• Structural Engineering and Mechanics
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• v.50 no.1
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• pp.37-52
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• 2014

The accurate determination of cable tension is important to the monitoring of the condition of a cable-stayed bridge. When applying a vibration-based formula to identify the tension of a real cable under sag, stiffness and boundary conditions, the resulting error must not be overlooked. In this work, by resolving the implicit frequency function of a real cable under the above conditions numerically, indirect methods of determining the cable force and a method to calculate the corresponding cable mode frequency are investigated. The error in the tension is studied by numerical simulation, and an empirical error correction formula is presented by fitting the relationship between the cable force error and cable parameters ${\lambda}^2$ and ${\xi}$. A case study on two real cables of the Shanghai Changjiang Bridge shows that employing the method proposed in this paper can increase the accuracy of the determined cable force and reduce the computing time relative to the time required for the finite element model.

• Smart Structures and Systems
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• v.3 no.3
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• pp.281-298
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• 2007

The load carrying capacity of a bridge needs to be properly assessed to operate the bridge safely and maintain it efficiently. For the evaluation of load carrying capacity considering the current state of a bridge, static and quasi-static loading tests with weight-controlled heavy trucks have been conventionally utilized. In these tests, the deflection (or strain) of the structural members loaded by the controlled vehicles are measured and analyzed. Using the measured data, deflection (or strain) correction factor and impact correction factor are calculated. These correction factors are used in the enhancement of the load carrying capacity of a bridge, reflecting the real state of a bridge. However, full or partial control of the traffic during the tests and difficulties during the installment of displacement transducers or strain gauges may cause not only inconvenience to the traffic but also the increase of the logistics cost and time. To overcome these difficulties, an alternative method is proposed using an excited response part of full measured ambient acceleration data by ordinary traffic on a bridge without traffic control. Based on the modal properties extracted from the ambient vibration data, the initial finite element (FE) model of a bridge can be updated to represent the current real state of a bridge. Using the updated FE model, the deflection of a bridge akin to the real value can be easily obtained without measuring the real deflection. Impact factors are obtained from pseudo-deflection, which is obtained by double-integration of the acceleration data with removal of the linear components on the acceleration data. For validation, a series of tests were carried out on a steel plategirder bridge of an expressway in Korea in four different seasons, and the evaluated load carrying capacities of the bridge by the proposed method are compared with the result obtained by the conventional load test method.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.3
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• pp.239-245
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• 2002

Many civil and infrastructures continue to be used despite aging and the associated potential for damage accumulation. Therefore, the ability to monitor the health of these systems is becoming increasingly important. The purpose of this paper is to propose a real-time health monitoring system of cable-stayed bridge, based-on non-destructive measurement. And also this paper focuses on the safety assessment for bridge from health monitoring system to accomplish this safety assesment. Using the proposed health monitoring system, it helps bridge maintenance and reduces the economic cost of a life-cycle costs. Also it give important data to develop the design and analysis method for cable-stayed bridges.

• Smart Structures and Systems
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• v.23 no.4
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• pp.359-371
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• 2019

As part of a structural health monitoring system, the relative geometric relationship between a ship and bridge has been recognized as important for bridge authorities and ship owners to avoid ship-bridge collision. This study proposes a novel computer vision method for the real-time geometric parameter identification of moving ships based on a single shot multibox detector (SSD) by using transfer learning techniques and monocular vision. The identification framework consists of ship detection (coarse scale) and geometric parameter calculation (fine scale) modules. For the ship detection, the SSD, which is a deep learning algorithm, was employed and fine-tuned by ship image samples downloaded from the Internet to obtain the rectangle regions of interest in the coarse scale. Subsequently, for the geometric parameter calculation, an accurate ship contour is created using morphological operations within the saturation channel in hue, saturation, and value color space. Furthermore, a local coordinate system was constructed using projective geometry transformation to calculate the geometric parameters of ships, such as width, length, height, localization, and velocity. The application of the proposed method to in situ video images, obtained from cameras set on the girder of the Wuhan Yangtze River Bridge above the shipping channel, confirmed the efficiency, accuracy, and effectiveness of the proposed method.

• Smart Structures and Systems
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• v.31 no.5
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• pp.501-516
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• 2023

Dynamic irregularity and acceleration of bridges subjected to high-speed trains provide crucial information for comprehensive evaluation of the health state of under-track structures. This paper proposes a novel approach for real-time estimation of vertical track dynamic irregularity and bridge acceleration using deep generative adversarial network (GAN) and vibration data from in-service train. The vehicle-body and bogie acceleration responses are correlated with the two target variables by modeling train-bridge interaction (TBI) through least squares generative adversarial network (LSGAN). To realize supervised learning required in the present task, the conventional LSGAN is modified by implementing new loss function and linear activation function. The proposed approach can offer pointwise and accurate estimates of track dynamic irregularity and bridge acceleration, allowing frequent inspection of high-speed railway (HSR) bridges in an economical way. Thanks to its applicability in scenarios of high noise level and critical resonance condition, the proposed approach has a promising prospect in engineering applications.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05a
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• pp.34-37
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• 2006

Accoarding as a specimen for reinforced concrete bridge deck was designed by each researcher's opinions, its size and shape was variable. Therefore, it makes difficult to comparison with other experiments. In the result of researching papers for design method of reinforced concrete bridge deck specimens, there is hardly found. The target of this study is introduction of the design method of a reinforced concrete bridge deck specimen. The most important point for the specimen design is materialization of the curvature of the real bridge deck. The result of this study appears that the specimens thickness effects highly to fit for the real reinforced concrete bridge deck's curvature.

