• 반도체디스플레이기술학회지
• /
• 제23권1호
• /
• pp.110-116
• /
• 2024

Despite the continuous advancement of science and technology, fire accidents continue to occur without decreasing over time, so there is a constant need for a system that can accurately detect fires at an early stage. However, because most existing fire detection systems detect fire in the early stage of combustion when smoke is generated, rapid fire prevention actions may be delayed. Therefore we propose an early fire detection system that can perform early fire detection at a reasonable cost using LSTM, a deep learning model based on multi-gas sensors with high selectivity in the early stage of decomposition rather than the smoke generation stage. This system combines multiple gas sensors to achieve faster detection speeds than traditional sensors. In addition, through window sliding techniques and model light-weighting, the false alarm rate is low while maintaining the same high accuracy as existing deep learning. This shows that the proposed fire early detection system is a meaningful research in the disaster and engineering fields.

• 한국콘텐츠학회논문지
• /
• 제9권12호
• /
• pp.504-514
• /
• 2009

최근 문화재나 시설물 관리를 위한 화재 감시 응용 시스템에 대한 요구가 증대되고 있다. 이러한 화재 감시 시스템은 화재 상황을 대처할 수 있도록 지원함으로써 피해규모를 축소시킬 수 있다. 그러나 기존 시스템은 일정 주기로 화재 감시를 수행함으로써 화재 판단을 지연시키는 단점이 존재한다. 또한 감시 상황을 확인 할 수 있는 사용자 인터페이스를 제공하지 않는다. 따라서 이러한 두 가지 문제점을 해결하기 위하여 첫째, 조기 위험상황 경보를 위해 새로운 화재 판단 알고리즘(Early Fire Detection Algorithm)을 제안한다. 이는 데이터 분포를 기반으로 하여 화재 판단 시작 주기를 동적으로 설정하기 때문에, 화재 판단 시간 측면에서 기존 알고리즘 보다 우수하다. 둘째, 제안하는 화재 판단 알고리즘을 통하여 사용자 인터페이스를 제공하는 화재 감시 응용 시스템을 개발한다. 마지막으로 성능 실험을 통해, 개발된 시스템이 다양한 화재 상황에서 조기 위험상황 경보를 위해 활용될 수 있음을 보인다.

• 한국안전학회지
• /
• 제32권2호
• /
• pp.38-45
• /
• 2017

This paper is an experimental study to find an optimal detection method for detecting fire early in a rack-type warehouse stored with goods. In this study, we constructed rack-type structure with the fourth floor of 13.5 m high and conducted fire experiments which were to measure flow of heat/smoke in rack-type structure and response time of fire detectors. The detectors used at experiments were fixed temperature type detectors, rate of rise detectors, photoelectric smoke detectors, air sampling smoke detectors and flame detectors. The used ignition sources are n-heptane fire for response of heat detection and cotton fire for response of smoke detection. The fixed temperature type detectors, rate of rise detectors and photoelectric detectors were installed to every rack level respectively. The results show that the rate of rise detector should be installed every 2 levels and photoelectric smoke detector should be installed every 4 levels for the early stage fire detection. Air sampling smoke detectors can detect fire early in response to control of sensitivity, but there is a problem in false alarm. The fixed temperature detector is not suitable for early stage fire detection in warehouse and flame detector not worked if flame is not visible, so it need to install combination with other detector.

• 한국정밀공학회지
• /
• 제31권9호
• /
• pp.847-854
• /
• 2014

The paper presented a method of early fire detection based on the environmental characteristics inside the nacelle of wind turbine generator system(WTGS). The rising rates of the temperature and smoke density were used as the parameters for early fire detection. By considering the characteristics of temperature and smoke density of a nacelle, this method is very reliable and can minimize the possibility of a malfunction of fire detection. The performance of the method was tested through sets of experiments by using nacelle simulator.

• 한국화재소방학회:학술대회논문집
• /
• 한국화재소방학회 2008년도 춘계학술논문발표회 논문집
• /
• pp.135-138
• /
• 2008

Many Victims and property damage are caused in fires. In this paper, an flame detection algorithm is proposed to early alarm fires. The proposed flame detection algorithm is based on 2-stage decision strategy of video processing. The first decision is to check with color distribution of input vidoe. In the second, the candidated region is settled as fire region with activity. As a result of simulation, it is shown that the proposed algorithm is useful for fire recognition.

