• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.2
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• pp.134-144
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• 2007

In this study, a smart sensor unit is developed by using the smart sensor technology that is being rapidly developed in recent years for structural health monitoring system, and its performance is evaluated through various experiments, and also, damage detection experiment is performed on a model structure. This paper as the first half of this study contains the development and performance evaluation of the smart sensor. In the latter half of this study, structure damage detection experiment is performed for the application of verified smart sensor unit into structural health monitoring, and it is compared with a wire measurement system. The smart sensor is developed by using high-power wireless modem, MEMS Sensor and AVR microcontroller, and an embedded program is also developed for the control and operation of the sensor unit. To verify the performance of the smart sensor, many experiments are performed for sensitivity and resolution analysis tests, data acquisition by using cantilever beam and shaker, and on-site application using actual bridge. As a result, the smart sensor proves to be satisfactory in its performance.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.11-21
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• 2016

Recently, structure safety management techniques using cutting-edge technology(Displacement senor, sensor of acceleration) has emerged as an important issue owing to the aging of infrastructure such as bridge and building. In general, the structural monitoring system for structure safety management is based on IT technology and it is expensive to install. In this paper developed an image-based structure dynamic characteristic analysis system prototype to assess the damage of structure in a more cost-effective way than traditional structure health monitoring system. The inspector can take a video of buildings or other structures with digital camera or any other devices that is passible to take video, and then using NCC calculation for image processing technique to get natural frequency. This system is analysis of damage of the structure using a compare between the frequency response ratio and functions when problems are occurs send alarm to administrator. This system is easier to install and remove than previous monitoring sensor in economical way.

• Journal of the Korea institute for structural maintenance and inspection
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• v.1 no.2
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• pp.87-94
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• 1997

This research aims to develop an algorithm of optimal transducer placement using Kinetic Energy of the structural system. The structural vibration response-based health monitoring is considered one of the best for the system which requires a long-term, continuous monitoring. In its experimental modal testing, however, it is difficult to decide on the measurement locations and their number, especially for complex structures, which have a major influence on the quality of the results. In order to minimize the number of sensing operations and optimize the transducer location while maximizing the accuracy of results, this paper discusses about an optimum transducer placement criterion suitable for the identification of structural damage. As a criterion algorithm, it proposes the Kinetic Energy Optimization Technique (EOT), and then addresses the numerical issues which are subsequently applicable to actual experiment where a bridge model is used. By using the experimental data, it compares the EOT with the EIM (Effective Independence Method) which is generally used to optimize the transducer placement for the damage identification and control purposes. The comparison conclusively shows that the EOT algorithm proposed in this paper is preferable when a structure is to be instrumented with fewer sensors.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.393-402
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• 2011

This paper describes a design and application of middleware that is essential to the context-aware system. We define a transducer interface protocol in order to deal with a variety of context data. For the purpose of systematic process of data between middleware modules, a message oriented middleware is designed and implemented. Memory improves the performance of high-performance computing system compared to previous strategies. Context aware middleware adopts service oriented architecture so that functions in modules may be independent and scalability can be remarkable. Using messages across modules decreases the complexity of the application development. In order to justify the usefulness of the proposed context aware middleware, we carried out our experiments in bridge health monitoring system and verified the efficacy.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1994.10a
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• pp.95-102
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• 1994

This paper presents a Cable Stayed Bridge Construction Management System, which consists of Structural System Identification Method (SSIM), Error Sensitivity Analysis and Optimum Error Adjustment & Prediction System. The 1st System Identification Method builds an error influence matrix using the linear superposition of each error modes. The 2nd SSIM also considers the second error mode term, which shows good error factor estimation. The optimal cable adjustment can be accomplished within the allowable range of both cable tension and camber. The Post processor, constituted with Motif and GL library on SGI platform, is useful for monitoring construction stage management by displaying construction data, adjustment and prediction results at each construction step.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.197-202
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• 2008

In this paper, a hybrid vibration-impedance approaches is newly proposed to detect the occurrence of damage, the location of damage, and extent of damage in steel plate-girder bridges. The hybrid scheme mainly consists of three sequential phases: 1) to alarm the occurrence of damage, 2) to classify the alarmed damage, and 3) to estimate the classified damage in detail. Damage types of interest include flexural stiffness-loss in girder and bolts-loose in supports. In the first phase, the global occurrence of damage is alarmed by monitoring changes in acceleration features. In the second phase, the alarmed damage is classified into subsystems by recognizing patterns of impedance features. In the final phase, the location and the extent of damage are estimated by using modal strain energy-based damage index method and root mean square deviation method. The feasibility of the proposed system is evaluated on a laboratory-scaled steel plate-girder bridge model for which hybrid vibration-impedance signatures were measured for several damage scenarios.

