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Recently, the construction of long-span bridges has increased due to continuous developments in materials and construction technologies. For long-span bridges that use cables, it is important to continuously monitor bridge safety by measuring cable tensions under construction and in traffic use. Among the many methods of measuring cable tensions, t...
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... This method allows for the use of sensors on operational bridges, though their installation may be challenged by site conditions. Consequently, research has been dedicated to developing methods that enable efficient and convenient measurement of cable response [17][18][19][20][21][22]. In addition, techniques for directly measuring tension using ultrasonic waves or elasto-magnetic sensors have been explored, particularly for operational bridges where sensors for tension measurement could not be installed during construction [23][24][25][26][27]. ...
Continuous structural health monitoring of long-span bridges, such as suspension bridges, is essential for ensuring stability, and various efforts have been undertaken towards this goal. The hanger cables of suspension bridges play a crucial role in transmitting the main loads within the cable support structure. Therefore, monitoring the tension of hanger cables is vital for maintaining structural stability. Traditionally, the vibration method has been utilized for operational suspension bridges to indirectly estimate the tension of suspension bridge hanger cables. This method involves measuring the natural frequencies for vibration modes from the cables and their geometric conditions. In this study, digital camcorders and tripods were employed to measure the hanger cable response conveniently and efficiently. The response measured by digital camcorders is displacement based, posing challenges in measuring the natural frequencies for high-order modes required by the vibration method. Typically, systems for measuring structural response incorporate white noise components across all frequency domains, complicating the identification of cable frequency component characteristics when the response frequency measured by a digital camcorder is lower than the white noise frequency. Furthermore, measurements taken with a digital camcorder may suffer from low resolution due to long distances and optical limitations, hindering the measurement of high-frequency response components. To address these challenges, this study introduced a back analysis method to estimate tension using the natural frequencies of low-order modes. The method defines the difference between measured natural frequencies and those predicted by finite-element analysis as the error function. Optimization was then conducted using the univariate search method to minimize this error function. The findings suggest that the tension estimated by applying only the first natural frequency of hanger cables through the back analysis method closely aligns with estimates obtained using the vibration method. This research highlights the potential of using standard digital camcorders as an accurate and cost-effective means for estimating hanger cable tension.
... In addition, there is a limitation that an additional mass should be considered because of the bracket needed to install the sensor. To overcome these limitations, non-contact sensor (i.e., microwaves [10][11][12], lasers [13,14], vision [15][16][17][18][19][20], etc.)-based tension estimation methods have been proposed. Non-contact sensors do not need to consider damage to the surface paint of a structure and can measure multiple targets simultaneously compared with contact systems, which can only provide limited information. ...
Since all structures vibrate due to external loads, measuring and analyzing vibration data is a representative method of structural health monitoring. In this paper, we propose a non-contact cable estimation method using a vision sensor mounted on an unmanned aerial vehicle. A target cable among many cables can be identified through marker detection. In addition, the motion of the structure can be quickly captured using the extracted feature points. Although computer vision can be used to transform displacements of multiple axis, in this study, only the vertical displacement is considered to estimate tension. Finally, the cable tension can be estimated via the vibration method using the modal frequencies derived from the cable displacement. To verify the performance of the proposed method, lab-scale experiments were carried out and the results were compared with the conventional method based on the accelerometer. The proposed method showed a 3.54% error compared with the existing method and confirmed that the cable tension force can be estimated quickly at low cost.
... A source of acoustic motion could cause change in sound wavelength which can be used to measure surface motion. The LDV method does not require a high-energy interferometer, and is also well-established in modal analysis [201][202][203]. ...
The building and construction industry is a traditional industry that features high-capacity investment, long return period, high environment impact, and low technology demand in the past decades. With the fast development of technology and the demand for environmental sustainability, it is inevitable for the building and construction industry to embrace the revolution of technology. Intelligent construction is developed in light of advanced technologies including advanced computing technology, 3D design and manufacturing, automation and control, sensing, unmanned aircraft, and autonomous intelligence. It is also closely integrated with using perceived, analytical, decision-making coordination for building construction with perceived intelligent execution technology in the processes. Currently, there is no consensus definition on “intelligent construction” despite its rapid development. This paper reviews existing and current development in intelligent construction focusing on the following three aspects: (a) new structural forms, which are innovative and with potential or are being applied to automated and mass manufacturing/construction; (b) automated and intelligent construction system; and (c) advanced structure sensing and monitoring technology. These three components do not compromise the entire aspects for intelligent construction, but they have no doubt are the core elements for intelligent construction towards future building systems.
... The basic principle of DIC is to compare the same points (or pixels) recorded between two images before and after deformation, and to calculate the motion of each point [83]. As a representative non-interference optical technique, DIC has the advantage of continuous measurement of the whole displacement field and strain field. ...
