• 전기학회논문지P
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• 제57권2호
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• pp.202-208
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• 2008

Condition monitoring technologies allow achieving this goal by minimizing downtime through the integrated planning and scheduling of repairs indicated by condition monitoring techniques. Thermal runaways induced by conduction problems deteriorate insulating material and cause disruptive dielectric discharges resulting in arcing faults. Therefore, having the ability to directly measure the temperature of the contacts while in service will provide more information to determine the true condition of the equipment. It allows connective measures to be taken to prevent upcoming failure. Continuous temperature monitoring and event recording provides information on the energized equipment's response to normal and emergency conditions. On-line temperature monitoring helps to coordinate equipment specifications and ratings, determine the real limits of the monitored equipment and optimize facility operations. Using wireless technique eliminates any need for special cables and wires with lower installation costs if compared to other types of online condition monitoring equipment. In addition, wireless temperature monitoring works well under difficult conditions in strategically important locations. Wireless technology for on -line condition monitoring of energized equipment is applicable both as stand alone system and with an interface for power quality monitoring system. The paper presents the results of wireless temperature monitoring: of electrical equipment at a power plant.

• International Journal of Advanced Culture Technology
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• 제10권4호
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• pp.569-575
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• 2022

This is a research thesis on the development of a monitoring and diagnosis device that prevents the risk of an accident through monitoring and diagnosis of a modular Main Circuit Breaker (MCB) using Vacuum Interrupter (VI) for Korean high-speed rolling stock. In this paper, a comprehensive MCB monitoring and diagnosis was performed by converging vacuum level diagnosis of interrupter, operating coil monitoring of MCB and environmental temperature/humidity monitoring of modular box. In addition, to develop an algorithm that is expected to have a similar data processing before the actual field test of the MCB monitoring and diagnosis device in 2023, the cluster analysis and factor analysis were performed using the WEKA data mining technique on the big data of Korean railroad transformer, which was previously researched by Tae Hee Evolution with KORAIL.

• 한국산업정보학회논문지
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• 제26권5호
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• pp.69-77
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• 2021

본 논문에서는 기업의 IT시스템에 대한 위협에 대응하고자 하는 기업의 자산을 지켜주는데 매우 중요한 영역인 보안관제 위협정보를 확인하고자 한다. 보안관제는 보안 장비에서 발생한 이벤트, 로그를 중심으로 실시간 분석하여 위협을 판정하고 대응한다. 보안관제 업무에 있어서 우선적으로 위협정보를 평판정보와 분석정보로 구분하여 우선순위를 도출하고자 한다. 평판정보는 Hash, URL, IP, Domain으로 구성하였으며, 분석정보는 E-mail, CMD-Line, CVE, 공격동향정보로 구성하여 분석하였다. 연구결과, 평판정보의 우선순위가 상대적으로 높았으며 위협정보에 대한 정확성과 대응성을 높이는 것에 의의가 있다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.185-189
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• 2006

Time series analysis is a frequently effective method of constructing model and prediction in data processing of deformation monitoring. The monitoring data sample must to be as more as possible and time intervals are equal roughly so as to construct time series model accurately and achieve reliable prediction. But in the project practice of GPS deformation monitoring, the monitoring data sample can't be obtained too much and time intervals are not equal because of being restricted by all kinds of factors, and it contains many variates in the deformation model moreover. It is very important to study the data processing method for small samples and multi-variates time series in GPS deformation monitoring. A new method of establishing small samples and multi-variates deformation model and prediction model are put forward so as to resolve contradiction of small samples and multi-variates encountered in constructing deformation model and improve formerly data processing method of deformation monitoring. Based on the system theory, a deformation body is regarded as a whole organism; a time-dependence linear system model and a time-dependence bilinear system model are established. The dynamic parameters estimation is derived by means of prediction fit and least information distribution criteria. The final example demonstrates the validity and practice of this method.

• 한국정보통신학회논문지
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• 제17권12호
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• pp.2853-2858
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• 2013

본 논문에서는 기상청, 교통관리센터, GPS, 센서 등을 이용하여 화물의 이동 경로, 컨테이너의 화물 보관 상태를 관리하는 지능형 운송 모니터링 시스템인 ITMS(Intelligent Transport Monitoring System)을 제안한다. ITMS는 컨테이너 내부의 온도 및 습도에 대한 정보, 화물 차량의 위치 정보를 ITMS 서버에 전송하는 CIMS(Container Inner Monitoring System), 화물 차량의 위치정보로 도착 예정시간을 산출하여 CIMS에게 전달하는 TMM(Transport Management Module), 수집한 컨테이너의 온도 및 습도 정보를 이용하여 화물의 신선도를 점검하고 관리하는 FMM(Freight Management Module), 그리고 CIMS, TMM, FMM으로부터 전달받은 정보로 컨테이너 하역 장소를 선정하고, 화물에 대한 정보를 RFID 라벨로 출력하여 컨테이너에 부착하는 SMM(Stevedoring Management Module)로 구성된다. 제안하는 ITMS는 CIMS를 이용하여 화물의 상태를 수시로 점검할 뿐만 아니라, RFID 라벨로 빠르게 화물의 정보를 획득하고, 관리하는데 소용되는 시간을 단축할 수 있다.

