• Journal of the Korea institute for structural maintenance and inspection
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• v.3 no.2
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• pp.221-232
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• 1999

This study investigates the applicability and design scheme of fieldbus network in the measurement system used for precise and safe construction as well as efficient maintenance of bridges. In order to maximize the function and performance of bridge monitoring system, this study introduces the CAN(Controller Area Network), one of the fieldbus protocols, in the measurement system of bridges. This study presents the implementation method of CAN on the monitoring system of bridge, and also proposes a bandwidth allocation scheme for the design of network. The validity of the proposed CAN design method is verified through a simulation experiment. It is shown that the CAN can be readily applicable to the measurement system of bridges.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.65.6-65
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• 2001

The satellite communication has been widely applied in the various fields included the remote monitoring and control system through the technical progress. In the star network that is a type of the satellite communication network, users can easily use an earth station because of the large scale and high power of the hub station. This type has many profits which are flexible of network configuration, and can conveniently and inexpensively supply various services which is used in the data acquisition and distribution by important communication means for construction of information society. Using these profits, the satellite communication system is applied to the unmaned remote operation field for the remote control and monitor of the water treatment plants But, ...

• Nuclear Engineering and Technology
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• v.50 no.7
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• pp.1160-1167
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• 2018

Detectability of the loose parts (LPs) in steam generator (SG) was studied with eddy current testing technique such as X-probe, bobbin and rotating coils ($MRPC^{(R)}$) as a function of LP size and spacing between LP and tube or between LP and support structures. SG mockup simulating SG tube and support structures with LP was fabricated. The X-probe showed slightly better detectability than $MRPC^{(R)}$ for LP of ferrous (F-LP) material and vice versa for LP of nonferrous (NF-LP) material. In terms of feasibility, inspection rate and other predictable features of the SG tubing inspections, X-probe can be used reliably for monitoring the LPs and the flaws formed by LPs on SG tubes.

• Smart Structures and Systems
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• v.21 no.1
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• pp.123-137
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• 2018

Structural monitoring is the most important part of the construction and operation of the embankment dams. Appropriate instruments selection for dams is vital, as inappropriate selection causes irreparable loss in critical condition. Due to the lack of a systematic approach to determine adequate instruments, a framework based on three comparable Multi-Attribute Decision Making (MADM) methods, which are VIKOR, technique of order preference by similarity to ideal solution (TOPSIS) and Preference ranking organization method for enrichment evaluation (PROMETHEE), has been developed. MADM techniques have been widely used for optimizing priorities and determination of the most suitable alternatives. However, the results of the different methods of MADM have indicated inconsistency in ranking alternatives due to closeness of judgements from decision makers. In this study, 9 criteria and 42 geotechnical instruments have been applied. A new method has been developed to determine the decision makers' importance weights and an aggregation method has been introduced to optimally select the most suitable instruments. Consequently, the outcomes of the aggregation ranking correlate about 94% with TOPSIS and VIKOR, and 83% with PROMETHEE methods' results providing remarkably appropriate prioritisation of instruments for embankment dams.

• Smart Structures and Systems
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• v.26 no.5
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• pp.667-680
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• 2020

This study aims at reporting a systematic procedure for evaluating the static and dynamic structural performance of steel bridges based on a short-period structural health monitoring measurement. Sungsu bridge located in Korea is considered as a case study presenting the most recent tests carried out to examine the bridge condition. Short-period measurements of Structural Health Monitoring (SHM) system were used during the bridge testing phase. A novel symmetry index is introduced using statistical analyses of deflection and strain measurements. Frequency Domain Decomposition (FDD) is implemented to the strain measurements to estimate the bridge mode shapes and damping ratios. Furthermore, Markov Chain Monte Carlo (MCMC) is also implemented to examine the reliability of bridge performance while ambient design trucks are in static or moving at different speeds. Strain, displacement and acceleration were measured at selected locations on the bridge. The results show that the symmetry index can be an efficient and useful measure in assessing the steel bridge performance. The results from the used method reveal that the performance of the Sungsu bridge is safe under operational conditions.

