• Proceedings of the KSR Conference
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• 2009.05a
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• pp.291-295
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• 2009

We did the blooth module test as a pre-test of wireless sensor monitoring system, which for the improving of on-condition maintenance reliability, on the train. In this test, we examined the communication environment of wireless sensor monitoring system by the acceleration date and frequency date in the real train structure during the operation. Also based on this results, we did the experimental verification of the sensor power system which use piezoelectric energy conversion technology by the theoretical modeling for the applying on the train on-condition maintenance.

• Smart Structures and Systems
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• v.11 no.6
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• pp.637-662
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• 2013

The Jiangyin Bridge is a suspension bridge with a main span of 1385 m over the Yangtze River in Jiangsu Province, China. Being the first bridge with a main span exceeding 1 km in Chinese mainland, it had been instrumented with a structural health monitoring (SHM) system when completed in 1999. After operation for several years, it was found with malfunction in sensors and data acquisition units, and insufficient sensors to provide necessary information for structural health evaluation. This study reports the SHM system upgrade project on the Jiangyin Bridge. Although implementations of SHM system have been reported worldwide, few studies are available on the upgrade of SHM system so far. Recognizing this, the upgrade of original SHM system for the bridge is first discussed in detail. Especially, lessons learned from the original SHM system are applied to the design of upgraded SHM system right away. Then, performance assessment of the bridge, including: (i) characterization of temperature profiles and effects; (ii) recognition of wind characteristics and effects; and (iii) identification of modal properties, is carried out by making use of the long-term monitoring data obtained from the upgraded SHM system. Emphasis is placed on the verification of design assumptions and prediction of bridge behavior or extreme responses. The results may provide the baseline for structural health evaluation.

• IEMEK Journal of Embedded Systems and Applications
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• v.2 no.2
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• pp.101-106
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• 2007

Recently, according as USN application service models have been integrated each other and have become various, the need on the development of monitoring programs corresponding each service model has been risen steadily. However, if we stick to the traditional method developing independently each service model, we might pay unnecessary expenses. In this paper, we propose the monitoring program authoring tool for USN. Furthermore, we introduce an implementing example of the forest fire prevention monitoring system for verification of the proposed tool. The tool adopted the framework based programming and the S/W reusability techniques for minimizing waste of redeveloping cost.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.643-648
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• 2023

The Korea Augmentation Satellite System is an SBAS system being developed with the goal of providing SoL (Safety of Life) in accordance with ICAO (International Civil Aviation Organization) standards by December 2023. Monitoring the status of the system is essential for the continuous provision of KASS services, and a status monitoring tool should be developed for this purpose. The development of a status monitoring tool was divided into SYSRT (SYStem Real Time monitoring tool), SMSPP (Subsystem Monitoring Statistics tool for Post Processing) depending on the purpose. Tool development was completed through a series of procedures: requirements definition, design, development, and verification. To verify the status monitoring tool, the KASS system's real data (August 2023) were used to verify it, and the results were statistically analyzed to derive operating time and operating rate. It plans to use these tools to support continuous service provision for SoL service starting after this year.

• Tunnel and Underground Space
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• v.30 no.1
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• pp.1-14
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• 2020

Microseismic monitoring is utilized for the performance verification and safety management of the structure by detecting fine levels of damage. In order to construct a highly reliable microseismic monitoring system, the role of signal conditioner is critical. The signal conditioner helps with accurate data collection and precision control of the device, and performs additional functions such as signal conversion, linearization, and amplification. In this technical report, noise reduction signal conditioner suitable for mining sites was developed and reviewed for the purpose of implementing more precise monitoring by supplementing the previously developed microseismic monitoring system.

