• Title/Summary/Keyword: Smoke detection

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A Study on the Early Fire Detection based on Environmental Characteristics inside the Nacelle of Wind Turbine Generator System (풍력발전기 너셀 내부 환경특성을 고려한 화재 조기감지방법 연구)

  • Kim, Da Hee;Lim, Jong Hwan
    • Journal of the Korean Society for Precision Engineering
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    • v.31 no.9
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    • pp.847-854
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    • 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.

Study on fire smoke identification method based on SVM and K fold cross verification fusion algorithm (SVM과 K 접힘 교차 검증 융합 알고리즘 기반의 화재 연기 식별 방법 연구)

  • Wang Yudong;Sangbong Park;Jeonghwa Heo
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.843-847
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    • 2023
  • In this paper, we propose a model for detecting efficient fire identification to prevent fires that can lead to various industrial accidents, farmland and large forest fires, with the widespread use of various chemicals and flammable substances as modern technology advances. This paper presents an algorithm that can detect fire smoke in a high-efficiency and short time using images, and an algorithm based on SVM(Support Vector Machine) and K fold cross-verification technologies. By analyzing images, fire and smoke detection algorithms have relatively superior detection performance compared to existing algorithms, and the analysis of fire and smoke characteristics detected in this paper is analyzed stably and efficiently and is expected to be used in various fields that may be exposed to fire risks in the future.

A Numerical Modeling of Smoke Behavior and Detection for Fire Developed in International Space Station (국제우주정거장 내부 화재시 연기거동 및 감지특성에 관한 수치 모델링)

  • Park, Seul-Hyun;Lee, Joo-Hee;Kim, Youn-Kyu;Hwang, Cheol-Hong
    • Fire Science and Engineering
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    • v.26 no.6
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    • pp.51-56
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    • 2012
  • The onset of fire on the International Space Station (ISS) is a critical problem that can threaten the life of crew members onboard and thus instantaneous fire detection and extinguishment technology has been considered as one of the most important aspects in the ISS operation. In the present study, a numerical analysis was performed to better understanding of the characteristics of smoke behaviors and detection in a pressurized module of the ISS using the NIST Fire Dynamic Simulator (FDS). Numerical results indicate that the smoke flow patterns under zero-gravity condition are clearly different from those under normal gravity condition. In addition, the results obtained from numerical simulations coupled with the PM internal flows are expected to provide basic and useful information in designing the microgravity fire detection devices and establishing in fire response protocol for astronauts or the crew members.

A Fire Detection System Using Fuzzy Logic with Input Variables of Temperature and Smoke Density (열과 연기농도를 입력변수로 갖는 퍼지로직을 이용한 화재감지시스템)

  • Hong Sung-Ho;Kim Doo-Hyun;Kim Sang-Chul
    • Fire Science and Engineering
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    • v.18 no.4
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    • pp.42-51
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    • 2004
  • This paper presents a study on the analysis of fire detection system using fuzzy logic with input variables of temperature and smoke density. The input variables for the fuzzy logic algorithm are measured by fire experiment of small scale with temperature detector and smoke detector. The antecedent part of fuzzy rules consists of temperature and smoke density, and the consequent part consists of fire possibility. Also the triangular fuzzy membership function is chosen for input variables and fuzzy rules to simplify computation. In order to calculate fuzzy values of such fuzzy system, a computer program is developed with Matlab based on graphics user interface. The experiment was conducted with paper and ethanol to simulate flaming fire and with plastic and sawdust to model smoldering fire. The results showed that the fire detection system presented here was able to diagnose fire very precisely. With the help of algorithms using fuzzy logic we could distinguish whether fire or not.

A Study on the Application of Fire Protection Facilities in Large Enclosure Gymnasium (대규모 실내경기장의 소방방재설비 적용현황 분석)

  • Choi, Dong-Ho;Kim, Choon-Dong;Yang, Jeong-Hoon;Cho, Young-Hum
    • Journal of Korean Association for Spatial Structures
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    • v.10 no.2
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    • pp.135-145
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    • 2010
  • The objective of this study is to draw basic data for the application of the fire protection planning for the future plan large enclosure buildings in Korea through an analysis of its characteristics by case studies of the domestic and foreign large scale gymnasiums. In this study, domestic building codes for the fire protection are investigated and fire detection systems, fire extinguishing systems, smoke control systems and evacuation systems of three large scale gymnasiums located at Korea and eight foreign countries are compared and analyzed. The results of this study show that infrared light fire detection system and flame detector for spacial characteristics are potentially used in fire protection systems of large scale gymnasiums: dry type sprinkler and sprinkler water gun are adopted in fire detection system; and smoke accumulation system is widely utilized in smoke control system.

