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This paper explores the development of a smart Structural Health Monitoring (SHM) platform tailored for long-span bridge monitoring, using the Forth Road Bridge (FRB) as a case study. It discusses the selection of smart sensors available for real-time monitoring, the formulation of an effective data strategy encompassing the collection, processing, management, analysis, and visualization of monitoring data sets to support decision-making, and the establishment of a cost-effective and intelligent sensor network aligned with the objectives set through comprehensive communication with asset owners. Due to the high data rates and dense sensor installations, conventional processing techniques are inadequate for fulfilling monitoring functionalities and ensuring security. Cloud-computing emerges as a widely adopted solution for processing and storing vast monitoring data sets. Drawing from the authors' experience in implementing long-span bridge monitoring systems in the UK and China, this paper compares the advantages and limitations of employing cloud- computing for long-span bridge monitoring. Furthermore, it explores strategies for developing a robust data strategy and leveraging artificial intelligence (AI) and digital twin (DT) technologies to extract relevant information or patterns regarding asset health conditions. This information is then visualized through the interaction between physical and virtual worlds, facilitating timely and informed decision-making in managing critical road transport infrastructure. [ABSTRACT FROM AUTHOR]

Aging, corrosive environments, and inadequate maintenance may result in performance deterioration of civil infrastructures, and finite element model updating is a commonly employed structural health monitoring procedure in civil engineering to reflect the current situation and to ensure the safety and serviceability of structures. Using the finite element model updating process to obtain the relationship between the structural responses and updating parameters, this paper proposes a method of using the wavelet neural network (WNN) as the surrogate model combined with the wind-driven optimization (WDO) algorithm to update the structural finite element model. The method was applied to finite element model updating of a continuous beam structure of three equal spans to verify its feasibility, the results show that the WNN can reflect the nonlinear relationship between structural responses and the parameters and has an outstanding simulation performance; the WDO has an excellent ability for optimization and can effectively improve the efficiency of model updating. Finally, the method was applied to update a real bridge model, and the results show that the finite element model update based on WDO and WNN is applicable to the updating of a multi-parameter bridge model, which has practical significance in engineering and high efficiency in finite element model updating. The differences between the updated values and measured values are all within the range of 5%, while the maximum difference was reduced from −10.9% to −3.6%. The proposed finite element model updating method is applicable and practical for multi-parameter bridge model updating and has the advantages of high updating efficiency, reliability, and practical significance. [ABSTRACT FROM AUTHOR]

Structural health monitoring (SHM) has attracted significant attention over the past two decades due to its ability to provide real-time insight into the condition of structures. Despite the development of several SHM systems for long-span bridges, which play a crucial role in the assessment of these structures, studies focusing on short- or middle-span bridges remain scarce. This research paper presents an efficient and practical bridge monitoring and warning system established on a middle-span bridge, a key crossroad bridge located in Shenzhen. The monitoring system consists of sensors and measuring points that collect a substantial amount of data, enabling the close monitoring of various operational indicators to facilitate the early detection of threshold exceedances. Based on this system, the subtle condition of the bridge can be evaluated, and the operational condition of the bridge can be studied through the comparative analysis of the collected data. Over four months of monitoring, data including the strain and creep of the main beam, the strain and settlement of piers and the crack width of the bridge body are observed. Furthermore, the real-time operational status of the bridge is analyzed and evaluated through the combination of the collected data and the structural finite element model. [ABSTRACT FROM AUTHOR]