Computer vision-based structural deformation monitoring techniques were studied in a large number of applications in the field of structural health monitoring (SHM). Numerous laboratory tests and short-term field applications contributed to the formation of the basic framework of computer vision deformation monitoring systems towards developing long-term stable monitoring in field environments. The major contribution of this paper was to analyze the influence mechanism of the measuring accuracy of computer vision deformation monitoring systems from two perspectives, the physical impact, and target tracking algorithm impact, and provide the existing solutions. Physical impact included the hardware impact and the environmental impact, while the target tracking algorithm impact included image preprocessing, measurement efficiency and accuracy. The applicability and limitations of computer vision monitoring algorithms were summarized.
... The direct method obtains cable tension by using measuring devices installed at the end of the cable or enclose the cable surface, such as load cells, hydraulic jacks, and Elasto-Magnetic (EM) sensors (Cappello et al. 2018, Sumitro et al. 2005. The indirect method mainly uses a vibration-based approach, which can relatively get a fast cable tension estimation compared to direct methods (Caetano 2011, Geier et al. 2006, Kim et al. 2017.cn a Ph.D. Student, E-mail: guowei@tongji.edu.cn b Professor, E-mail: wally@tongji.edu.cn ...
... For instance, the use of cameras to determine cable tension (Du et al. 2020, Kim et al. 2017, Xu et al. 2018, Yang et al. 2019, the use of microwave interferometric radar to estimate the cable tension in a long-span cable-stayed bridge (Bartoli et al. 2008, Zhang et al. 2020a, Zhao et al. 2020, and the application of Laser Doppler technology (Nassif et al. 2005) have been reported. The detection accuracy of current vision-based measurements is often affected by the intensity of light and weather. ...
The loss of cable tension for civil infrastructure reduces structural bearing capacity and causes harmful deformation of structures. Currently, most of the structural health monitoring (SHM) approaches for cables rely on contact transducers. This paper proposes a cable tension identification technology using percussion sound, which provides a fast determination of steel cable tension without physical contact between cables and sensors. Notably, inspired by the concept of tensioning strings for piano tuning, this proposed technology predicts cable tension value by deep learning assisted classification of "percussion" sound from tapping a steel cable. To simulate the non-linear mapping of human ears to sound and to better quantify the minor changes in the high-frequency bands of the sound spectrum generated by percussions, Mel-frequency cepstral coefficients (MFCCs) were extracted as acoustic features to train
... Bridges currently in operation are subjected to performance degradation due to the applied load, deterioration of components, and changes in the external environment [3,4]. It is essential for bridge maintenance to continuously examine such changes in the condition of the bridge and to evaluate bridge safety by continually monitoring them [5][6][7][8][9]. Therefore, there is an urgent need to develop technologies to secure bridge safety in relation to the growing number of old bridges worldwide [10][11][12]. ...
... The number of vehicle axles that pass through the bridge is the frequency at which the impact of the measured reaction force response is applied, and the wheel base can be expressed as Equation (9). Here, is the distance between the A axis and B axis of the vehicle, and ∆ is the time difference that the A and B axes pass one point on the bridge. ...
... Here, is the distance between the A axis and B axis of the vehicle, and ∆ is the time difference that the A and B axes pass one point on the bridge. The number of vehicle axles that pass through the bridge is the frequency at which the impact of the measured reaction force response is applied, and the wheel base can be expressed as Equation (9). Here, l AB is the distance between the A axis and B axis of the vehicle, and ∆t AB is the time difference that the A and B axes pass one point on the bridge. ...
Accurately calculating the vehicle load acting on a bridge at any one time is crucial to determining the integrity and safety of the bridge. To ensure this integrity and safety, information on the types, characteristics, and load of vehicles that regularly cross the bridge is very important in terms of its structural adequacy and maintenance. In this study, the vehicle load that a bridge will be subjected to was estimated using the reaction force response at the support. To estimate this response to the reaction force, a vertical displacement sensor, developed based on Fiber Bragg Grating (FBG), was applied to the Eradi Quake System (EQS), a commercially available bridge bearing. This vertical displacement sensor can measure the vertical load and has the advantage of being easy to attach and detach. To verify the performance and accuracy of this sensor, this study conducted numerical analysis and vehicle loading tests. It found that the vehicle load can be estimated from the reaction force response, as measured by the vertical displacement sensor on the bridge.
... Therefore, it is essential to develop effective methods to evaluate the healthy condition of stay cables under the operational conditions. The cable tension force can be directly measured by the load cell, fiber Bragg grating (FBG) strain sensor or indirectly measured by vibration-based and recently developed visionbased techniques (Kangas et al. 2012, Feng et al. 2017, Kim et al. 2017. Therefore, it is of potential to identify the * Corresponding author, Ph.D., E-mail: junli@curtin.edu.au ...
