a 2.5 km long suspension bridge across the Firth of Forth connecting Edinburgh and the Northern part of Scotland, was selected as the test structure for the GeoSHM FS project. Initial results have shown the significant potential of the GNSS and EO technologies. With these successes, the FS project was further extended to the demonstration stage, which is called the GeoSHM Demo project where two other long-span bridges in China were included as test structures. Led by UbiPOS UK Ltd. (Nottingham, UK), a Nottingham Hi-tech company, this stage focuses on addressing limitations identified during the feasibility study and developing an innovative data strategy to process, store, and interpret monitoring data. This paper will present an overview of the motivation and challenges of the GeoSHM Demo Project, a description of the software and hardware architecture and a discussion of some primary results that were obtained in the last three years.

Vertical Deformation Monitoring of the Suspension Bridge Tower Using GNSS: A Case Study of the Forth Road Bridge in the UK

The vertical deformation monitoring of a suspension bridge tower is of paramount importance to maintain the operational safety since nearly all forces are eventually transferred as the vertical stress on the tower. This paper analyses the components affecting the vertical deformation and attempts to reveal its deformation mechanism. Firstly, we designed a strategy for high-precision GNSS data processing aiming at facilitating deformation extraction and analysis. Then, 33 months of vertical deformation time series of the southern tower of the Forth Road Bridge (FRB) in the UK were processed, and the accurate subsidence and the parameters of seasonal signals were estimated based on a classic function model that has been widely studied to analyse GNSS coordinate time series. We found that the subsidence rate is about 4.7 mm/year, with 0.1 mm uncertainty. Meanwhile, a 15-month meteorological dataset was utilised with a thermal expansion model (TEM) to explain the effects of seasonal signals on tower deformation. The amplitude of the annual signals correlated quite well that obtained by the TEM, with the consistency reaching 98.9%, demonstrating that the thermal effect contributes significantly to the annual signals. The amplitude of daily signals displays poor consistency with the ambient temperature data. However, the phase variation tendencies between the daily signals of the vertical deformation and the ambient temperature are highly consistent after February 2016. Finally, the potential contribution of the North Atlantic Drift (NAD) to the characteristics of annual and daily signals is discussed because of the special geographical location of the FRB. Meanwhile, this paper emphasizes the importance of collecting more detailed meteorological and other loading data for the investigation of the vertical deformation mechanism of the bridge towers over time with the support of GNSS.

Analysis of Seasonal Signal in GPS Short-Baseline Time Series

Proper modeling of seasonal signals and their quantitative analysis are of interest in geoscience applications, which are based on position time series of permanent GPS stations. Seasonal signals in GPS short-baseline (<u20092xa0km) time series, if they exist, are mainly related to site-specific effects, such as thermal expansion of the monument (TEM). However, only part of the seasonal signal can be explained by known factors due to the limited data span, the GPS processing strategy and/or the adoption of an imperfect TEM model. In this paper, to better understand the seasonal signal in GPS short-baseline time series, we adopted and processed six different short-baselines with data span that varies from 2 to 14xa0years and baseline length that varies from 6 to 1100xa0m. To avoid seasonal signals that are overwhelmed by noise, each of the station pairs is chosen with significant differences in their height (>u20095xa0m) or type of the monument. For comparison, we also processed an approximately zero baseline with a distance ofu2009<u20091xa0m and identical monuments. The daily solutions show that there are apparent annual signals with annual amplitude ofu2009~u20091xa0mm (maximum amplitude of 1.86u2009±u20090.17xa0mm) on almost all of the components, which are consistent with the results from previous studies. Semi-annual signal with a maximum amplitude of 0.97u2009±u20090.25xa0mm is also present. The analysis of time-correlated noise indicates that instead of flicker (FL) or random walk (RW) noise, band-pass-filtered (BP) noise is valid for approximately 40% of the baseline components, and another 20% of the components can be best modeled by a combination of the first-order Gauss–Markov (FOGM) process plus white noise (WN). The TEM displacements are then modeled by considering the monument height of the building structure beneath the GPS antenna. The median contributions of TEM to the annual amplitude in the vertical direction are 84% and 46% with and without additional parts of the monument, respectively. Obvious annual signals with amplitudeu2009>u20090.4xa0mm in the horizontal direction are observed in five short-baselines, and the amplitudes exceed 1xa0mm in four of them. These horizontal seasonal signals are likely related to the propagation of daily/sub-daily TEM displacement or other signals related to the site environment. Mismodeling of the tropospheric delay may also introduce spurious seasonal signals with annual amplitudes ofu2009~u20095 andu2009~u20092xa0mm, respectively, for two short-baselines with elevation differences greater than 100xa0m. The results suggest that the monument height of the additional part of a typical GPS station should be considered when estimating the TEM displacement and that the tropospheric delay should be modeled cautiously, especially with station pairs with apparent elevation differences. The scheme adopted in this paper is expected to explicate more seasonal signals in GPS coordinate time series, particularly in the vertical direction.