Structural displacement monitoring is one of the major tasks of structural health monitoring and it is a significant challenge for research and engineering practices relating to large-scale civil structures. While computer vision-based structural monitoring has gained traction, current practices largely focus on laboratory experiments, small-scale structures, or close-range applications. This paper demonstrates its applications on three landmark long-span suspension bridges in Turkey: the First Bosphorus Bridge, the Second Bosphorus Bridge, and the Osman Gazi Bridge, among the longest landmark bridges in the world, with main spans of 1074 m, 1090 m, and 1550 m, respectively. The presented studies achieved non-contact displacement monitoring from a distance of 600 m, 755 m, and 1350 m for the respective bridges. The presented concepts, analysis, and results provide an overview of long-span bridge monitoring using computer vision-based monitoring. The results are assessed with conventional monitoring approaches and finite element analysis based on observed traffic conditions. Both displacements and dynamic frequencies align well with these conventional techniques and finite element analyses. This study also highlights the challenges of computer vision-based structural monitoring of long-span bridges and presents considerations such as the encountered adverse environmental factors, target and algorithm selection, and potential directions of future studies. [ABSTRACT FROM AUTHOR]

Structural Health Monitoring (SHM) is a technique that involves gathering information to ensure that a structure is safe and behaving as expected. Within SHM, vibration-based monitoring is generally seen as one of the more cost-effective types of monitoring. However, vibration-based monitoring has mostly been undertaken on long-span bridges using data collected with a dense network of sensors. Historically, the logistical difficulty of collecting data on short- and medium-span bridges has meant that the usefulness of vibration-based methods on these bridges is largely unknown. Therefore, this study proposes Minimal Information Data-modelling (MID). MID is an approach that utilises low-cost, easily implementable sensors that are potentially feasible for operators to purchase and operate across a network. This approach will be investigated to determine whether MID is a feasible approach for monitoring short- and medium- span bridges. The results from MID were assessed to determine whether they could detect a suitably small shift in frequency, which is indicative of damage. It was determined that the data models could reliably detect frequency shifts as low as 0.01 Hz. This magnitude of frequency shift is similar to the level of frequency shift reported for a range of bridge damage cases found by others and validated with FE models. The accuracy achieved by the data models indicates that MID could potentially be used as a damage detection method. The cost of the equipment used to collect the data was approximately £370, demonstrating that it is feasible to use MID to monitor bridges across an entire network. [ABSTRACT FROM AUTHOR]

Establishing an online perception mechanism for a driver's front blind area on a full bridge under vertical vortex-induced vibration (VVIV) is essential for ensuring road safety and traffic control on bridge decks under specific conditions. Based on accelerations of vibration monitoring of the main girders, this paper uses a real-time acceleration integration algorithm to obtain real-time displacements of measurement points; realizes the real-time estimation of the dynamic configurations of a main girder through parametric function fitting; and then can perceive the front blind area for vehicles driving on bridges experiencing VVIV in real time. On this basis, taking a long-span suspension bridge suffering from VVIV as an engineering example, the influence of different driving conditions on the front blind area is examined. Then, the applicability of the intelligent perception technology framework of the front blind area is verified. The results indicate that, during VVIV, the driver's front blind area changes periodically and the vehicle model has the most significant impact on the front blind area; in contrast, the vehicle's speed and the times of the vehicle entering the bridge have minimal impact on it. Meanwhile, it is shown that the framework can accurately perceive front blind areas of vehicles driving on the bridge, and identify different vehicle models, speeds and times of vehicle bridge entries in real time. [ABSTRACT FROM AUTHOR]

Structural health monitoring (SHM) systems have been widely applied in long-span bridges and a large amount of SHM data is continually collected. The harsh environment of sensors installed at structures causes multiple types of anomalies such as outlier, minor, missing, trend, drift, and break in the SHM data, which seriously hinders the further analysis of SHM data. In order to achieve anomaly detection from a large amount of SHM data, this paper proposes a long-short term memory (LSTM) network-based anomaly detection method. Firstly, the proposed method reduces the workload for preparing training sets. Secondly, the purpose of real-time anomaly detection can be met. Thirdly, the problem of high alarm rate can be avoided by utilizing double thresholds. To validate the effectiveness of the proposed method, a case study of finite element model simulation is firstly introduced, which illustrates the detailed implementation process. Finally, acceleration data from the SHM system of a long-span suspension bridge located in Jiangyin, China is employed. The results show that the proposed method can detect anomaly with high accuracy and identify abnormal accidents such as a ship collision quickly. [ABSTRACT FROM AUTHOR]