• Structural Monitoring and Maintenance
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• 제2권4호
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• pp.301-318
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• 2015

This is the story of a bell-tower and its monitoring. The Civic Tower in Portogruaro is a 59 m high masonry bell-tower, originally built in the XIII century, today leaning more than a meter out of plumb. Since 2003, the building inclination has been continuously monitored with an optical inclinometer in an effort to see whether the tilt is still in progress. When the monitoring started, it was thought highly unlikely that the Tower would tilt further. After three years of monitoring and historical investigation, this idea was completely overturned. We show here how the initial view developed to a final awareness via a probabilistic analysis of the information acquired, based on Bayesian logic. We illustrate how the joint use of instrumental monitoring and historical documentation allowed timely recognition of signs of ongoing tilting and accurate calculation not only of the mean inclination trend, but also the credibility of this information.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.190-195
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• 2009

With the growth of information and communication technologies adoption in construction projects, it could be anticipated that more property owners and construction firms will attempt to use electronic gears and gadgets for site monitoring or surveillance purposes. As the construction workers may be the major group of project team members being monitored, from managerial perspectives and for ethical reasons, it is essential to investigate their degree of acceptance on site monitoring systems. Indeed studies on office workplace monitoring suggest that a monitoring system could shape or control the behaviors of employees. With adequate refinements, their research models could be applicable in the construction industry. This paper presents a model for analyzing the antecedences that affect workers' acceptance level on electronic monitoring, and investigating if there is any behavioral change.

• 산업경영시스템학회지
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• 제46권3호
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• pp.275-284
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• 2023

Land monitoring involves systematically understanding changes in land use, leveraging spatial information such as satellite imagery and aerial photographs. Recently, the integration of deep learning technologies, notably object detection and semantic segmentation, into land monitoring has spurred active research. This study developed a web service to facilitate such integrations, allowing users to analyze aerial and drone images using CNN models. The web service architecture comprises AI, WEB/WAS, and DB servers and employs three primary deep learning models: DeepLab V3, YOLO, and Rotated Mask R-CNN. Specifically, YOLO offers rapid detection capabilities, Rotated Mask R-CNN excels in detecting rotated objects, while DeepLab V3 provides pixel-wise image classification. The performance of these models fluctuates depending on the quantity and quality of the training data. Anticipated to be integrated into the LX Corporation's operational network and the Land-XI system, this service is expected to enhance the accuracy and efficiency of land monitoring.

• Smart Structures and Systems
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• 제16권4호
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• pp.607-621
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• 2015

Wireless sensor technology has been opened up numerous opportunities to advanced health and maintenance monitoring of civil infrastructure. Compare to the traditional tactics, it offers a better way of providing relevant information regarding the condition of building structure health at a lower price. Numerous domestic buildings, especially longer-span buildings have a low frequency response and challenging to measure using deployed numbers of sensors. The way the sensor nodes are connected plays an important role in providing the signals with required strengths. Out of many topologies, the dense and sparse topologies wireless sensor network were extensively used in sensor network applications for collecting health information. However, it is still unclear which topology is better for obtaining health information in terms of greatest components, node's size and degree. Theoretical and computational issues arising in the selection of the optimum topology sensor network for estimating coverage area with sensor placement in building structural monitoring are addressed. This work is an attempt to fill this gap in high-rise building structural health monitoring application. The result shows that, the sparse topology sensor network provides better performance compared with the dense topology network and would be a good choice for monitoring high-rise building structural health damage.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2002년도 Proceedings of the International Welding/Joining Conference-Korea
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• pp.595-599
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• 2002

Edge welding of thin sheets is very difficult because of the fit-up problem and small weld area In laser welding, joint fit-up and penetration are critical for sound weld quality, which can be monitored by appropriate methods. Among the various monitoring systems, visual monitoring method is attractive because various kinds of weld pool information can be extracted directly. In this study, a vision sensor was adopted for the weld pool monitoring in pulsed Nd:YAG laser edge welding to monitor whether the penetration is enough and the joint fit-up is within the requirement. Pulsed Nd:YAG laser provides a series of periodic laser pulses, while the shape and brightness of the weld pool change temporally even in one pulse duration. The shutter-triggered and non-interlaced CCD camera was used to acquire a temporally changed weld pool image at the moment representing the weld status well. The information for quality monitoring can be extracted from the monitored weld pool image by an image processing algorithm. Weld pool image contains not only the information about the joint fit-up, but the penetration. The information about the joint fit-up can be extracted from the weld pool shape, and that about a penetration from the brightness. Weld pool parameters that represent the characteristics of the weld pool were selected based on the geometrical appearance and brightness profile. In order to achieve accurate prediction of the weld penetration, which is nonlinear model, neural network with the selected weld pool parameters was applied.