Required navigation performance for connected and autonomous vehicles: where are we now and where are we going?

ABSTRACT While automotive original equipment manufacturers and IT companies are developing and demonstrating self-driving cars, true autonomy will not be realised in the near future due in part to the technology readiness level of the existing systems as well as issues of ethics, security, governance and standards surrounding the implementation of autonomy for road transport. However, advances in cellular phones and networks, satellite-based positioning and communications, cloud computing, combined with a rise in the volumes of available data, allied with a reduction in their costs, offer the very real possibility of connecting vehicles, one to another and to smart city infrastructure as part of the Internet of Things (IoT). Data from connected vehicles, when combined with other information, may provide valuable intelligence to traffic managers and other stakeholders via cooperative intelligent transport system (C-ITS) platforms. Nevertheless, many issues face the implementation of a truly connected IoT in general and C-ITS in particular.

GNSS for real-time monitoring of bridge dynamic responses

Global Navigation Satellite Systems (GNSS) Realtime Kinematic (RTK) positioning technique has been widely used for the structural health monitoring (SHM) of different structures in the past two decades. Through post processing and analysis, it has been demonstrated that the displacements and natural frequencies identified with GNSS data are highly consistent with those obtained by using a finite element (FE) model. However, structural health monitoring needs to measure all spectrum of the dynamic responses of bridges such as deformations, natural frequencies, damping, etc. in real-time in order to support the timely decision making for the bridge operation and maintenance, particularly under extreme loading conditions caused by busy traffic, severe wind or even earthquake etc. This paper proposes a new quasi real time time-frequency analysis strategy based on the Fast Fourier Transform (FFT). With the support of the European Space Agency (ESA) and the University of Nottingham in the UK, one week of real-life GNSS data gathered from the Forth Road Bridge in Scotland has been used since the traffic loading has an approximate repetition period of one week from the weekdays to weekend. Firstly, the approximate frequency distribution is achieved by using the whole date set. Then a sliding window method is proposed to simulate a quasi real time mode for the time-frequency analysis, and a set of experiments are carried out to decide the optimal window length and the overlapped sliding step, through which the natural frequencies and relevant deformation amplitudes can be calculated at the same time. Finally, the results show that the natural frequencies calculated by FFT are quite stable which indicates the frequency responses are not sensitive enough to the changing loadings. However, the relevant amplitude time series of each frequency can clearly display the influence caused by different kinds of loading respectively, such as vehicles and wind etc., which would be a reliable indicator of bridge dynamic responses to assess the structural health conditions in the future.

Feasibility analysis of low-cost GNSS receivers for achieving required positioning performance in CAV applications

For Connected and Autonomous Vehicle (CAV) applications, the location solution is desired to provide better than 0.1m real-time positioning accuracy. This level of accuracy can only be achieved by using geodetic GNSS receivers under an open sky observation condition, and each unit costs around £20,000. This kind of geodetic GNSS receiver is not a good option for mass market use in terms of price and ubiquity aspects. Therefore, using low-cost receiver to achieve real-time, high accuracy and ubiquitous positioning performance could be a future trend. This paper will first establish a framework of assessing low-cost receivers based on required navigation performance (RNP) concept in aviation and required accuracy categories in ITS. Then adynamic test that was conducted to simulate the future CAV driving environment will be introduced. Under the guidance of the former established framework, the collected data was post-processed to explore the real positioning performance of both two grades receivers. By comparing real-time/post-processed results and high-end/low-cost receivers, the limitations and technical gaps between two types of receivers, as well as current positioning solution and required positioning performance will be identified.