• Structural Monitoring and Maintenance
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• v.7 no.2
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• pp.149-166
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• 2020

This paper presents the results of an experimental investigation on a vibration-based damage identification framework for a steel girder type and a truss bridge based on acceleration responses to operational loading. The method relies on sensor clustering-based time-series analysis of the operational acceleration response of the bridge to the passage of a moving vehicle. The results are presented in terms of Damage Features from each sensor, which are obtained by comparing the actual acceleration response from the sensors to the predicted response from the time-series model. The damage in the bridge is detected by observing the change in damage features of the bridge as structural changes occur in the bridge. The relative severity of the damage can also be quantitatively assessed by observing the magnitude of the changes in the damage features. The experimental results show the potential usefulness of the proposed method for future applications on condition assessment of real-life bridge infrastructures.

• Proceedings of the Korea Concrete Institute Conference
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• 2010.05a
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• pp.109-110
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• 2010

A pedestrian UHPC cable-stayed bridge(Super Bridge I) of the KICT was completed as a test bed. A long-term monitoring system has been installed on the UHPC bridge in order to acquire all types of long-term data such as strain, acceleration, tension force, wind direction and speed, temperature, etc. This system will provide valuable database enabling to assess the long-term behavior of the UHPC pedestrian hybrid cable-stayed bridge. This database will be exploited for the evaluation of the mechanical characteristics and serviceability of the UHPC members so as to estimate the behavioral features of long-span hybrid cable stayed bridges.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.525-543
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• 2010

Testing and validation processes are critical tasks in developing a new hardware platform based on a new technology. This paper describes a series of experiments to evaluate the performance of a newly developed MEMS-based wireless sensor node as part of a wireless sensor network (WSN). The sensor node consists of a sensor board with four accelerometers, a thermometer and filtering and digitization units, and a MICAz mote for control, local computation and communication. The experiments include calibration and linearity tests for all sensor channels on the sensor boards, dynamic range tests to evaluate their performance when subjected to varying excitation, noise characteristic tests to quantify the noise floor of the sensor board, and temperature tests to study the behavior of the sensors under changing temperature profiles. The paper also describes a large-scale deployment of the WSN on a long-span suspension bridge, which lasted over three months and continuously collected ambient vibration and temperature data on the bridge. Statistical modal properties of a bridge tower are presented and compared with similar estimates from a previous deployment of sensors on the bridge and finite element models.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.04a
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• pp.813-818
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• 1999

The construction of large scale civil and building structures which form the base of social economy has been grown greatly. As the increasing of aged and deteriorated structures, it is necessary to evaluate the safety of those structures. The deterioration, safety evaluation, repair and rehabilitation are important problems in the construction area that every country faces. This paper presents the general information on how to conduct a data analysis of long-term monitoring system and evaluate the characteristics of surveying methods.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.10a
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• pp.105-110
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• 2004

This study suggests a trial system for facility monitoring technology on ubiquitous environment. The trial system can be used for integrated various collection and sending data by bluetooth and wireless network from bridge. We used smart sensor and wireless network for it. Especially, we analyzed out all appliable technologies at monitoring part on ubiquitous environment and gave a standard spec to build the system. We wanted it as a guideline to apply ubiquitous in smart facility monitoring part.

• Smart Structures and Systems
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• v.17 no.6
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• pp.995-1015
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• 2016

In the design and condition assessment of bridges, it is usually necessary to take into consideration the extreme conditions which are not expected to occur within a short time period and thus require an extrapolation from observations of limited duration. Long-term structural health monitoring (SHM) provides a rich database to evaluate the extreme conditions. This paper focuses on the extrapolation of extreme traffic load effects on bridges using long-term monitoring data of structural strain. The suspension Tsing Ma Bridge (TMB), which carries both highway and railway traffic and is instrumented with a long-term SHM system, is taken as a testbed for the present study. Two popular extreme value extrapolation methods: the block maxima approach and the peaks-over-threshold approach, are employed to extrapolate the extreme stresses induced by highway traffic and railway traffic, respectively. Characteristic values of the extreme stresses with a return period of 120 years (the design life of the bridge) obtained by the two methods are compared. It is found that the extrapolated extreme stresses are robust to the extrapolation technique. It may owe to the richness and good quality of the long-term strain data acquired. These characteristic extremes are also compared with the design values and found to be much smaller than the design values, indicating conservative design values of traffic loading and a safe traffic-loading condition of the bridge. The results of this study can be used as a reference for the design and condition assessment of similar bridges carrying heavy traffic, analogous to the TMB.

• Spatial Information Research
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• v.17 no.3
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• pp.301-307
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• 2009

Recently, the various studies has been focused on evaluating the damage and stability of long span bridge through measuring and monitoring to ensure the stability and usability. But, even if various studies are performed, it is hard to predict and evaluate the real motion of structure. The aim of this study is check the application of GPS to the motion monitoring of long span bridge by comparing data acquired form RTK-GPS and laser displacement meter.

• Steel and Composite Structures
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• v.46 no.6
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• pp.731-744
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• 2023

Vehicle load information is an important role in operating and ensuring the structural health of cable-stayed bridges. In this regard, an efficient and economic method is proposed for vehicle load detection based on the observed cable tension and vehicle position using a graph neural network (GNN). Datasets are first generated using the practical advanced analysis program (PAAP), a robust program for modeling and considering both geometric and material nonlinearities of bridge structures subjected to vehicle load with low computational costs. With the superiority of GNN, the proposed model is demonstrated to precisely capture complex nonlinear correlations between the input features and vehicle load in the output. Four popular machine learning methods including artificial neural network (ANN), decision tree (DT), random forest (RF), and support vector machines (SVM) are refereed in a comparison. A case study of a cable-stayed bridge with the typical truck is considered to evaluate the model's performance. The results demonstrate that the GNN-based model provides high accuracy and efficiency in prediction with satisfactory correlation coefficients, efficient determination values, and very small errors; and is a novel approach for vehicle load detection with the input data of the existing monitoring system.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.111-117
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• 2008

This study aims to develop a system which is able to monitor and analyze behavior of long span bridge in real time using multiple GPS. Through setting up many GPS at the important points of long span bridge and measuring displacement in real time, over all behavior of bridge could be analyzed. Behavior analyzing system developed in this study is able to digitize and visualize the overall and points displacement of bridge and deal with events actively. Also it is able to calculate statistical data related to analyze behavior through the constructing a database of measuring data.

• Smart Structures and Systems
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• v.25 no.5
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• pp.593-604
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• 2020

Temperature may have more significant influences on structural responses than operational loads or structural damage. Therefore, a comprehensive understanding of temperature distributions has great significance for proper design and maintenance of bridges. In this study, the temperature distribution of the steel box girder is systematically investigated based on the structural health monitoring system (SHMS) of the Sutong Cable-stayed Bridge. Specifically, the characteristics of the temperature and temperature difference between different measurement points are studied based on field temperature measurements. Accordingly, the probability density distributions of the temperature and temperature difference are calculated statistically, which are further described by the general formulas. The results indicate that: (1) the temperature and temperature difference exhibit distinct seasonal characteristics and strong periodicity, and the temperature and temperature difference among different measurement points are strongly correlated, respectively; (2) the probability density of the temperature difference distribution presents strong non-Gaussian characteristics; (3) the probability density function of temperature can be described by the weighted sum of four Normal distributions. Meanwhile, the temperature difference can be described by the weighted sum of Weibull distribution and Normal distribution.