Bridges and subgrades are the main route forms for expressways. The ideal form for passing through sandy areas remains unclear. This study aims to understand the differences in the influence of expressway bridges and subgrades on the near-surface blown sand environment and movement laws, such as the difference in wind speed and profile around the bridge and subgrade, the difference in wind flow-field characteristics, and the difference in sand transport rate, to provide a scientific basis for the selection of expressway route forms in sandy areas. Therefore, a wind tunnel test was carried out by making models of a highway bridge and subgrade and comparing the environmental effects of wind sand on them. The disturbance in the bridge to near-surface blown sand activities was less than that of the subgrade. The variation ranges of the wind speed of the bridge and its upwind and downwind directions were lower than those of the subgrade. However, the required distance to recover the wind speed downwind of the bridge was greater than that of the subgrade, resulting in the sand transport rate of the bridge being lower than that of the subgrade. The variation in the wind field of the subgrade was more drastic than that of the bridge, but the required distance to recover the wind field downwind of the bridge was greater than that of the subgrade. In the wind speed-weakening area upwind, the wind speed-weakening range and intensity of the bridge were smaller than those of the subgrade. In the wind speed-increasing area on the top of the model, the wind speed-increasing range and intensity of the bridge were smaller than those of the subgrade. In the wind-speed-weakening area downwind, the wind speed weakening range of the bridge was greater than that of the subgrade, and the wind speed-weakening intensity was smaller than that of the subgrade. This investigation has theoretical and practical significance for the selection of expressway route forms in sandy areas. [ABSTRACT FROM AUTHOR]

Recently, vibration-based monitoring technologies have become extremely popular, providing effective tools to assess the health condition and evaluate the structural integrity of civil structures and infrastructures in real-time. In this context, battery-operated wireless sensors allow us to stop using wired sensor networks, providing easy installation processes and low maintenance costs. Nevertheless, wireless transmission of high-rate data such as structural vibration consumes considerable power. Consequently, these wireless networks demand frequent battery replacement, which is problematic for large structures with poor accessibility, such as long-span bridges. This work proposes a low-power multi-hop wireless sensor network suitable for monitoring large-sized civil infrastructures to handle this problem. The proposed network employs low-power wireless devices that act in the sub-GHz band, permitting long-distance data transmission and communication surpassing 1 km. Data collection over vast areas is accomplished via multi-hop communication, in which the sensor data are acquired and re-transmitted by neighboring sensors. The communication and transmission times are synchronized, and time-division communication is executed, which depends on the wireless devices to sleep when the connection is not necessary to consume less power. An experimental field test is performed to evaluate the reliability and accuracy of the designed wireless sensor network to collect and capture the acceleration response of the long-span Manhattan Bridge. Thanks to the high-quality monitoring data collected with the developed low-power wireless sensor network, the natural frequencies and mode shapes were robustly recognized. The monitoring tests also showed the benefits of the presented wireless sensor system concerning the installation and measuring operations. [ABSTRACT FROM AUTHOR]

A cable-stayed bridge is widely adopted to construct long-span bridges. The deformation of cable-stayed bridges is relatively larger than that of conventional bridges, such as beam and truss types. Therefore, studies regarding the monitoring systems for cable-stayed bridges have been conducted to evaluate the performance of bridges based on measurement data. However, most studies required sufficient measurement data for evaluation and just focused on the local response estimation. To overcome these limitations, Structural Responses Analysis using a Limited amount of Multi-Response data (SRALMR) was recently proposed and validated with the beam and truss model that has a simple structural behavior. In this research, the structural responses of a cable-stayed bridge were analyzed using SRALMR. The deformed shape and member internal forces were estimated using a limited amount of displacement, slope, and strain data. Target structural responses were determined by applying four load cases to the numerical model. In addition, pre-analysis for initial shape analysis was conducted to determine the initial equilibrium state, minimizing the deformation under dead loads. Finally, the performance of SRALMR for cable-stayed bridges was analyzed according to the combination and number of response data. [ABSTRACT FROM AUTHOR]

