• 문화기술의 융합
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• 제8권2호
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• pp.355-360
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• 2022

본 연구에서는 마이크로 데이터 센터의 환경 모니터링 시스템(EMS)을 설계하고 개발하는 방법을 나타낸다. 설계하는 환경 모니터링 시스템은 IoT 센서 및 싱글보드 컴퓨터를 이용하여 데이터센터 운영환경을 실시간으로 감지하여 데이터를 해석하고 운영환경을 모니터한다. 먼저, EMS 하드웨어 플랫폼 및 IoT 센싱 패키지 설계 방법에 대하여 나타낸다. 또한 서로 다른 프로토콜을 갖는 IoT 센서에 대한 데이터 수집 SW을 설계하고 원격에서 모니터링이 가능한 EMS 모니터링 SW를 개발한다. 데이터 수집 SW는 센서 수집 모듈과 수집 메니저 모듈로 구성된다. EMS 소프트웨어는 마이크로 서비스 아키텍츠(MSA) 개념을 적용하여 설계하며 각각의 서비스는 독립적인 비즈니스 로직을 포함한다.

• Smart Structures and Systems
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• 제10권3호
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• pp.209-228
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• 2012

Structural health monitoring with wireless sensor networks has received much attention in recent years due to the ease of sensor installation and low deployment and maintenance costs. However, sensor network technology needs to solve numerous challenges in order to substitute conventional systems: large amounts of data, remote configuration of measurement parameters, on-site calibration of sensors and robust networking functionality for long-term deployments. We present a structural health monitoring network that addresses these challenges and is used in several deployments for monitoring of bridges and buildings. Our system supports a diverse set of sensors, a library of highly optimized processing algorithms and a lightweight solution to support a wide range of network runtime configurations. This allows flexible partitioning of the application between the sensor network and the backend software. We present an analysis of this partitioning and evaluate the performance of our system in three experimental network deployments on civil structures.

• Smart Structures and Systems
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• 제5권4호
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• pp.469-482
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• 2009

The emerging sensor-based structural health monitoring (SHM) technology has a potential for cost-effective maintenance of aging civil infrastructure systems. The author proposes to integrate continuous and global monitoring using on-structure sensors with targeted local non-destructive evaluation (NDE). Significant technical challenges arise, however, from the lack of cost-effective sensors for monitoring spatially large structures, as well as reliable methods for interpreting sensor data into structural health conditions. This paper reviews recent efforts and advances made in addressing these challenges, with example sensor hardware and health monitoring software developed in the author's research center. The hardware includes a novel fiber optic accelerometer, a vision-based displacement sensor, a distributed strain sensor, and a microwave imaging NDE device. The health monitoring software includes a number of system identification methods such as the neural networks, extended Kalman filter, and nonlinear damping identificaiton based on structural dynamic response measurement. These methods have been experimentally validated through seismic shaking table tests of a realistic bridge model and tested in a number of instrumented bridges and buildings.

• 설비공학논문집
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• 제29권6호
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• pp.306-315
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• 2017

This study introduces a software for real-time assessment of combustion stability for utility gas turbines. The software was written with LabView, and implemented the time-domain kurtosis as a parameter to proactively access the instantaneous combustion stability during operation of the industrial gas turbine. The simple time-domain assessment algorithm incorporated in the software is advantageous over conventional frequency-domain signal processing of dynamic pressure signal since it reduces the computational cost, thereby making the algorithm more appropriate for real-time monitoring of combustion stability. Benchmark data obtained from a model gas turbine combustor were used for the reproducibility test of the software. The assessment obtained from the software agreed well with previously published results, indicating that incorporation of the software could enhance the performance of systems monitoring the combustion stability for gas turbines during power generation.

