• Journal of Korean Society of societal Security
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• v.3 no.1
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• pp.33-42
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• 2010

This study predicts the stress history for truss bridge with local damages by using global-local model combination method. For this end, the global structure is modeled by 3D frame elements and the selected local details are modeled by shell elements. Then superposition principle enable the global-local model to be combined interactively. Because the frame model cannot consider the rigidity of gusset plate and the interation of structural members due to the complexity of stress distribution in truss connection. The section modification factors are proposed to calibrate the stiffness of global frame element. The global-local model combination is verified by comparing the numerical results with experimental data obtained from the proof loading test to the operating truss bridge. Furthermore, stress histrories of the truss bridge are generated in the consideration of the rigidity of truss connection with local damage by using the combination method.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.4
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• pp.121-125
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• 2018

This paper presents the assessment of 7-wire strand monitoring using acoustic emission technique for bridges. 7-wire strand is widely used construction materials to provide additional tensile force to bridges. PSC (PreStressed Concrete) bridge and cable-stayed bridge are representatives for such cases. However, as the bridge aging progresses recently, corrosion problems of strand are emerging. For this reason, various NDT (Non-Destructive Test) methods for cable inspection are being studied and applied to the field. One of the NDT methods, acoustic emission technique, is known as an effective technique to detect cable damage and breakage. In this study, to evaluate the applicability of acoustic emission technique to bridges, acoustic emission signals according to damage of the strand were acquired and analyzed by tensile test. Moreover, The optimal AE sensor type was selected for field application. As a result, it is considered that the acoustic emission technique will be able to detect corrosion breakage and signs of rupture.

• Smart Structures and Systems
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• v.29 no.1
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• pp.17-28
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• 2022

The cable component of cable-stayed bridges is gradually impacted by weather conditions, vehicle loads, and material corrosion. The stayed cable is a critical load-carrying part that closely affects the operational stability of a cable-stayed bridge. Damaged cables might lead to the bridge collapse due to their tension capacity reduction. Thus, it is necessary to develop structural health monitoring (SHM) techniques that accurately identify damaged cables. In this work, a combinational identification method of three efficient techniques, including statistical analysis, clustering, and neural network models, is proposed to detect the damaged cable in a cable-stayed bridge. The measured dataset from the bridge was initially preprocessed to remove the outlier channels. Then, the theory and application of each technique for damage detection were introduced. In general, the statistical approach extracts the parameters representing the damage within time series, and the clustering approach identifies the outliers from the data signals as damaged members, while the deep learning approach uses the nonlinear data dependencies in SHM for the training model. The performance of these approaches in classifying the damaged cable was assessed, and the combinational identification method was obtained using the voting ensemble. Finally, the combination method was compared with an existing outlier detection algorithm, support vector machines (SVM). The results demonstrate that the proposed method is robust and provides higher accuracy for the damaged cable detection in the cable-stayed bridge.

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.129-136
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• 2023

A special offshore bridge with a high pylon has special structural features.Special offshore bridges have inspection blind spots that are difficult to visually inspect. To solve this problem, safety inspection methods using drones are being studied. In this study, image data of the pylon of a special offshore bridge was acquired using a drone. In addition, an artificial intelligence algorithm was developed to detect damage to the pylon surface. The AI algorithm utilized a deep learning network with different structures. The algorithm applied the stacking ensemble learning method to build a model that formed the ensemble and collect the results.

• Smart Structures and Systems
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• v.11 no.1
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• pp.19-34
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• 2013

The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using the Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approach. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis (rSSA) is presented to remove the noise contaminant measurements so as to enhance the stability of data analysis. Through the application of rSSA-SSI-COV to the vibration measurement of bridge during scouring experiment, the ability of the proposed algorithm was proved to be robust to the noise perturbations and offers a very good online tracking capability. The accuracy and robustness offered by rSSA-SSI-COV provides a key to obtain the evidence of imminent bridge settlement and a very stable modal frequency tracking which makes it possible for early warning. The peak values of the identified $1^{st}$ mode shape slope ratio has shown to be a good indicator for damage location, meanwhile, the drastic movements of the peak of $2^{nd}$ mode slope ratio could be used as another feature to indicate imminent pier settlement.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.3
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• pp.235-242
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• 2004

Bridge Management System (BMS) requires a more objective condition assessment over the lifespan of a given bridge. Thus, a quantitative assessment model of resistance capacity was developed here to meet the requirement for deteriorated concrete bridges. The model focuses on damage mechanisms of concrete bridges deteriorated by traffic loads and environment factors such as chloride and carbonation attacks. Also, it was applied to a typical concrete slab bridge which was severely damaged due to both load and environmental conditions. It was shown that the proposed quantitative model simulates well the deterioration level considering the two damage criteria.

