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• A new vision-based multi-point displacement monitoring system is proposed. • A fast multi-feature matching and location method of light spot is proposed. • The camera-motion-induced error can be well compensated. • The bridge deformation evolution in the time and space dimensions are discussed. The existing vision measurement methods face a significant challenge in the multi-point displacement monitoring of large-span bridges due to the contradiction between the measurement scale and image spatial resolution. Based on a cable-stayed bridge on a kilometer scale, a new vision-based multi-point displacement monitoring system is proposed. The bridge was designed and arranged with a camera network, consisting of a series of double-head camera stations that were connected by cooperative markers. Based on the observed multi-point deflection and lateral displacement, the deformation evolution of the bridge in the two dimensions of time and space is discussed. The results show that the proposed vision-based camera network can accurately monitor the dynamic deflection and lateral displacement across the whole span of the bridge. The measurement errors induced by the camera motion can be well compensated based on the optical constraints of the proposed camera network. The feasibility of the vision method for long-span bridge monitoring has greatly improved. The proposed system can provide a new method for displacement monitoring and fine parameters for the safety evaluation of large-span bridges. [ABSTRACT FROM AUTHOR]

For long-term vision-based cable force monitoring, it is essential to fully consider different types of challenges, such as complex backgrounds in the field of view, illumination changes, occlusion, camera motion, and real-time realization. To address these challenges, this study proposes a vision-based, robust real-time cable force measurement method. In terms of innovation, three unique aspects were incorporated. First, to solve the difficulty of cable edge recognition caused by complex backgrounds, a linear feature detection operator called edge drawing lines was optimized by setting screening strategy based on the slope and line segments length. Second, the average of bilateral edge displacements was used as the final value to offset the displacement deviation caused by the illumination change. Third, to overcome obstacles to identifying the cable frequency caused by the camera motion, an interference frequency elimination method without reference targets or additional sensors was proposed. Furthermore, the integrated cable force calculation method was developed into a real-time measurement software. Finally, the proposed method was applied to a long-span cable-stayed bridge, where the camera was vibrated by the bridge deck or the wind significantly. The reliability of the proposed method was proved by comparing the results obtained with those achieved by accelerometers. [ABSTRACT FROM AUTHOR]

Over the past few years, longitudinal displacement has gained popularity as a means of evaluating the condition of long-span cable-supported bridge components, such as bearings. However, accurately predicting bearing displacement under varying load conditions is challenging due to the exposure of bridges to environmental and traffic loads. To address this issue, a hierarchical convolutional neural network (HCNN) model was developed in this paper for predicting bearing displacement using comprehensive loads as predictors. Structural health monitoring (SHM) systems of a cable-stayed bridge are utilized to provide one-month datasets for training and testing of the proposed method. Temperature, wind, and vehicle loads are adopted as input variables, and bearing displacement is the output. Results demonstrated the effectiveness of the proposed approach in predicting bearing displacement with an accuracy of over 95.6%, surpassing other models like traditional CNN, encoder-decoder, and U-Net in both accuracy and efficiency. Additionally, the contributions of different loads in predicting displacement are investigated, demonstrating the importance of traffic loads. Cumulative displacement can consequently be calculated for condition assessment of components such as bearings and expansion joints. A comparison with another cable-stayed bridge showed that the expansion joints in the current bridge were in satisfactory condition. Overall, the proposed approach can facilitate predictive maintenance in long-span bridges, helping to prevent premature failures. [ABSTRACT FROM AUTHOR]

For long-span cable-stayed bridges, interconnecting adjacent cables using cross-ties and connecting each cable to bridge deck become a promising solution for cable vibration mitigation, leading to hybrid cable networks. However, optimizing the system parameters and configuration for best vibration control effects is still challenging. Therefore, this study proposes an optimization method based on three important ingredients, i.e., a general and efficient numerical model of cable networks, a reasonable definition of the optimization objectives, and a multi-objective optimization method. The cable network is modeled using the component mode synthesis method with modal expansion and quasi-static correction, the optimization objectives consider both multi-mode damping effects and stiffness enhancement, and the multi-objective genetic algorithm is then employed. The proposed method is first verified by comparing with analytical methods when applying to relatively simple cable–damper systems. Subsequently, a five-cable network is studied using the method for optimal design of cross-tie and damper parameters. Furthermore, the method is applied to optimize cross-ties and dampers for the eight longest cables in the Sutong Bridge, considering different numbers, locations and anchoring conditions of the cross-ties. The results have demonstrated the effectiveness of the proposed method in dealing with real-world large-scale cable networks. It is shown that the optimization can ensure that vibrations in local modes of the cable network are dominated by cable segments with a damper installed in the span and hence are sufficiently damped. Besides, damping ratios of hybrid cable networks are shown to be sensitive to the cross-tie location and parameters while they are relatively insensitive to the damper coefficients. • A MOGA-based framework proposed for optimal design of cables with cross-ties and dampers. • Objective functions presented for optimization of configuration and cross-tie/damper parameters. • Application to an eight-cable network in a real large-span cable-stayed bridge. • Low-damping local modes of hybrid cable networks avoided through the optimization. [ABSTRACT FROM AUTHOR]