• 한국화재소방학회논문지
• /
• 제33권5호
• /
• pp.55-60
• /
• 2019

랙크식 창고에서 화재가 발생되는 경우 건물이 전소되거나 붕괴되는 상태까지 발생된다. 이러한 현상이 발생되는 이유는 랙크식 창고가 층고가 높고, 물품을 수직으로 적재하고 있어 화재 시 천장에 설치되어 있는 감지기에 의한 조기감지가 어렵고, 그로 인하여 초기에 소화하지 못하기 때문이다. 본 연구에서는 수치해석 프로그램인 Fire dynamic simulator (FDS)를 이용하여 랙크식 창고 내에서 화재 시 발생되는 열과 연기의 유동을 분석하였다. 이러한 분석을 통하여 랙크식 창고 내에서 조기 화재감지를 위한 화재감지기의 최적 설치조건을 확인하였다. 그 결과 랙크식 창고에서 조기 화재감지를 위하여 열과 연기의 복합적인 감지가 필요하며, 복합형 감지기를 랙크의 3 level 마다 설치해야 하며, 정온식 감지기는 랙크식 창고에 적합하지 않은 것을 알 수 있었다.

• 대한기계학회논문집B
• /
• 제39권12호
• /
• pp.935-943
• /
• 2015

본 논문에서는 풍력발전기 나셀 내부의 화재 조기감지 및 화재발생위치를 판단하는 방법을 제안한다. 화재감지 변수로는 온도와 공기 혼탁도 상승률을 이용하는데, 이것은 온도와 혼탁도의 절대 값과 상관이 없이 화재를 감지할 수 있기 때문에 비화재보를 최소화 할 수 있는 방법이다. 화재발생위치는 다수의 화재감지 센서들의 거리에 따른 화재감지 시간차를 이용하였다. 또한 다양한 실험을 통하여 개발된 방법의 성능을 테스트하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제8권10호
• /
• pp.3475-3489
• /
• 2014

Here we present a simple flame detection method for an infrared (IR) thermal camera based real-time fire surveillance digital signal processor (DSP) system. Infrared thermal cameras are especially advantageous for unattended fire surveillance. All-weather monitoring is possible, regardless of illumination and climate conditions, and the data quantity to be processed is one-third that of color videos. Conventional IR camera-based fire detection methods used mainly pixel-based temporal correlation functions. In the temporal correlation function-based methods, temporal changes in pixel intensity generated by the irregular motion and spreading of the flame pixels are measured using correlation functions. The correlation values of non-flame regions are uniform, but the flame regions have irregular temporal correlation values. To satisfy the requirement of early detection, all fire detection techniques should be practically applied within a very short period of time. The conventional pixel-based correlation function is computationally intensive. In this paper, we propose an IR camera-based simple flame detection algorithm optimized with a compact embedded DSP system to achieve early detection. To reduce the computational load, block-based calculations are used to select the candidate flame region and measure the temporal motion of flames. These functions are used together to obtain the early flame detection algorithm. The proposed simple algorithm was tested to verify the required function and performance in real-time using IR test videos and a real-time DSP system. The findings indicated that the system detected the flames within 5 to 20 seconds, and had a correct flame detection ratio of 100% with an acceptable false detection ratio in video sequence level.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
• /
• pp.1734-1737
• /
• 1997

The conventional fire detection devices are operated after a processed fire phase, which are sensing only a high density of somke level or high temperature heat. They are not so precision to detect a fire in the early phase to protect the facility form the fire. We need to develope a new high precision smoke detection system to keep expensive industrial facilities most reliably form fire. A new optical precision smoke detection system was developed. It monitors very low level density of smoke particles in the air. It is operated continously through many years without a stop or any malfunction. The developed precision smoke detection system will be installed in important industrial facilities, such as power plants, underground common tunnel, main control rooms, computer rooms etc.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2009년도 제40회 하계학술대회
• /
• pp.2164.1_2165.1
• /
• 2009

In this study we suggest fire detection algorithm using fuzzy inference with input variables of temperature and smoke density to detect electrical fire of early stage. The algorithm consists of membership function of temperature and smoke density and fire probability. The antecedent part of the algorithm consists of temperature and smoke density, and the consequent part consists of fire possibility. The inference rules of the algorithm is estimated to input temperature and smoke density obtained by real fire. With the help of algorithms using fuzzy inference we may be diagnose electrical fire precisely.