• International Journal of High-Rise Buildings
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• v.12 no.4
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• pp.321-333
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• 2023

Structural health monitoring is a technology or research field that extends the service life of structures and contributes to the prevention of disaster accidents by continuously evaluating the safety, stability, and serviceability of structures as well as allowing timely and proper maintenance. However, the contact-type sensors used for it require considerable time, cost, and labor for installation and maintenance. As an alternative, computer vision has attracted attention recently. Computer vision has the potential to make quality, deformation, and damage monitoring for structures contactless and automated. In this study, research cases in which computer vision was utilized for structural health monitoring are introduced, and its effects and limitations are summarized. Therefore, the applicability and future research directions of computer vision-based structural health monitoring are discussed.

• Smart Structures and Systems
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• v.24 no.6
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• pp.693-707
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• 2019

This paper proposes an integrated safety assessment method that can take multiple sources data into consideration based on a data fusion approach. Data cleaning using the Kalman filter method (KF) was conducted first for monitoring data from each sensor. The inclination data from the four tilt sensors of the same monitoring section have been associated to synchronize in time. Secondly, the finite element method (FEM) model was established to physically correlate the external forces with various structural responses of the shield tunnel, including the measured inclination. Response surface method (RSM) was adopted to express the relationship between external forces and the structural responses. Then, the external forces were updated based on the in situ monitoring data from tilt sensors using the extended Kalman filter method (EKF). Finally, mechanics parameters of the tunnel lining were estimated based on the updated data to make an integrated safety assessment. An application example of the proposed method was presented for an urban tunnel during a nearby deep excavation with multiple source monitoring plans. The change of tunnel convergence, bolt stress and segment internal forces can also be calculated based on the real time deformation monitoring of the shield tunnel. The proposed method was verified by predicting the data using the other three sensors in the same section. The correlation among different monitoring data has been discussed before the conclusion was drawn.

• Smart Structures and Systems
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• v.12 no.2
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• pp.209-233
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• 2013

With an annual growth rate of about 30%, wind energy systems, such as wind turbines, represent one of the fastest growing renewable energy technologies. Continuous structural health monitoring of wind turbines can help improving structural reliability and facilitating optimal decisions with respect to maintenance and operation at minimum associated life-cycle costs. This paper presents an integrated monitoring system that is designed to support structural assessment and life-cycle management of wind turbines. The monitoring system systematically integrates a wide variety of hardware and software modules, including sensors and computer systems for automated data acquisition, data analysis and data archival, a multiagent-based system for self-diagnosis of sensor malfunctions, a model updating and damage detection framework for structural assessment, and a management module for monitoring the structural condition and the operational efficiency of the wind turbine. The monitoring system has been installed on a 500 kW wind turbine located in Germany. Since its initial deployment in 2009, the system automatically collects and processes structural, environmental, and operational wind turbine data. The results demonstrate the potential of the proposed approach not only to ensure continuous safety of the structures, but also to enable cost-efficient maintenance and operation of wind turbines.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.635-638
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• 2007

In this paper, we described the fundamental concepts of proposed structural health monitoring system for Uldolmok Tidal Current Power Plant focusing on the use of smart sensors including fiber bragg grating sensors and macro fiber composite sensors. The structural health monitoring system can play an important role to maintain the structural safety for offshore structures like as bridges and high-rise buildings. In the case of tidal current power plant, the monitoring system is much more important since the structures are usually constructed at the site with severer environmental loadings such as high current speed.

• Geomechanics and Engineering
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• v.30 no.3
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• pp.313-324
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• 2022

With the development of the economy, people's utilization of underground space are also improved, and a large number of cities have begun to build subways to relieve traffic pressure. The choice of subway station construction method is crucial. If an inappropriate construction method is selected, it will not only waste costs but also cause excessive deformation that may also threaten construction safety. In this paper, a subway station construction scheme selects model based on the AHP-fuzzy comprehensive evaluation. The rationality of the model is verified using numerical simulation and monitoring measurement data. Firstly, considering the economy and safety, a comprehensive evaluation system is established by selecting several indicators. Then, the analytic hierarchy process is used to determine the weight of the evaluation index, and the dimensionless membership in the fuzzy comprehensive evaluation method is used to evaluate the advantages and disadvantages of the construction method. Finally, the method is applied to Liaoyang east road station of Qingdao metro Line 2, and the results are verified by numerical simulation and monitoring measurement data. The results show that the model is scientific, practical and applicable.

• Journal of the Korea Safety Management & Science
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• v.23 no.4
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• pp.67-72
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• 2021

To ensure the safety and functionality of a railroad bridge, maintaining the integrity of the bridge via continuous structural health monitoring is important. However, most structural integrity monitoring methods proposed to date are based on modal responses which require the extracting process and have limited availability. In this paper, the applicability of the existing damage identification method based on free-vibration reponses to time-domain deflection shapes due to moving train load is investigated. Since the proposed method directly utilizes the time-domain responses of the structure due to the moving vehicles, the extracting process for modal responses can be avoided, and the applicability of structural health evaluation can be enhanced. The feasibility of the presented method is verified via a numerical example of a simple plate girder bridge.