Deflection is one of the key parameters that reflects the state of a bridge. However, deflection measurement is difficult for a bridge that is under operation. Most existing sensors and measuring techniques often do not meet the requirements for health monitoring for various types of bridges. Therefore, based on changes of optical fiber intensity, a novel sensing system using connected pipes to measure bridge deflection in different positions is proposed in this paper. As an absolute reference, the liquid level position along the structure is adopted for the deflection measurement, and an additional external reference to the ground is not needed in this system. The proposed system consists of three parts: connected pipes to connect the measurement points along the structure, liquid to fill in the connected pipes, and the sensing element to detect the change of level. A plastic optical fiber sensor based on the intensity change is used as the sensing element of the developed system. Then, a set of experimental tests are conducted for performance evaluation purposes. Results show that this system has an accurate linear response and high reliability under various environmental conditions. The deflection of the test beam measured by the sensor agrees with linear variable differential transformer (LVDT) within an error margin of 2.1%. The proposed system shows great potential applicability for future health monitoring of long-span bridges. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Aimed at the health monitoring and evaluation of bridges based on sensing technology, the monitoring contents of different structural types of long-span bridges were defined. Then, the definition, classification, selection principle, and installation requirements of the sensors were summarized. The concept was proposed that new adaptable long-life sensors could be developed by new theories and new effects. The principle and methods to select controlled sections and optimize the layout design of measuring points were illustrated. The functional requirements were elaborated on about the acquisition, transmission, processing, and management of sensing information. Some advanced concepts about the method of bridge safety evaluation were demonstrated and technology bottlenecks in the current safety evaluation were also put forward. Ultimately, combined with engineering practices, an application was carried out. The results showed that new, intelligent, and reliable sensor technology would be one of the main future development directions in the long-span bridge health monitoring and evaluation field. Also, it was imperative to optimize the design of the health monitoring system and realize its standardization. Moreover, it is a heavy responsibility to explore new thoughts and new concepts regarding practical bridge safety and evaluation technology. [ABSTRACT FROM AUTHOR]

In-service prestressed concrete box girder bridges have received increasing attention in recent years due to a large number of bridges reaching decades in service. Therefore, the ageing of infrastructure demands the development of robust condition assessment methodologies based on affordable technology such as vehicle-induced vibration tests (VITs) in contrast with more expensive existing technologies such as tests using hammers or shakers. Ambient vibration tests (AVTs) have been widely used worldwide, taking advantage of freely available ambient excitation sources. However, the literature has commonly reported insufficient input energy to excite the structure to obtain satisfactory modal identification results, especially in long-span concrete bridges. On the other hand, the use of forced vibration tests (FVTs) requires more economic resources. This paper presents the results of field measurements at optimally selected locations in VITs consisting of a 32-ton truck and a springboard with a height of 50 mm. AVTs using optimal sensor placement (OSP) provide similar results to VITs without considering OSP locations. Additionally, the VIT/AVT cost ratio is reduced to 2 since a shorter data collection time is achieved within a one-day (8 h) test framework, which minimizes temperature effects, thus leading to improvements in AVT identification results, especially in vertical modes. [ABSTRACT FROM AUTHOR]

Data-driven methodologies can also be used with other types of sensor data rather than images. Wireless smart sensors can significantly reduce the installation and maintenance costs of the monitoring system, in addition to allowing multi-sensor data to be collected from a dense network of sensors [[7], [9]]. Sensors and sensor networks are the most important components of a smart city, acquiring various types of data containing useful information. Recent developments in sensor technologies and data-driven approaches have been recognized as the main enablers of smart cities. [Extracted from the article]