• Smart Structures and Systems
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• v.4 no.6
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• pp.795-807
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• 2008

A challenging problem in structural damage detection based on vibration data is the requirement of a large number of sensors and the numerical difficulty in obtaining reasonably accurate results when the system is large. To address this issue, the substructure identification approach may be used. Due to practical limitations, the response data are not available at all degrees of freedom of the structure and the external excitations may not be measured (or available). In this paper, an adaptive damage tracking technique, referred to as the sequential nonlinear least-square estimation with unknown inputs and unknown outputs (SNLSE-UI-UO) and the sub-structure approach are used to identify damages at critical locations (hot spots) of the complex structure. In our approach, only a limited number of response data are needed and the external excitations may not be measured, thus significantly reducing the number of sensors required and the corresponding computational efforts. The accuracy of the proposed approach is illustrated using a long-span truss with finite-element formulation and an 8-story nonlinear base-isolated building. Simulation results demonstrate that the proposed approach is capable of tracking the local structural damages without the global information of the entire structure, and it is suitable for local structural health monitoring.

• Smart Structures and Systems
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• v.24 no.6
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• pp.733-744
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• 2019

Wind speed forecasting is critical for a variety of engineering tasks, such as wind energy harvesting, scheduling of a wind power system, and dynamic control of structures (e.g., wind turbine, bridge, and building). Wind speed, which has characteristics of random, nonlinear and uncertainty, is difficult to forecast. Nowadays, machine learning approaches (generalized regression neural network (GRNN), back propagation neural network (BPNN), and extreme learning machine (ELM)) are widely used for wind speed forecasting. In this study, two schemes are proposed to improve the forecasting performance of machine learning approaches. One is that optimization algorithms, i.e., cross validation (CV), genetic algorithm (GA), and particle swarm optimization (PSO), are used to automatically find the optimal model parameters. The other is that the combination of different machine learning methods is proposed by finite mixture (FM) method. Specifically, CV-GRNN, GA-BPNN, PSO-ELM belong to optimization algorithm-assisted machine learning approaches, and FM is a hybrid machine learning approach consisting of GRNN, BPNN, and ELM. The effectiveness of these machine learning methods in wind speed forecasting are fully investigated by one-year field monitoring data, and their performance is comprehensively compared.

• Journal of the Korean Geotechnical Society
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• v.36 no.11
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• pp.71-81
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• 2020

The large circular steel pipe for a marine bridge foundation has been developed as a construction method capable of performing the role of the working platform and cofferdam. The objective of this study is to demonstrate the wireless remote sensing system for monitoring the stability of the large circular steel pipe during construction and operation through field tests. The artificial seabed ground with an water level of 4 m is constructed for field tests. The large circular steel pipe with a diameter of 5 m and height of 9.5 m is installed into the ground by suction, and the embedded depth is 5 m. The inclinometer and strain gauges are installed on different surfaces of the upper module, and the tilt angle and stress are monitored throughout the entire construction process. As results, tilt angles are measured to be constant during the suction penetration. However, the tilt angle is larger in the x-axis direction. In addition, even when installed on different surfaces, the tilt angle in the same axial direction is measured to be almost the same. The stresses measured by strain gauges increase during suction penetration and decrease during pull-out. Based on measured stresses, it is found that the eccentricity is acting on the large circular steel pipe. This study shows that a wireless remote sensing system built with an inclinometer and strain gauge can be a useful tool for the stability monitoring of the large circular steel pipe.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2005.03a
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• pp.477-486
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• 2005

본 논문에서는 한국과 일본에 위치한 여러 연구기관들 사이에서 수행된 온라인 네트워크 유사동적 실험 결과에 대해 나타내었다.예제 구조물로는 4경간 연속의 면진 교량을 이용하였다. 실험 장비를 보유하고 있는 두 연구기관에서 면진 장치의 비선형 거동에 대한 실험을 수행하고 각 실험 결과를 조합하여 전체 구조의 동적 해석을 수행하였다. 본 논문에서는 먼저 인터넷을 이용한 두 가지 데이터 전송기법을 이용하여 두 기법의 효율성을 비교, 분석하였다. 또한 최근 국내에 위치한 두 연구기관 사이에서 수행된 실험 결과에 대해 논의하였다. 본 연구에서는 상대 연구기관의 실험 상황 및 수행된 실험 결과의 효율적인 모니터링을 위하여 웹 기반의 자바 모니터링 시스템을 개발하였다. 마지막으로 유선과 무선 인터넷을 이용한 온라인 실험 기법에 대하여 나타내었다. 그 결과, 온라인 네트워크 실험에 소요된 실험 시간은 데이터 전송 기법과 실험장비에 따라 매 시간 단계의 데이터 전송에 0.2-15초, 각 연구기관의 유사동적 실험에 1-10초의 시간이 소요되어 매우 큰 폭으로 변화함을 알 수 있었다. 또한 무선 인터넷을 이용한 온라인 실험의 경우, 뛰어난 이동성과 인터넷 보안성 등과 같은 여러 가지 장점을 가지고 있음을 알 수 있었다.