• Earthquakes and Structures
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• v.8 no.3
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• pp.573-589
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• 2015

In order to investigate the seismic behavior of highway bridges under near-fault earthquakes, a parametric study was conducted for different regular and irregular bridges. To this end, an existing regular viaduct Highway Bridge was used as a reference model and five irregular samples were generated by varying span length and pier height. The seismic response of the six highway bridges was evaluated by three dimensional non-linear response history analysis using an ensemble of far-fault and scenario-based near-fault records. In this regard, drift ratio, input and dissipated energy as well as damage index of bridges were compared under far- and near-fault motions. The results indicate that the drift ratio under near-fault motions, on the average, is 100% and 30% more than far-fault motions at DBE and MCE levels, respectively. The energy and damage index results demonstrate a dissipation of lower energy in piers and a significant increase of collapse risk, especially for irregular highway bridges, under near-fault ground motions.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.09a
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• pp.263-270
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• 2003

Before the implementation of the 1992 seismic design provisions in Korea, longitudinal steels of RC bridge piers were practically lap-spliced in the plastic hinge region. Experimental investigation was made to evaluate the seismic performance of RC bridge pier specimens in a flexure/shear mode. Six circular test specimens in an aspect ratio of 2.5 (600mm in diameter) were made with test parameters confinement ratio, lap splices, and retrofit FRP materials. They were damaged under a series of artificial earthquakes with 0.22g PGA, being compatible in Korean peninsula, through the pseudo-dynamic test. Probable damages were assessed by the Park and Ang damage index. Approximate 0.1 and 0.3 damage indices were obtained for RC specimens without lap splice and with lap splice, respectively. Directly after the pseudo-dynamic test, damaged test columns were laterally actuated under inelastic reversal cyclic loadings simultaneously under a constant axial load. Through curvature measurements, residual seismic performance was evaluated for test specimens. Test results show that RC pier specimens with lap-spliced appeared to fail at low ductility, but significant improvement was obtained for the ductility of these specimens if externally wrapped with FRP.

• Smart Structures and Systems
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• v.23 no.3
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• pp.279-293
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• 2019

To ensure high quality data being used for data mining or feature extraction in the bridge structural health monitoring (SHM) system, a practical sensor fault diagnosis methodology has been developed based on the similarity of symmetric structure responses. First, the similarity of symmetric response is discussed using field monitoring data from different sensor types. All the sensors are initially paired and sensor faults are then detected pair by pair to achieve the multi-fault diagnosis of sensor systems. To resolve the coupling response issue between structural damage and sensor fault, the similarity for the target zone (where the studied sensor pair is located) is assessed to determine whether the localized structural damage or sensor fault results in the dissimilarity of the studied sensor pair. If the suspected sensor pair is detected with at least one sensor being faulty, field test could be implemented to support the regression analysis based on the monitoring and field test data for sensor fault isolation and reconstruction. Finally, a case study is adopted to demonstrate the effectiveness of the proposed methodology. As a result, Dasarathy's information fusion model is adopted for multi-sensor information fusion. Euclidean distance is selected as the index to assess the similarity. In conclusion, the proposed method is practical for actual engineering which ensures the reliability of further analysis based on monitoring data.

• Structural Monitoring and Maintenance
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• v.10 no.2
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• pp.107-116
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• 2023

The health condition of of deep water high pile foundation is vital to the safe operation of bridges. However, pier foundations are vulnerable to damage in deep water due to exposure to sea torrents and corrosive environments over an extended period. In this paper, combined with aninvestigation and analysis of the typical damage characteristics of main pier group pile foundations, we study the safety monitoring and real-time early warning technology of the deep water high pile foundations, we propose an early warning index item and early warning threshold of deep water high pile foundation by utilizing a numerical simulation analysis and referring to domestic and foreign standards and literature. First, we combine the characteristics of structures and draw on more mature evaluation theories and experience in civil engineering-related fields such as dam and bridge engineering. Then, we establish a scheme consisting of a Early Warning Index Systemand evaluation model based on the analytic hierarchy process and constant weight evaluation method and apply the research results to a project based on the Jiashao bridge in Zhejiang province, China. Finally, we verify the rationality and reliability of the Early Warning Index Systemof the Deep Water High Pile Foundations.