• Journal of the Earthquake Engineering Society of Korea
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• v.7 no.2
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• pp.85-92
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• 2003

This paper presents an electric power generating system for stand-alone health monitoring sensor unit of bridge structure based on ambient vibration of bridge. In this paper, a novel electric power generator which has minimum effect of armature reaction is proposed. The related mechanical and electrical design equations are obtained, and a pilot generator has been implemented. In addition, the charging system for extremely low generator current is discussed, and some improvements are identified for the system. This investigation reveals that diode characteristics of rectifier is dominant factor in the charging process. Finally, both the simulation, which uses real measurement data of the Namhae bridge as input of the pilot generator, and indoor test are carried out. The results showed the applicability and effectiveness of the stand-alone vibration powered generator.

• Structural Monitoring and Maintenance
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• v.7 no.2
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• pp.109-124
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• 2020

Benefiting from the massive monitoring data collected by the Structural health monitoring (SHM) system, scholars can grasp the complex environmental effects and structural state during structure operation. However, the monitoring data is often missing due to sensor faults and other reasons. It is necessary to study the recovery method of missing monitoring data. Taking the structural temperature monitoring data of Nanjing Dashengguan Yangtze River Bridge as an example, the long short-term memory (LSTM) network-based recovery method for missing structural temperature data is proposed in this paper. Firstly, the prediction results of temperature data using LSTM network, support vector machine (SVM), and wavelet neural network (WNN) are compared to verify the accuracy advantage of LSTM network in predicting time series data (such as structural temperature). Secondly, the application of LSTM network in the recovery of missing structural temperature data is discussed in detail. The results show that: the LSTM network can effectively recover the missing structural temperature data; incorporating more intact sensor data as input will further improve the recovery effect of missing data; selecting the sensor data which has a higher correlation coefficient with the data we want to recover as the input can achieve higher accuracy.

• Smart Structures and Systems
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• v.21 no.5
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• pp.611-621
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• 2018

Compared with the highway bridges, the relatively higher requirement on the safety and comfort of vehicle makes the high-speed railway (HSR) bridges need to present enhanced dynamic performance. To this end, installing a health monitor system (HMS) on selected key HSR bridges has been widely applied. Typically, the HSR takes fully enclosed operation model and its skylight time is very short, which means that it is not easy to operate the acquisition devices and download data on site. However, current HMS usually involves manual operations, which makes it inconvenient to be used for the HSR. Hence, a HMS named DASP-MTS (Data Acquisition and Signal Processing - Monitoring Test System) that integrates the internet, cloud computing (CC) and virtual instrument (VI) techniques, is developed in this study. DASP-MTS can realize data acquisition and transmission automatically. Furthermore, the acquired data can be timely shared with experts from various locations to deal with the unexpected events. The system works in a Browser/Server frame so that users at any places can obtain real-time data and assess the health situation without installing any software. The developed integrated HMS has been applied to the Xijiang high-speed railway arch bridge. Preliminary analysis results are presented to demonstrate the efficacy of the DASP-MTS as applied to the HSR bridges. This study will provide a reference to design the HMS for other similar bridges.

• Steel and Composite Structures
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• v.27 no.3
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• pp.327-335
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• 2018

This paper presents structural assessment of a steel railway bridge for current condition using modal parameter to upgrade finite element modeling in order to gather accurate result. An adequate monitoring, such as acceleration, displacement, strain monitoring, is important tool to understand behavior and to assess structural performance of the structure under surround vibration by means of the dynamic analysis. Evaluation of conditions of an existing steel railway bridge consist of 4 decks, three of them are 14 m, one of them is 9.7 m, was performed with a numerical analysis and a series of dynamic tests. Numerical analysis was performed implementing finite element model of the bridge using SAP2000 software. Dynamic tests were performed by collecting acceleration data caused by surrounding vibrations and dynamic analysis is performed by Operational Modal Analysis (OMA) using collected acceleration data. The acceleration response of the steel bridge is assumed to be governing response quantity for structural assessment and provide valuable information about the current statute of the structure. Modal identification determined based on response of the structure play significant role for upgrading finite element model of the structure and helping structural evaluation. Numerical and experimental dynamic properties are compared and finite element model of the bridge is updated by changing of material properties to reduce the differences between the results. In this paper, an existing steel railway bridge with four spans is evaluated by finite element model improved using operational modal analysis. Structural analysis performed for the bridge both for original and calibrated models, and results are compared. It is demonstrated that differences in natural frequencies are reduced between 0.2% to 5% by calibrating finite element modeling and stiffness properties.

• The Journal of the Korea Contents Association
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• v.16 no.1
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• pp.362-369
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• 2016

Recently, Last to check the security status of various medium and large bridge structures using various kinds of measurement equipment, but most of the methods are used to measure and check the displacement behavior of the bridge by a certain period. In this study, receive GPS satellite signals that can be observed in real time the whole region, a bridge to automatically measure the displacement and behavior characteristics of the structure in real-time in mm over the 24 hours, the measurement information and transmits the data to the wireless network, by making use, it was applied to the real-time monitoring system in connection with a bridge to be able to automatically notify GNSS fine displacement behavior. In fact, analysis and receives the measurement data to GNSS provided in the upper bridge of the middle and large-sized aging for this purpose, measuring USN and at the same time is converted into a three-dimensional position information of a test study was conducted to monitor the bridge displacement in real time. As a result, a vertical displacement of about 0.027~0.037m at the measurement time of day of the measurement point is that the repeated and confirmed.