• Journal of the Korean Society of Safety
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• v.25 no.2
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• pp.29-34
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• 2010

This paper is aimed to develop monitoring software for detecting the characteristics of current and voltage signals for series arc on electric wire. In order to attain this purpose, the characteristics of series arc were analyzed by the current and voltage signals on electric wire which were installed, and also analyzed by the changes of RMS, instantaneous of waveform value in time domain and THD in frequency domain. Monitoring program which analyze the signal was developed by Labview which can analyze in time domain and frequency domain, and save data. Experimental setup for detecting verification of monitoring program was composed loads of a lamp, an electric heater and an electric fan loads which were usually using. Measurement points for detecting verification of monitoring program were selected at both the panel board and the arc generator at the same time. As results of the experiments by monitoring program, the arc current waveform showed the same characteristic in all measurement points of all load. But the arc voltage waveform was different in each measurement point. When arc occurred, the THD of current value increased above 20%. The results of this study will be effectively used in developing the preventive system of electric fire by series arc.

• Spatial Information Research
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• v.21 no.3
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• pp.11-19
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• 2013

Compared with traditional video monitoring systems that provide a video-recording function as a main service, an intelligent video monitoring system is capable of extracting/tracking objects and detecting events such as car accidents, traffic congestion, pedestrian detection, and so on. Thus, the object tracking is an essential function for various intelligent video monitoring and surveillance systems. In this paper, we propose a background and local histogram-based object tracking approach for intelligent video monitoring systems. For robust object tracking in a live situation, the result of optical flow and local histogram verification are combined with the result of background subtraction. In the proposed approach, local histogram verification allows the system to track target objects more reliably when the local histogram of LK position is not similar to the previous histogram. Experimental results are provided to show the proposed tracking algorithm is robust in object occlusion and scale change situation.

• Journal of Korean Society of Rural Planning
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• v.21 no.4
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• pp.177-186
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• 2015

The main objective of this study was to assess the applicability of IoT (Internet of Things)-based flood management under climate change by developing intelligent water level monitoring platform based on IoT. In this study, Arduino Uno was selected as the development board, which is an open-source electronic platform. Arduino Uno was designed to connect the ultrasonic sensor, temperature sensor, and data logger shield for implementing IoT. Arduino IDE (Integrated Development Environment) was selected as the Arduino software and used to develop the intelligent algorithm to measure and calibrate the real-time water level automatically. The intelligent water level monitoring platform consists of water level measurement, temperature calibration, data calibration, stage-discharge relationship, and data logger algorithms. Water level measurement and temperature calibration algorithm corrected the bias inherent in the ultrasonic sensor. Data calibration algorithm analyzed and corrected the outliers during the measurement process. The verification of the intelligent water level measurement algorithm was performed by comparing water levels using the tape and ultrasonic sensor, which was generated by measuring water levels at regular intervals up to the maximum level. The statistics of the slope of the regression line and $R^2$ were 1.00 and 0.99, respectively which were considered acceptable. The error was 0.0575 cm. The verification of data calibration algorithm was performed by analyzing water levels containing all error codes in a time series graph. The intelligent platform developed in this study may contribute to the public IoT service, which is applicable to intelligent flood management under climate change.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.519-522
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• 2006

Accurate modeling of a dynamic system from experimental data is the bases for the model updating or heath monitoring of the system. Modal analysis or modal test is a routine process to get the modal parameters of a dynamic system. The modal parameters include the natural frequencies, damping ratios and mode shapes. This paper presents a new method that can derive the equations of motion for a dynamic system from the modal parameters obtained by the modal analysis or modal test. The present method based on the relation between the eigenvalues and eigenvectors of the state space equation derives the mass, damping and stiffness matrices of the system. The modeling of a cantilevered beam from modal parameters is an example to prove the efficiency and accuracy of the present method. Using the lateral displacements only, not the rotations, gives limited information for the system. The numerical verification up to now gives reasonable results and the verification with the test data is scheduled.

• Journal of Platform Technology
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• v.9 no.1
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• pp.23-31
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• 2021

In recent years, in the domestic industry, personal damage has occurred due to sensor malfunction and the emission of harmful gases. But there is a limit to the reliability verification of sensor data because the evaluation of environmental sensors is focused on durability and risk tests. This platform designed a sensor board that measures 10 major substances and a performance verification system for each sensor. In addition, the data collected by the sensor board was transferred to the server for data reliability evaluation and verification using LoRa communication, and a prototype of the sensor data platform was produced to monitor the transferred data. And the collected data is analyzed and predicted by using machine learning techniques.