• 한국멀티미디어학회논문지
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• 제24권7호
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• pp.890-902
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• 2021

Although the object detection accuracy with still images has been significantly improved with the advance of deep learning techniques, the object detection problem with video data remains as a challenging problem due to the real-time requirement and accuracy drop with occlusion. In this research, we propose a method in pig detection for video monitoring environment. First, we determine a motion, from a video data obtained from a tilted-down-view camera, based on the average size of each pig at each location with the training data, and extract key frames based on the motion information. For each key frame, we then apply YOLO, which is known to have a superior trade-off between accuracy and execution speed among many deep learning-based object detectors, in order to get pig's bounding boxes. Finally, we merge the bounding boxes between consecutive key frames in order to reduce false positive and negative cases. Based on the experiment results with a video data set obtained from a pig farm, we confirmed that the pigs could be detected with an accuracy of 97% at a processing speed of 37fps.

• 한국컴퓨터정보학회논문지
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• 제15권4호
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• pp.99-106
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• 2010

본 논문에서는 MFC(Mass Flow Controller) 유닛으로부터 전송된 유체의 압력을 모니터하고 흐름 제어 기능을 수행하는 유체 유동 모니터링 시스템을 제안한다. 이 시스템은 MFC 유닛과 채널 디바이스, 모니터 및 관리 소프트웨어로 구성된다. MFC 유닛은 유체 압력 값을 측정하여 채널 디바이스로 전송하고, 채널 디바이스는 MFC 유닛과 모니터 및 관리 소프트웨어간의 입출력 인터페이스를 제공하는 기능을 한다. 모니터 및 관리 소프트웨어는 각 채널의 MFC 유닛에서 실시간으로 측정한 유체 압력 값을 모니터링하여 분석하고 제어한다. 이 소프트웨어는 20개의 채널과 0.1의 모니터링 주기로 구성하여 1초당 200개 즉, 1시간당 72만개의 데이터를 처리한다. 이때 입력 데이터 수의 증가에 따라 저장 공간도 비례하여 증가한다. 이러한 데이터 수의 증가와 저장 공간의 증가는 데이터 조회 성능을 저하시키기 때문에 데이터를 효율적으로 관리할 수 있는 변경값 감지 기법과 변경 범위 감지 기법으로 구현한다.

• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.216-224
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• 2017

Abnormal situation caused by aggressive behavior of pigs adversely affects the growth of pigs, and comes with an economic loss in intensive pigsties. Therefore, IT-based video surveillance system is needed to monitor the abnormal situations in pigsty continuously in order to minimize the economic demage. Recently, some advances have been made in pig monitoring; however, detecting each pig is still challenging problem. In this paper, we propose a new color image-based monitoring system for the detection of the individual pig using a fast region-based convolution neural network with consideration of detecting touching pigs in a crowed pigsty. The experimental results with the color images obtained from a pig farm located in Sejong city illustrate the efficiency of the proposed method.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2005년도 춘계학술대회
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• pp.453-459
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• 2005

On this research, we show some concrete examples as software design, 2D/3D display, graph display, and gage display to develop a data monitoring system for real time safe fire testing. Developed software which is simulation software for live fire testing, has been designed to display informations about whole test status in a live fire testing, and with this, user can control a live fire testing under the safe environment. Beside, we increase a security by using a authority of user to access on this software. and we develop it based on module designed to apply a requirement of user later on.

• 대한안전경영과학회지
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• 제7권2호
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• pp.65-72
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• 2005

On this research, we show some concrete examples as software design, 2D/3D display, graph display, and gage display to develop a data monitoring system for real time safe fire testing. Developed software which is simulation software for live fire testing, has been designed to display informations about whole test status in a live fire testing, and with this, user can control a live fire testing under the safe environment. Beside, we increase a security by using a authority of user to access on this software. and we develop it based on module designed to apply a requirement of user later on.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 추계학술대회논문집
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• pp.602-607
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• 2003

Sensors based bridge monitoring system (SBBMS) is designed to perform real-time monitoring and to store the performance history of in-service bridges. In general, visual inspections play a major role in maintenance of in-service bridges; however, they are not adequate to document the behavior of a bridge. Therefore, visual inspections and sensor based monitoring systems complement each other. Sensor based bridge monitoring systems consist of hardware and software systems. The hardware system contains the sensors and data-loggers to measure the behavior of a structure, the communicational equipment to transmit the measured data from the site to the monitoring center, and the computers to arrange and analyze the data. The software system controls data-loggers, arranges and analyzes the measured data, makes real-time display, stores the performance history.