• Title/Summary/Keyword: 화재 검출 시스템

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Implementation of Intelligent Fire-Detection Systems Using DSP (DSP를 이용한 지능형 화재검출시스템 구현)

  • Kim, Hyun-tae;Song, Chong-kwan;Park, Jang-sik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.05a
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    • pp.411-414
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    • 2009
  • Many victims and property damages are caused in fires every year. In this paper, intelligent fire-detection systems with embedded fire-detection algorithms for early fire detection and alarm is proposed to reduce fire damages by using image processing technique, high speed digital signal processor(DSP) technique, and information technique. The fire detection algorithms used for the proposed systems consist of flame and smoke detection algorithms. If flame or smoke is detected respectively, the corresponding alarm signal can be transferred to management computer. And if flame and smoke is detected simultaneously, the fire alarm signal shall be generated. Through several experiments in the physical environment, it is shown that the proposed system works well without malfunction.

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Design of Fire Detection System Based on Sensor Network (센서 네트워크 기반 화재 감지 시스템 설계)

  • Yuk, Ui-Su;Kim, Seong-Ho
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2006.11a
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    • pp.378-382
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    • 2006
  • 현재 주로 사용되고 있는 화재 감지 장치들은 경고 기반으로 되어 있어 정확한 화재 발생의 위치 검색이 어려우며 장치의 고장이 발생한 경우 고장 유/무의 확인이 어려워 보다 큰 인명 피해 및 재산 피해를 가져올 수 있다. 센서 네트워크 시스템은 통신매체 없이 데이터 송/수신이 가능하며 이를 통한 모니터링 환경의 구축이 쉬워 위치검색 및 고장 검출 알고리즘의 적용이 간단하다. 본 논문에서는 WSN 기반의 화재 감지 시스템을 제안하며 오류검출 알고리즘인 Consensus 알고리즘을 적용하여 그 유용성을 확인하고자 한다.

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Learning algorithm for flame pattern recognition (화재 패턴 인식을 위한 학습 알고리즘)

  • Kang, Suk Won;Lee, Soon Yi;Lee, Tae Ho
    • Proceedings of the Korea Contents Association Conference
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    • 2009.05a
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    • pp.521-525
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    • 2009
  • In this paper, we introduce fire detection system and software learning algorithm that recognize fire patterns. Flame patterns means that periodical and consistent pattern about general conception of fire, and to process it with the definition. Learning algorithm for flame pattern recognition that we propose is the method which is faster and more exactly than existing algorithm. Also, we trying to elicit the method through experiment result and by applying it, we show the validity of an early fire warning system.

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The Implementation of the system-on-board controllable the electrical fires due to ground fault, arc fault and overload (누전, 아크, 과부하에 의한 전기화재 제어 시스템 보드의 구현)

  • Kim, Byung-Cheul;Chun, Joong-Chang
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.2
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    • pp.419-424
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    • 2011
  • The system-on-board detectable and controllable the electrical fires due to ground fault(GF), arc fault and overload is implemented. The system IC for controlling and preventing the electrical fires is available to this system. The GF detection circuit for detecting the electrical leakage current, the arc fault detection circuit and the overload detection circuit controllable the input voltage for flowing the overload current are designed. The GF detection circuit and the arc fault detection circuit are good operated to the electrical leakage current and the arc signal, respectively. It is confirmed that the overload detection circuit has shown no erratic operation with the noise or the load variation and is only operated at the overload condition.

Video-based Intelligent Unmanned Fire Surveillance System (영상기반 지능형 무인 화재감시 시스템)

  • Jeon, Hyoung-Seok;Yeom, Dong-Hae;Joo, Young-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.4
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    • pp.516-521
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    • 2010
  • In this paper, we propose a video-based intelligent unmanned fire surveillance system using fuzzy color models. In general, to detect heat or smoke, a separate device is required for a fire surveillance system, this system, however, can be implemented by using widely used CCTV, which does not need separate devices and extra cost. The systems called video-based fire surveillance systems use mainly a method extracting smoke or flame from an input image only. The smoke is difficult to extract at night because of its gray-scale color, and the flame color depends on the temperature, the inflammable, the size of flame, etc, which makes it hard to extract the flame region from the input image. This paper deals with a intelligent fire surveillance system which is robust against the variation of the flame color, especially at night. The proposed system extracts the moving object from the input image, makes a decision whether the object is the flame or not by means of the color obtained by fuzzy color model and the shape obtained by histogram, and issues a fire alarm when the flame is spread. Finally, we verify the efficiency of the proposed system through the experiment of the controlled real fire.

