• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.389-404
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• 2017

The main purpose of this presented investigation is to build up the BHMS based on GNSS. This proposed monitoring system can conduct the deflection and dynamic characteristics analysis by using only GNSS positioning solution. The general bridge monitoring system being operated recently is composed of a combination of various sensors that are able to conduct deflection monitoring and dynamic characteristics monitoring analysis at the same time. However, GNSS based BHMS has the unique procedure in terms of data analysis. In the other words, GNSS positioning solution is firstly applied to deflection monitoring analysis then, this deflection analysis can be sequentially reflected in the dynamic characteristics. Unfortunately, the adjustment result of GNSS positioning solution estimated through various options and conditions and the process of monitoring analysis has not been fulfilled systematically. This means that different results or analysis value are presented according to the methodology and officers. Most of researches have been focusing on deflection monitoring analysis and some investigation regarding to dynamic characteristics is recently introduced. Moreover, it is not still reported the systematic investigation with regards to proper filtering and analysis methodology. This study was carried out based on a large amount of data, from this, various variables not reported yet are actively considered. Therefore, specific software for both monitoring analysis have been developed.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.50_51
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• 2009

This paper describes the novel real-time embeded Dynamic System Monitor(KDSM) for dynamic device modeling and disturbace monitoring. The KDSM uses the variable resampling technique together with DFT algorithm so that it overcomes the shortcomings of the existing DFT algorithm at the big deviation of network frequency. The suggested algorithm is implemented by using the NI-PXI system, and verified by applying to the generator testing.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.11
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• pp.1732-1736
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• 2012

To increase speed up of train, in the field of catenary system, it is necessary to develop of new monitoring methods for dynamic interaction between pantograph and contact wire. Also, there is a need to develop technologies that constantly measure are from various railway structure such as uplift of contact wire, vibration of catenary, dynamic strain of contact line in tunnel. In this paper condition monitoring systems for dynamic performance of catenary systems in tunnel were proposed. An advanced method and results of field tests using high speed camera for monitoring of vertical upward movement of the grooved contact wire due to the force produced from the pantograph were presented. The proposed uplift measurement system of contact wire is expected to enhance precision of current collection quality performance assessment methods at high-speed lines.

• Smart Structures and Systems
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• v.29 no.5
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• pp.715-728
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• 2022

Recently, numbers of long span pedestrian suspension bridges have been constructed worldwide. While recent tragedies regarding pedestrian suspension bridges have shown how these bridges can wreak havoc on the society, there are no specific guidelines for construction standards nor safety inspections yet. Therefore, a structural health monitoring system that could help ensure the safety of pedestrian suspension bridges are needed. System identification is one of the popular applications for structural health monitoring method, which estimates the dynamic system. Most of the system identification methods for bridges are currently adapting output-only system identification method, which assumes the dynamic load to be a white noise due to the difficulty of measuring the dynamic load. In the case of pedestrian suspension bridges, the pedestrian load is within specific frequency range, resulting in large errors when using the output-only system identification method. Therefore, this study aims to develop a system identification method for pedestrian suspension bridges considering both input and output of the dynamic system. This study estimates the location and the magnitude of the pedestrian load, as well as the dynamic response of the pedestrian bridges by utilizing artificial intelligence and computer vision techniques. A simulation-based validation test was conducted to verify the performance of the proposed system. The proposed method is expected to improve the accuracy and the efficiency of the current inspection and monitoring systems for pedestrian suspension bridges.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.9
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• pp.512-519
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• 2000

A Neural networks has been used for a expert system and fault diagnosis system. It is possible to nonlinear function mapping and parallel processing. Therefore It has been developing for a Diagnosis system of nuclear plower plant. In general Neural Networks is a static mapping but Dynamic Neural Network(DNN) is dynamic mapping.쪼두 a fault occur in system a state of system is changed with transient state. Because of a previous state signal is considered as a information DNN is better suited for diagnosis systems than static neural network. But a DNN has many weights so a real time implementation of diagnosis system is in need of a rapid network architecture. This paper presents a algorithm for RCP monitoring Alarm diagnosis system using Self Dynamic Neural Network(SDNN). SDNN has considerably fewer weights than a general DNN. Since there is no interlink among the hidden layer. The effectiveness of Alarm diagnosis system using the proposed algorithm is demonstrated by applying to RCP monitoring in Nuclear power plant.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.219-225
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• 1999