• Fire Science and Engineering
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• v.30 no.4
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• pp.103-110
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• 2016

While the demand for the gas system fire extinguishers increases every year, there are insufficient safety measures for assessing the extinguishing performance, such as system safety and reliability in the preparation of increasing demand, which has emerged as a social problem. One of the most critical causes of accidents occurring with the gas extinguishing system is pressure leakage from the extinguishing agent storage container. This is considered to be one of the critical factors on which the success of fire suppression depends. In this study, its safety measure was studied, Because it was deemed urgently necessary. The newly developed pressure leakage monitoring system is a system monitoring storage condition, pressure, leakage and discharge of the storage container related to agent concentration, which is one of the critical factors for fire suppression. This was developed to be applicable to the $CO_2$ and HFC-23 systems. Therefore, for structural safety analysis, the safety performance was verified by the fluid structure coupling analysis of the safety problems that may occur when the pressure leakage monitoring system is applied to the gas fire extinguisher. For analysis programs, the FloEFD program from Mentor Graphics was used for computational fluid dynamics analysis and ABAQUS from Dassault Systems was used for structural analysis. From the result of numerical analysis, the structure of $CO_2$ did not develop plastic deformation and its safety was verified. However, plastic deformation and deviation issue occurred with the HFC-23 monitoring system and therefore verified the structural safety of pressure leakage monitoring system by data obtained from redesigning and adjusting the condition of numerical interpretation three times.

• Smart Structures and Systems
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• v.18 no.2
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• pp.317-334
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• 2016

Structural Health Monitoring System (SHMS) works as an efficient platform for monitoring the health status and performance deterioration of engineering structures during long-term service periods. The objective of its installation is to provide reasonable suggestions for structural maintenance and management, and therefore ensure the structural safety based on the information extracted from the real-time measured data. In this paper, the SHMS implemented on a world-famous kilometer-level cable-stayed bridge, named as Sutong Cable-stayed Bridge (SCB), is introduced in detail. The composition and core functions of the SHMS on SCB are elaborately presented. The system consists of four main subsystems including sensory subsystem, data acquisition and transmission subsystem, data management and control subsystem and structural health evaluation subsystem. All of the four parts are decomposed to separately describe their own constitutions and connected to illustrate the systematic functions. Accordingly, the main techniques and strategies adopted in the SHMS establishment are presented and some extension researches based on structural health monitoring are discussed. The introduction of the SHMS on SCB is expected to provide references for the establishment of SHMSs on long-span bridges with similar features as well as the implementation of potential researches based on structural health monitoring.

• Proceedings of the Korea Concrete Institute Conference
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• 2002.10a
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• pp.717-723
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• 2002

Recently, the interest in safety assessment of civil infrastructures is increasing in Korea. Especially, as bridge structures become large-scale, it is necessary to monitor and maintain the safety state of bridges, which requires the monitoring system that can make a long-term measurement during the service time of bridge. In this paper, advanced fiber optic sensors for long-term measurement, setup techniques of bridge monitoring system and the assessment of measured data are introduced. Attached or embedded optical fiber sensors to structural members of small and big structures including Sung San Bridge are surveyed. For the Sung San Bridge, the responses of the fiber optic sensors by 30 ton weigh truck loads with various speeds ate measured. Monitoring system is also applied to the mock-up of bridges. The monitoring capability of the advanced fiber optic sensor system was confirmed.

• Computers and Concrete
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• v.20 no.5
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• pp.555-562
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• 2017

The accuracy and integrity of stress data acquired by bridge heath monitoring system is of significant importance for bridge safety assessment. However, the missing and abnormal data are inevitably existed in a realistic monitoring system. This paper presents a data reconstruction approach for bridge heath monitoring based on the wavelet multi-resolution analysis and support vector machine (SVM). The proposed method has been applied for data imputation based on the recorded data by the structural health monitoring (SHM) system instrumented on a prestressed concrete cable-stayed bridge. The effectiveness and accuracy of the proposed wavelet-based SVM prediction method is examined by comparing with the traditional autoregression moving average (ARMA) method and SVM prediction method without wavelet multi-resolution analysis in accordance with the prediction errors. The data reconstruction analysis based on 5-day and 1-day continuous stress history data with obvious preternatural signals is performed to examine the effect of sample size on the accuracy of data reconstruction. The results indicate that the proposed data reconstruction approach based on wavelet multi-resolution analysis and SVM is an effective tool for missing data imputation or preternatural signal replacement, which can serve as a solid foundation for the purpose of accurately evaluating the safety of bridge structures.