• Journal of the Korea Safety Management & Science
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• v.13 no.2
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• pp.31-42
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• 2011

Smart-Phones are utilized in disaster management field because it can deliver disaster information to large population simultaneously and quickly, and provide accurate information through situation-based service using the LBS(Location Based Service). To study on the utilization of smart phone for disaster information collection and dissemination method, this study suggest a framework which connects smart phone by loading application for reporting disaster. The disaster monitoring and situation dissemination system framework using smart phone is composed of 4 parts. First, smart phone application enters image, video, voice and text information and location of the disaster. Second, the disaster report reception and situation dissemination server receives the information, save in the DB, and send through smart phone SMS. Third, store into disaster information database. Fourth, display the disaster report and management information on 2D GIS, support the decision making process in deciding whether to manage as disaster, and disaster management web service which disseminates situation.

• Smart Structures and Systems
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• v.23 no.3
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• pp.295-306
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• 2019

Shanghai Tower is a 632-meter super high-rise building located in an area with wind and active earthquake. A sophisticated structural health monitoring (SHM) system consisting of more than 400 sensors has been built to carry out a long-term monitoring for its operational safety. In this paper, a reduced-order model including 31 elements was generated from a full model of this super tall building. An iterative regularized matrix method was proposed to tune the system parameters, making the dynamic characteristic of the reduced-order model be consistent with those in the full model. The updating reduced-order model can be regarded as a benchmark model for further analysis. A long-term monitoring for structural dynamic characteristics of Shanghai Tower under different construction stages was also investigated. The identified results, including natural frequency and damping ratio, were discussed. Based on the data collected from the SHM system, the dynamic characteristics of the whole structure was investigated. Compared with the result of the finite element model, a good agreement can be observed. The result provides a valuable reference for examining the evolution of future dynamic characteristics of this super tall building.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.2D
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• pp.159-166
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• 2012

During concrete placement, the formwork structure supports the weight of concrete mass. The complexity of the operation can cause concentrated workloads, which in turn brings about a collapse of the temporary structure. As a countermeasure, the operation needs to be constantly monitored to maintain safety and prevent accidents. This paper presents a USN (Ubiquitous Sensor Network)-based safety monitoring system for formwork construction. The system takes advantage of ubiquitous technology in monitoring the behavior of the formwork structure such as deflection, load weight, and tilting. The collected data are sent to the host computer wirelessly for real time monitoring. The data can be then compared with the allowed limits on guidelines. The comparison can indicate whether the concrete placement operation is executed in a safe condition.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.463-481
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• 2020

Cutter suction dredgers (CSDs) are widely used in various dredging constructions such as channel excavation, wharf construction, and reef construction. During a CSD construction, the main operation is to control the swing speed of cutter to keep the slurry concentration in a proper range. However, the slurry concentration cannot be monitored in real-time, i.e., there is a "time-lag effect" in the log of slurry concentration, making it difficult for operators to make the optimal decision on controlling. Concerning this issue, a solution scheme that using real-time monitored indicators to predict current slurry concentration is proposed in this research. The characteristics of the CSD monitoring data are first studied, and a set of preprocessing methods are presented. Then we put forward the concept of "index class" to select the important indices. Finally, an ensemble learning algorithm is set up to fit the relationship between the slurry concentration and the indices of the index classes. In the experiment, log data over seven days of a practical dredging construction is collected. For comparison, the Deep Neural Network (DNN), Long Short Time Memory (LSTM), Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and the Bayesian Ridge algorithm are tried. The results show that our method has the best performance with an R² of 0.886 and a mean square error (MSE) of 5.538. This research provides an effective way for real-time predicting the slurry concentration of CSDs and can help to improve the stationarity and production efficiency of dredging construction.