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Sub Oriented Histograms of Local Binary Patterns for Smoke Detection and Texture Classification

  • Yuan, Feiniu;Shi, Jinting;Xia, Xue;Yang, Yong;Fang, Yuming;Wang, Rui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.4
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    • pp.1807-1823
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    • 2016
  • Local Binary Pattern (LBP) and its variants have powerful discriminative capabilities but most of them just consider each LBP code independently. In this paper, we propose sub oriented histograms of LBP for smoke detection and image classification. We first extract LBP codes from an image, compute the gradient of LBP codes, and then calculate sub oriented histograms to capture spatial relations of LBP codes. Since an LBP code is just a label without any numerical meaning, we use Hamming distance to estimate the gradient of LBP codes instead of Euclidean distance. We propose to use two coordinates systems to compute two orientations, which are quantized into discrete bins. For each pair of the two discrete orientations, we generate a sub LBP code map from the original LBP code map, and compute sub oriented histograms for all sub LBP code maps. Finally, all the sub oriented histograms are concatenated together to form a robust feature vector, which is input into SVM for training and classifying. Experiments show that our approach not only has better performance than existing methods in smoke detection, but also has good performance in texture classification.

A Study on the Reliability Analysis for Smoke Detector using Dust (분진을 이용한 연기감지기 신뢰성 분석에 관한 연구)

  • Hong, Sung Ho;Choi, Moon Soo;Lee, Young Man
    • Journal of the Korean Society of Safety
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    • v.28 no.6
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    • pp.11-16
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    • 2013
  • This paper presents a study on the analyzing reliability of smoke fire detector using accelerated life test. In general, the smoke fire detector is broken by dust which flow in smoke detection chamber. In order to conduct accelerated life test of smoke fire detector dust is set accelerated factor in this paper. The dust is fly-ash which is test particle 5th regulated by KS A 0090. The dust accelerated level is 60 g, 180 g and 360 g and failure time is measured by smoke sensitivity testing. It is considered to failure of detector if detector don't operate within 30 secconds when subjected to an air stream having a velocity of 20 cm/s~40 cm/s containing smoke with a concentration of 15% of rate of light-response of 1 m. The goodness of fit test and mean life prediction conduct using the failure time. The result show that life distribution fits the weibull distribution for failure time data and the mean lifes calculate 22.5 year in domestic product and 14.7 years in overseas product applied dust stress only.

Image Segmentation for Fire Prediction using Deep Learning (딥러닝을 이용한 화재 발생 예측 이미지 분할)

  • TaeHoon, Kim;JongJin, Park
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.1
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    • pp.65-70
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    • 2023
  • In this paper, we used a deep learning model to detect and segment flame and smoke in real time from fires. To this end, well known U-NET was used to separate and divide the flame and smoke of the fire using multi-class. As a result of learning using the proposed technique, the values of loss error and accuracy are very good at 0.0486 and 0.97996, respectively. The IOU value used in object detection is also very good at 0.849. As a result of predicting fire images that were not used for learning using the learned model, the flame and smoke of fire are well detected and segmented, and smoke color were well distinguished. Proposed method can be used to build fire prediction and detection system.

New Scheme for Smoker Detection (흡연자 검출을 위한 새로운 방법)

  • Lee, Jong-seok;Lee, Hyun-jae;Lee, Dong-kyu;Oh, Seoung-jun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.9
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    • pp.1120-1131
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    • 2016
  • In this paper, we propose a smoker recognition algorithm, detecting smokers in a video sequence in order to prevent fire accidents. We use description-based method in hierarchical approaches to recognize smoker's activity, the algorithm consists of background subtraction, object detection, event search, event judgement. Background subtraction generates slow-motion and fast-motion foreground image from input image using Gaussian mixture model with two different learning-rate. Then, it extracts object locations in the slow-motion image using chain-rule based contour detection. For each object, face is detected by using Haar-like feature and smoke is detected by reflecting frequency and direction of smoke in fast-motion foreground. Hand movements are detected by motion estimation. The algorithm examines the features in a certain interval and infers that whether the object is a smoker. It robustly can detect a smoker among different objects while achieving real-time performance.

Development of the Low Power Stand-Alone Smoke and Heat Detector for the Reliability Improvement (신뢰성 개선을 위한 저전력 열연 복합식 단독경보형 감지기 개발)

  • Jee, Seung-Wook;Kim, Si-Kuk;Lee, Jae-Jin;Kim, Pil-Young;Lee, Chun-Ha
    • Fire Science and Engineering
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    • v.26 no.1
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    • pp.74-79
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    • 2012
  • This study is described for development of the stand-alone smoke and heat detector (SASHD) according to the revised in 2011 type approval and performance inspection code for detector. The main improvement of the revised regulation is source. CMOS microcontroller with nano watt technology is use for development of the workable SASHD over 10 years. The low-power SASHD is developed by using the power-saving sleep mode of microcontroller, by making the low-power source voltage checker, heat detector and smoke detector. The stand-alone detector is developed by smoke and heat detector type for reduce false fire alarm. User can choose type of work between the heat detection mode and smoke & heat detection mode. The SASHD can communicate with each them using RS-485 communication supported from microcontroller. So, this study can develop the SASHD that is able to alarm more wide area when fire occurs and reduce a flash fire alarm.