Monitoring of the cutting force signals in cutting process has been well emphasized in machine tool communities. Although the cutting force can be directly measured by a tool dynamometer, this method is not always feasible because of high cost and limitations in setup. In this paper an indirect cutting force monitoring system is developed so that the cutting force in turning process is estimated based on a AC spindle drive model. This monitoring system considers the cutting force as a disturbance input to the spindle drive and estimates the cutting force based on the inverse dynamic model. The inverse dynamic model represents the dynamic relation between the cutting force, the motor torque and the motor power. The proposed monitoring system is realized on a CNC lathe and its estimation performance is evaluated experimentally.

• Wind and Structures
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• v.24 no.4
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• pp.333-350
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• 2017

Differing from the fixed-type, the dynamic motion of floating-type offshore wind turbines is very sensitive to wind and wave excitations. Thus, the sensing and monitoring of its motion is important to evaluate the dynamic responses to the external excitation. In this context, a monitoring system for sensing and processing the wind-induced dynamic motion of spar-type floating offshore wind turbine is developed in this study. It is developed by integrating a 1/00 scale model of 2.5MW spar-type floating offshore wind turbine, water basin equipped with the wind generator, sensing and data acquisition systems, real-time CompactRIO controller and monitoring program. The scale model with the upper rotatable blades is installed within the basin by means of three mooring lines, and its translational and rotational motions are detected by 3-axis inclinometer and accelerometers and gyroscope. The detected motion signals are processed using a real-time controller CompactRIO to calculate the acceleration and tilting angle of nacelle and the attitude of floating platform. The developed monitoring system is demonstrated and validated by measuring and evaluating the time histories and trajectories of nacelle and platform motions for three different wind velocities and for eight different fairlead positions.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1019-1039
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• 2015

Shanghai Tower is a composite structure building with a height of 632 m. In order to verify the structural properties and behaviors in construction and operation, a structural health monitoring project was conducted by Tongji University. The monitoring system includes sensor system, data acquisition system and a monitoring software system. Focusing on the health monitoring in construction, this paper introduced the monitoring parameters in construction, the data acquisition strategy and an integration structural health monitoring (SHM) software. The integration software - Structural Monitoring/ Analysis/ Evaluation System (SMAE) is designed based on integration and modular design idea, which includes on-line data acquisition, finite elements and dynamic property analysis functions. With the integration and modular design idea, this SHM system can realize the data exchange and results comparison from on-site monitoring and FEM effectively. The analysis of the monitoring data collected during the process of construction shows that the system works stably, realize data acquirement and analysis effectively, and also provides measured basis for understanding the structural state of the construction. Meanwhile, references are provided for the future automates construction monitoring and implementation of high-rise building structures.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.11-15
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• 1999

Monitoring of the cutting force signals in cutting process has been well emphasized in machine tool communities. Although the cutting force can be directly measured by a tool dynamometer, this method is not always feasible because of high cost and limitations in setup. In this paper an indirect cutting force monitoring system is developed so that the cutting force in turning process is estimated based on a AC spindle drive model. This monitoring system considers the cutting force as a disturbance input to the spindle drive and estimates the cutting force based on the inverse dynamic model. The inverse dynamic model represents the dynamic relation between the cutting force, the motor torque and the motor power. The proposed monitoring system is realized on a CNC lathe and its estimation performance is evaluated experimentally.

• Journal of Internet Computing and Services
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• v.4 no.6
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• pp.13-24
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• 2003

Grid technology requires use of geographically distributed resources from multiple domains. Resource monitoring services or tools consisting sensors or agents will run on many systems to find static resource information (such as architecture vendor, OS name and version, MIPS rate, memory size, CPU capacity, disk size, and NIC information) and dynamic resource information (CPU usage, network usage(bandwidth, latency), memory usage, etc.). Thus monitoring itself may cause system overhead. This paper proposes the optimal monitoring interval to reduce the cost of monitoring services and the dynamic monitoring interval to measure monitoring events accurately. By employing two features, we find out unnecessary system overhead is significantly reduced and accuracy of events is still acquired.