This article develops a long-term condition assessment method for stay cables in cable stayed bridges using the monitored cable tension forces under operational condition. Based on the concept of influence surface, the matched cable tension ratio of two cables located at the same side (either in the upstream side or downstream side) is theoretically proven to be related to the condition of stay cables and independent of the positions of vehicles on the bridge. A sensor grouping scheme is designed to ensure that reliable damage detection result can be obtained even when sensor fault occurs in the neighbor of the damaged cable. Cable forces measured from an in-service cable-stayed bridge in China are used to demonstrate the accuracy and effectiveness of the proposed method. Damage detection results show that the proposed approach is sensitive to the rupture of wire damage in a specific cable and is robust to environmental effects, measurement noise, sensor fault and different traffic patterns. Using the damage sensitive feature in the proposed approach, the metrics such as accuracy, precision, recall and F1 score, which are used to evaluate the performance of damage detection, are 97.97%, 95.08%, 100% and 97.48%, respectively. These results indicate that the proposed approach can reliably detect the damage in stay cables. In addition, the proposed approach is efficient and promising with applications to the field monitoring of cables in cable-stayed bridges.
... Only limited works are solely dedicated and reported for vision-based SHM in a dark or night environment using real images. Li et al. [18] conducted a dynamic test using a smartphone and Kim et al. [19] installed a vision-based monitoring system equipped with a digital camera with a zoom lens on a three-span cable-stayed bridge. However, these two studies were conducted in low light and completely dark settings without additional lighting, so the SHM was unable to identify the monitored object [19] and a significant quantity of time-signals were missing in the data [18]. ...
... Li et al. [18] conducted a dynamic test using a smartphone and Kim et al. [19] installed a vision-based monitoring system equipped with a digital camera with a zoom lens on a three-span cable-stayed bridge. However, these two studies were conducted in low light and completely dark settings without additional lighting, so the SHM was unable to identify the monitored object [19] and a significant quantity of time-signals were missing in the data [18]. To solve these problems, a small number of studies that added additional components to the vision-based system have been reported. ...
This paper describes an alternative structural health monitoring (SHM) framework for low-light settings or dark environments using underexposed images from vision-based sensors based on the practical implementation of image enhancement algorithms. The proposed framework was validated by two experimental works monitored by two vision systems under ambient lights without assistance from additional lightings. The first experiment monitored six artificial templates attached to a sliding bar that was displaced by a standard one-inch steel block. The effect of image enhancement in the feature identification and bundle adjustment integrated into the close-range photogrammetry were evaluated. The second validation was from a seismic shake table test of a full-scale three-story building tested at E-Defense in Japan. Overall, this study demonstrated the efficiency and robustness of the proposed image enhancement framework in (i) modifying the original image characteristics so the feature identification algorithm is capable of accurately detecting, locating and registering the existing features on the object; (ii) integrating the identified features into the automatic bundle adjustment in the close-range photogrammetry process; and (iii) assessing the measurement of identified features in static and dynamic SHM, and in structural system identification, with high accuracy.
... Thus, it is necessary to extend their lifetime and secure safety and usability through proper maintenance [1][2][3][4]. Consequently, evaluating the integrity of bridges is an important maintenance task for securing safety [5][6][7][8][9][10][11]. ...
Maintenance of bridges in use is essential and measuring the live load distribution factor (LLDF) of a bridge to examine bridge integrity and safety is important. A vehicle loading test has been used to measure the LLDF of a bridge. To carry this out on a bridge in use, traffic control is required because loading must be performed at designated positions using vehicles whose details are known. This makes it difficult to measure LLDF. This study proposed a method of estimating the LLDF of a bridge using the vertical displacement response caused by traveling vehicles under ambient vibration conditions in the absence of vehicle control. Since the displacement response measured from a bridge included both static and dynamic components, the static component required for the estimation of LLDF was extracted using empirical mode decomposition (EMD). The vehicle loading and ambient vibration tests were conducted to verify the validity of the proposed method. It was confirmed that the proposed method can effectively estimate the LLDF of a bridge if the vehicle type and driving lane on the bridge are identified in the ambient vibration test.
... Furthermore, the condition of cable-stayed structures can be assessed through their cable tension during operation [2,3]. There are many methods to measure cable tension force, such as using load cells, hydraulic jacks [4], FBG sensors [5] or electromagnetic sensors. However, those conventional sensors become unfeasible and impracticable when applied in long-term monitoring. ...
Accurate estimation of cable tension is crucial for the structural health monitoring of cable-supported structures. Identifying the cable’s force from its vibration data is probably the most widely adopted method of cable tension estimation. According to string theory, the accuracy of estimated cable tension is highly related to identified modal parameters including natural frequencies and frequency order. To alleviate the factors that impact the accuracy of modal parameters when using the peak-picking method in wireless sensor networks, a fully automated and robust identifying method is proposed in this paper. This novel method was implemented on the Xnode wireless sensor system and validated with the data obtained from Jindo Bridge. The experiment results indicate that, through this method, the wireless sensor is able to distinguish the cognizable power spectrum, extract the peaks, eliminate false frequencies and determine frequency orders automatically to estimate cable tension force without any manual intervention or preprocessing. Meanwhile, the results of natural frequencies, corresponding orders and cable tension force obtained from the Xnode system show excellent agreement with the results obtained using the Matlab program method. This demonstrates the effectiveness and reliability of the Xnode estimation system. Furthermore, this method is also appropriate for other high-performance wireless sensor network systems to realize self-identification of cable in long-term monitoring.