• Smart Structures and Systems
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• v.6 no.3
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• pp.309-333
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• 2010

Civil infrastructure, in both its construction and maintenance, represents the largest societal investment in this country, outside of the health care industry. Despite being the lifeline of US commerce, civil infrastructure has scarcely benefited from the latest sensor technological advances. Our future should focus on harnessing these technologies to enhance the robustness, longevity and economic viability of this vast, societal investment, in light of inherent uncertainties and their exposure to service and even extreme loadings. One of the principal means of insuring the robustness and longevity of infrastructure is to strategically deploy smart sensors in them. Therefore, the objective is to develop novel, durable, smart sensors that are especially applicable to major infrastructure and the facilities to validate their reliability and long-term functionality. In some cases, this implies the development of new sensing elements themselves, while in other cases involves innovative packaging and use of existing sensor technologies. In either case, a parallel focus will be the integration and networking of these smart sensing elements for reliable data acquisition, transmission, and fusion, within a decision-making framework targeting efficient management and maintenance of infrastructure systems. In this paper, prudent and viable sensor and health monitoring technologies have been developed and used in several large structural systems. Discussion will also include several practical bridge health monitoring applications including their design, construction, and operation of the systems.

• Structural Engineering and Mechanics
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• v.74 no.2
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• pp.157-173
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• 2020

In the finite element modelling of long-span cable-stayed bridges, there are a lot of uncertainties brought about by the complex structural configuration, material behaviour, boundary conditions, structural connections, etc. In order to reduce the discrepancies between the theoretical finite element model and the actual static and dynamic behaviour, updating is indispensable after establishment of the finite element model to provide a reliable baseline version for further analysis. Traditional sensitivity-based updating methods cannot support updating based on static and dynamic measurement data at the same time. The finite element model is required in every optimization iteration which limits the efficiency greatly. A convenient but accurate Kriging surrogate model for updating of the finite element model of cable-stayed bridge is proposed. First, a simple cable-stayed bridge is used to verify the method and the updating results of Kriging model are compared with those using the response surface model. Results show that Kriging model has higher accuracy than the response surface model. Then the method is utilized to update the model of a long-span cable-stayed bridge in Hong Kong. The natural frequencies are extracted using various methods from the ambient data collected by the Wind and Structural Health Monitoring System installed on the bridge. The maximum deflection records at two specific locations in the load test form the updating objective function. Finally, the fatigue lives of the structure at two cross sections are calculated with the finite element models before and after updating considering the mean stress effect. Results are compared with those calculated from the strain gauge data for verification.

• Structural Monitoring and Maintenance
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• v.3 no.3
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• pp.233-257
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• 2016

This paper provides an overview on development of long-span bridges monitoring in Japan, with emphasis on monitoring strategies, types of monitoring system, and effective utilization of monitoring data. Because of severe environment condition such as high seismic activity and strong wind, bridge monitoring systems in Japan historically put more emphasis on structural evaluation against extreme events. Monitoring data were used to verify design assumptions, update specifications, and facilitate the efficacy of vibration control system. These were among the first objectives of instrumentation of long-span bridges in a framework of monitoring system in Japan. Later, monitoring systems were also utilized to evaluate structural performance under various environment and loading conditions, and to detect the possible structural deterioration over the age of structures. Monitoring systems are also employed as the basis of investigation and decision making for structural repair and/or retrofit when required. More recent interest has been to further extend application of monitoring to facilitate operation and maintenance, through rationalization of risk and asset management by utilizing monitoring data. The paper describes strategies and several examples of monitoring system and lessons learned from structural monitoring of long-span bridges in Japan.

• Smart Structures and Systems
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• v.33 no.6
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• pp.399-414
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• 2024

This study discusses the long-term deformation monitoring and shape sensing of bridge girder surfaces with an automated extraction scheme for point clouds in the Region Of Interest (ROI), invariant to the position of a Light Detection And Ranging system (LiDAR). Advanced smart construction necessitates continuous monitoring of the deformation and shape of bridge girders during the construction phase. An automated scheme is proposed for reconstructing geometric model of ROI in the presence of noisy non-stationary background. The proposed scheme involves (i) denoising irrelevant background point clouds using dimensions from the design model, (ii) extracting the outer boundaries of the bridge girder by transforming and processing the point cloud data in a two-dimensional image space, (iii) extracting topology of pre-defined targets using the modified Otsu method, (iv) registering the point clouds to a common reference frame or design coordinate using extracted predefined targets placed outside ROI, and (v) defining the bounding box in the point clouds using corresponding dimensional information of the bridge girder and abutments from the design model. The surface-fitted reconstructed geometric model in the ROI is superposed consistently over a long period to monitor bridge shape and derive deflection during the construction phase, which is highly correlated. The proposed scheme of combining 2D-3D with the design model overcomes the sensitivity of 3D point cloud registration to initial match, which often leads to a local extremum.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.66-73
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• 2024

Stay-cable is one of the most important load carrying members in cable-stayed bridges. Monitoring structural integrity of stay-cables is crucial for evaluating the structural condition of the cable-stayed bridge. For stay-cables, tension and damping ratio are estimated based on modal properties as a measure of structural integrity. Since the monitoring system continuously measures the vibration for the long-term period, data acquisition systems should be stable and power-efficiency as the hardware system. In addition, massive signals from the data acquisition systems are continuously generated, so that automated analysis system should be indispensable. In order to fulfill these purpose simultaneously, this study presents an autonomous cable monitoring system based on domain-knowledge using IoT for continuous cable monitoring systems of cable-stayed bridges. An IoT system was developed to provide effective and power-efficient data acquisition and on-board processing capability for Edge-computing. Automated peak-picking algorithm using domain knowledge was embedded to the IoT system in order to analyze massive data from continuous monitoring automatically and reliably. To evaluate its operational performance in real fields, the developed autonomous monitoring system has been installed on a cable-stayed bridge in Korea. The operational performance are confirmed and validated by comparing with the existing system in terms of data transmission rates, accuracy and efficiency of tension estimation.