A Development of Arc Detecting Device for 3 Phase Induction Motor (3상 유도전동기를 위한 Arc 검출 장치 개발)

  • Joo, Nam-Kyu;Shin, Bong-Il;Ban, Gi-Jong
    • Proceedings of the KIEE Conference
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    • 2007.04b
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    • pp.160-161
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    • 2007
  • 아크고장은 전기배선에서 다양한 형태로 발생하는 현상으로 전기화재의 주 원인으로 분석되고 있다. 현재까지는 단상 전원에서의 아크고장에 대해서만 연구가 진행되고 있으나 3상 전원 환경에서도 다양하게 발생하는 아크고장현상에 의한 전기화재를 방지할 필요가 있다. 따라서, 3상 전원에서 아크고장을 검출할 수 있는 장치의 필요성이 요구되어지고 있다. 본 논문에서는 3상 전원을 갖는 시스템에서 아크고장을 검출하여 전기 화재를 방지할 수 있는 시스템을 설계하였다.

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Color and Motion-based Fire Detection in Video Sequences (비디오 영상에서 컬러와 움직임 기반의 화재 검출)

  • Kim, Alla;Kim, Yoon-Ho
    • Journal of Advanced Navigation Technology
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    • v.15 no.3
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    • pp.471-477
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    • 2011
  • A wide distribution of CCTV cameras in many public areas can be used not only for video surveillance systems but also for preserving fire occurrence. A proposed approach is based on visual information through a static camera. Video sequences are analyzed to find fire candidates and then spatial analyses procedure for detected fire-like color foreground is carried out. If spatial and temporal variances changes rapidly and close to fire motion, fire candidate is considered as fire.

Development of Hardware and Software for Detecting of Electrical Fire Signal (전기화재 신호 검출이 가능한 하드웨어 및 소프트웨어 개발)

  • Kim, Sung-Chul;Kim, Doo-Hyun;Park, Jong-Young;Kim, Ho-Young
    • Proceedings of the Korea Institute of Fire Science and Engineering Conference
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    • 2010.04a
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    • pp.510-515
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    • 2010
  • 이 논문은 주택 및 영세사업장의 모의설비 시스템을 구성하여 전기화재원인 분석 및 이상신호 검출이 가능한 하드웨어 개발과 소프트웨어 개발이 주목표이다. 이를 위하여 주택 및 영세사업장 현장실태 조사를 통하여 모의설비 시스템을 구성하고 개발된 하드웨어와 소프트웨어를 정착하여 전압 및 전류에 대한 각각의 정상 및 이상신호를 분석하였다. 본 연구에서 제안한 전기화재 신호 분석용 시스템을 통하여 전기화재 감지장치의 기준값 설정과 전기재해 취약장소에 설치하여 전기화재를 조기에 경보하여 국민의 인적 물적 재산상의 손실을 방지할 수 있을 것으로 판단된다.

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Fire detection system using HSV, YCbCr Combined color information (HSV, YCbCr 컬러 모델의 복합 색상정보룰 이용한 화재 검출 시스템)

  • Jeong, Hee-yoon;Cehio, Kyung-joo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.04a
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    • pp.1010-1012
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    • 2017
  • 본 논문에서는 HSV, YCbCr 컬러 모델의 색상정보를 통한 화재 검출 알고리즘을 제안한다. 첫 번째 단계에서는 영상의 변화를 감지하기 위해서 입력된 영상으로부터 평균배경영상을 계산하여 전경영상을 분리한다. 그리고 차영상을 이용해 움직임을 인식하여 컬러 모델 색상정보를 비교할 영역을 구한다. 전경영상의 구해진 영역에서 컬러모델의 복합 색상정보를 이용하여 화재 영역을 검출한다.

A System IC for Controlling the Fire Prevention (화재방지제어 시스템 IC)

  • Kim, Byung-Cheul
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.4
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    • pp.737-746
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    • 2009
  • In this study, we have developed one chip system IC for preventing the overload, detecting an abnormal conditions, and controlling the fire prevention in the intelligent home appliances. For the purpose, a circuit detectable an electric leak for preventing an electric shock, and a circuit detectable arc that has effect directly on the fire are designed. The circuits designed on every block are verified by comparing simulation with bread-boarding using a standard transistors. The system IC is fabricated by using 34 V 2 metal $1.5{\mu}m$ bipolar transistor process from evaluation results. The electrical performances of IC application circuits and the system IC equipped on PCB board are evaluated. It is confirmed that the system IC is well operated for arc and ground fault(GF) signal.