• Journal of Navigation and Port Research
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• v.28 no.8
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• pp.735-743
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• 2004

A bridge which connects Mokpo North Harbor and Goha Island is going to be constructed until 2009. For the bridges being built in the navigable water area, it is indispensible to carry out vessel traffic safety assessment from the viewpoint of shiphandlers, however, there exist no specific guidelines for the necessary conditions which the bridge designers can rely on. In this paper, traffic safety assessment procedures for the layout of the bridge are briefly introduced, and the conditions which should be taken into account at the initial design stage of the bridge are surveyed For the safety assessment of the bridge design, ship navigation simulations, such as RTS( real time simulation) and FTS(fast time simulation), are carried out, the results of which are statistically analysed to estimate the probability of collision between the ship and the pier of the bridge.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7893-7901
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• 2015

It is important to the periodic collection and analysis of the maintenance and management information of bridges for a more safe and efficient management of the bridges. To enhance the reliability and ease of acquisition of the bridge inspection information that is the basis for a strategy for safe and economic management using the bridge management system (BMS), this study develops a smart phone application for bridge inspection and ensures the actual applicability of the application. The developed application that is linked with the BMS for life-cycle management of bridges is possible to real-time query, modify and transmit of the maintenance-related information, and the application is able to greatly relieve the time and cost for the bridge inspection through the automatic creation of site inspection reports. The proposed method using the application is directly or indirectly expected to be very high effects of value improvement, such as ease of use, improved accuracy, sustainability of information, and future utilization, compared to conventional inspection method.

• Structural Engineering and Mechanics
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• v.68 no.5
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• pp.563-573
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• 2018

Temperature-induced responses, such as strains and displacements, are related to the boundary conditions. Therefore, it is required to determine the boundary conditions to establish a reliable bridge model for temperature-induced responses analysis. Particularly, bridge bearings usually present nonlinear behavior with an increase in load, and the nonlinear boundary conditions cause significant effect on temperature-induced responses. In this paper, the bridge nonlinear boundary conditions were simulated as bilinear translational or rotational springs, and the boundary parameters of the bilinear springs were identified based on the measured temperature-induced responses. First of all, the temperature-induced responses of a simply support beam with nonlinear translational and rotational springs subjected to various temperature loads were analyzed. The simulated temperature-induced strains and displacements were assumed as measured data. To identify the nonlinear translational and rotational boundary parameters of the bridge, the objective function based on the temperature-induced responses is then created, and the nonlinear boundary parameters were further identified by using the nonlinear least squares optimization algorithm. Then, a beam structure with nonlinear translational and rotational springs was simulated as a numerical example, and the nonlinear boundary parameters were identified based on the proposed method. The numerical results show that the proposed method can effectively identify the parameters of the nonlinear boundary conditions. Finally, the boundary parameters of a real arch bridge were identified based on the measured strain data and the proposed method. Since the bearings of the real bridge do not perform nonlinear behavior, only the linear boundary parameters of the bridge model were identified. Based on the bridge model and the identified boundary conditions, the temperature-induced strains were recalculated to compare with the measured strain data. The recalculated temperature-induced strains are in a good agreement with the real measured data.

• Journal of the Korea institute for structural maintenance and inspection
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• v.2 no.4
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• pp.137-147
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• 1998

The neural net application was tried to develop the technique for monitoring the health status of a steel truss bridge which was scaled down to 1/15 of the real bridge for the laboratory experiments. The damage scenarios were chosen as 7 cases. The dynamic behavior, which was changed due to the breakage of the members, of the bridge was investigated by finite element analysis. The bridge consists of single spam, and eight (8) main structural subsystems. The loading vehicle, which weighs as 100 kgf, was operated by the servo-motor controller. The accelerometers were bonded on the surface of 7 cross-beams to measure the dynamic behavior induced by the abnormal structural condition. Artificial neural network technique was used to determine the severity of the damage. At first, the neural net was learnt by the results of finite element analysis, and also, the maximum detection error was 3.65 percents. Another neural net was also learnt, and verified by the experimental results, and in this case, the maximum detection error was 1.05 percents. In future study, neural net is necessary to be learnt and verified by various data from the real bridge.