In this work, we present a series of hammering tests on full-scale unit-plate ballastless tracks used for long-span bridges. There is no denying that it is a new attempt to pave ballastless tracks on high-speed railway long-span bridges; the related issues deserve to be studied, and especially the vibration characteristics. Hence, the vibration characteristics and transmission rules of the ballastless track with geotextile or rubber isolation layers are explored, and the vibration reduction effect of the rubber isolation layer is analyzed. The main conclusions are as follows: the isolation layers change vibration modes and transmission characteristics of ballastless tracks; the introduction of the rubber isolation layer makes the excited vibration frequency range of the ballastless track concentrated; and the vibrations of the ballastless track with the rubber isolation layers are stable. Moreover, the rubber isolation layer has an obvious attenuation effect on vibration transmission in ballastless track structures. When the vibration is transmitted from the rail to the bridge deck, the vibration level differences of the ballastless track with rubber isolation layers are 20 dB larger than that of the ballastless track with the geotextile isolation layers. The vibration attenuation rate of the rubber isolation layer is about ten times larger than that of geotextile isolation layer. [ABSTRACT FROM AUTHOR]

In this paper, we present a new attempt to lay ballastless tracks on long-span cable-stayed bridges on high-speed railways. The arrangements of ballastless tracks laid on cable-stayed bridges can be divided into two conditions: (i) across the cable suspension-point cross-section or (ii) in discontinuity at the cable suspension-point cross-section. At present, there is a lack of in-depth research on ballastless tracks laid on long-span cable-stayed bridges, especially on the mechanical behaviors and fatigue performances of the ballastless tracks with different arrangements. For this paper, a segmental model of a long-span cable-stayed bridge was designed and built, on which full-scale ballastless tracks with two different arrangements were arranged. A series of fatigue tests and post-fatigue loading tests were carried out based on the two selected full-scale ballastless tracks. Some conclusions were drawn as follows. For the longitudinal end of the ballastless track, which is far from the loading positions, the interlayers of the ballastless tracks tend to warp up relatively, and the compressive pressures at the interlayers are also unloaded. However, there is no void or gap formed at the interlayers of the longitudinal end of the track slab due to the precompression of the rubber isolation layer. For the center of the track slab, which is close to the loading positions, the compressive deformations occur at the interlayers, and the pressures at interlayers are also increased. The maximum compressive deformation is less than 0.5 mm under the standard train axle load (170 kN), and it cannot affect the high-speed trains' operation. With the increase of the post-fatigue loading, the load-displacement curves and the load-pressure variation curves of the ballastless tracks show apparent nonlinearity. Moreover, with the increase of the fatigue loading cycles, the compressive stiffness enhancement or degradation of the ballastless tracks are not noticeable. That is to say, the ballastless tracks laid on the long-span cable-stayed bridges with different arrangements have good mechanical behaviors, and their fatigue performances can also be guaranteed after bearing repeated loadings. [ABSTRACT FROM AUTHOR]

Image measurement methods have been widely used in broad areas due to their accuracy and efficiency. However, current techniques usually involve complex calibration, an elaborate optical design, or sensitivity to the test environment. In this paper, a simple optical device was designed to emit parallel beams to obtain a virtual scale for measurement purposes. The proposed theory ensures the robustness of the system when obtaining each scale in the presence of uncertainty. The scale creates a mapping from image coordinates to world coordinates. By using the moving least squares (MLS) method, a full-field scale map can be reconstructed to achieve high-precision measurement at the sub-pixel level. Experimental verifications are carried out, showing that the proposed method provides very accurate and reliable results. The proposed approach is simple in terms of equipment, and the scale can be automatically calculated. Therefore, the system proposed in this paper is a promising candidate as a tool for non-contacting measurements (e.g., the crack development, geometric size) in the inaccessible structures such as high-rise buildings and long-span bridges. [ABSTRACT FROM AUTHOR]