• The KIPS Transactions:PartB
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• v.16B no.6
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• pp.463-470
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• 2009

In this paper, we propose the advanced fire-flame detection algorithm using camera image for better performance than previous sensors-based systems which is limited on small area. Also, previous works using camera image were depend on a lot of heuristic thresholds or required an additional computation time. To solve these problems, we use statistical values and divide image into blocks to reduce the processing time. First, from the captured image, candidate flame regions are detected by a background model and fire colored models of the fire-flame. After the probability models are formed using the change of luminance, wavelet transform and the change of motion on time axis, they are used for membership function of fuzzy logic. Finally, the result function is made by the defuzzification, and the probability value of fire-flame is estimated. The proposed system has shown better performance when it compared to Toreyin's method which perform well among existing algorithms.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.9
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• pp.977-982
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• 2014

In this paper, we propose a system which can detect the flame in real time from the high-quality IP camera. First, open directly the RTSP streams transmitted from the IP camera using the library FFmpeg as opening a video file. The second thing is to extract the background images from video signal using Gaussian mixture model. Then the foreground images are obtained through subtracting operation between the input image and the background image. Separated foreground image through a mathematical morphology operation are considered as candidate area. By analysing colour information and dynamic characteristics of the candidate area, flame is determined finally. Through the experiments with input videos from IP camera, the proposed algorithms were useful to detect flames.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1301-1314
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• 2018

In this paper, we present a low-cost fire detection system using a thermal camera and a smartphone. The developed system collects thermal and RGB videos from the developed camera. To detect fire, candidate fire regions are extracted from videos obtained using a thermal camera. The block mean of variation of adjacent frames is measured to analyze the dynamic characteristics of the candidate fire regions. After analyzing the dynamic characteristics of regions of interest, a fire is determined by the candidate fire regions. In order to evaluate the performance of our system, we compared with a smoke detector, a heat detector, and a flame detector. In the experiments, our fire detection system showed the excellent performance in detecting fire with an overall accuracy rate of 97.8 %.

• Journal of Internet Computing and Services
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• v.14 no.2
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• pp.45-51
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• 2013

In this paper, the combination of ultraviolet and infrared sensors based design for flame signal detection algorithms was proposed with the application of light-wavelength from burning. And, the performance result of image detection was compared by an ultraviolet sensor, an infrared sensor, and the proposed dual-mode sensors(combination of ultraviolet and infrared sensors).

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.4
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• pp.476-481
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• 2019

Early detection of fire is an important measure for minimizing the loss of life and property damage. However, fire and smoke need to be simultaneously detected. In this context, numerous studies have been conducted on image-based fire detection. Conventional fire detection methods are compute-intensive and comprise several algorithms for extracting the flame and smoke characteristics. Hence, deep learning algorithms and convolution neural networks can be alternatively employed for fire detection. In this study, recorded image data of fire in a ship engine room were analyzed. The flame and smoke characteristics were extracted from the outer box, and the YOLO (You Only Look Once) convolutional neural network algorithm was subsequently employed for learning and testing. Experimental results were evaluated with respect to three attributes, namely detection rate, error rate, and accuracy. The respective values of detection rate, error rate, and accuracy are found to be 0.994, 0.011, and 0.998 for the flame, 0.978, 0.021, and 0.978 for the smoke, and the calculation time is found to be 0.009 s.

• Journal of Advanced Marine Engineering and Technology
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• v.10 no.3
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• pp.107-118
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• 1986

The presenet research attempts to examine the combustion characteristics and the structure of the flame in turbulent premixed flames and thus enhance the combustion performance that leads to the design of the effective combustion system (untilizing LNG). Following experimental investigations for several stabilized premixed flames were attempted to identify the interactive mechanism between flame structures and flow fields; Visualization by Schlieren method, measurement of flow velocity by LDV, detection of ion current by ion probe, measurement of fluctuating temperature by thermocouple having compensation circuit, average values with respect to time of fluctuating amount for flow velocity, temperature, ion current, etc., variable RMS values, PDFs, autocorrelation, crosscorrelation, spatial macroscale, power spectra, and velocity scale. Continuing the authors published studies whose flame dominated by coherent structures and the characteristics of combustion reaction for irregular three dimensional flame and stabilized flame by step were investigated with obtained experimental quantities. Results of this research are following : The most turbulent flames support the structure of a Wrinkled laminar flame or laminar flamelets. It also observed that combustion reaction is related to small tubulence microscales of the turbulent flow fields closly.

• Structural Engineering and Mechanics
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• v.70 no.6
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• pp.649-659
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• 2019

Vibration-based structural damage detection through optimization algorithms and minimization of objective function has recently become an interesting research topic. Application of various objective functions as well as optimization algorithms may affect damage diagnosis quality. This paper proposes a new damage identification method using Moth-Flame Optimization (MFO). MFO is a nature-inspired algorithm based on moth's ability to navigate in dark. Objective function consists of a term with modal assurance criterion flexibility and natural frequency. To show the performance of the said method, two numerical examples including truss and shear frame have been studied. Furthermore, Los Alamos National Laboratory test structure was used for validation purposes. Finite element model for both experimental and numerical examples was created by MATLAB software to extract modal properties of the structure. Mode shapes and natural frequencies were contaminated with noise in above mentioned numerical examples. In the meantime, one of the classical optimization algorithms called particle swarm optimization was compared with MFO. In short, results obtained from numerical and experimental examples showed that the presented method is efficient in damage identification.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.6
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• pp.769-776
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• 2000

Visible spectral characteristics of cross-sectional emissions from a partially premixed methane/air and propane/air flames have been investigated. An optical train with a two-axis scanning mirror system was used to record line-of-sight emission spectra from 354nm to 618nm, and inversion technique was adapted to obtain cross-sectional emission spectra. By analyzing the reconstructed emission spectra, cross-sectional intensities of CH and $C_2$ radicals were separated from the background emissions. The blue flame edge and yellow flame edge were also obtained by image processing technique for edge detection with color photograph of flame. These edges were compared with radial distributions of CH, $C_2$ radicals and background emissions. The CH radicals were observed at blue flame edge. The background emissions were generated by soot precursor at upstream of flame and by soot at downstream of flame. The $C_2$ radicals in propane/air flame were observed more than those in methane/air flame.

• Journal of the Korean Society of Safety
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• v.32 no.2
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• pp.38-45
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• 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.

• Journal of Mechanical Science and Technology
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• v.19 no.12
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• pp.2197-2204
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• 2005

The combination of Gas chromatography (GC) for separation and Flame Ionization Detection (FID) for detection and identification of the components of a mixture of compounds is a fast and strongly proved method of analytic chemistry. The objective of this research was to design a combined High-speed miniature screening Gas chromatograph along with a Flame Ionization Detector for quick, quantitative and qualitative analysis of gas components. This combined GC-FID system is suitable to detect the volatile and semi-volatile hydrocarbons present in a gas mixture. The construction made it less expensive, easy to use and movable. The complete gas path was developed. On/off valves, temperature and flow sensors and their interface electronics were used for controlling purpose. A Microcontroller was programmed to measure the temperature and gas flow using the sensors and to control and regulate them using the electronics and valves. A pocket PC with its touch screen served as a user interface for the system. Software was developed for the pocket PC, which makes the communication possible with the Microcontroller. The system parameters can be indicated in the Pocket PC as simple text and also the analysis result can be displayed.