• Fire Science and Engineering
• /
• v.31 no.4
• /
• pp.111-118
• /
• 2017

The present paper is a study on the risk analysis of complex electrical fire by the partial disconnection and tracking. First, in order to analysis the single cause of electrical fire risk by the partial disconnection, the thermal characteristic has been measured by the change in the number of strands and the rated current of a wire. And then, in order to analysis the electrical fire risk by complex cause, an experiment on the accelerated tracking has been carried out in a condition of partial disconnection and confirmed the fire relation between partial disconnection and tracking. From the experiment, if the partial wire disconnection acts as a single cause, the existing thermal characteristics generated by the flowing current has appeared more clearly by the increase in the flowing current due to the complex action of tracking. Accordingly, the disconnection of strands has appeared by the complex cause due to the drastic temperature increase which was not generated in the single cause. Namely, it has been confirmed that if the partial disconnection and tracking act complexly rather than the risk of electrical fire by the existing partial disconnection, relatively its risk has been increased in large.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.8 no.3
• /
• pp.155-161
• /
• 2013

To reduce the personnel and material loss caused by fire, we propose the automatic fire extinguishing system based on the ignition point tracking using the flame detecter. This automatic fire extinguishing system is composed of the flame detecting system and the fire extinguishing system based on the water cannon. We study the method for the ignition point tracking and the automatic fire extinguishing using the water cannon and the flame detecter. The flame detecting system for the early fire detection and the ignition point tracking has to be satisfied the requirement of the detecting range and the flame detection time. So we study the signal process algorithm for an improvement of the flame detecting system.

• Fire Science and Engineering
• /
• v.9 no.1
• /
• pp.3-9
• /
• 1995

This paper is a study to dectect the tracking owing to deterioration of indoor wiring, and to prevent the electrical fire. After analysing the harmonics of waveshapes in load current and tracking current by FFT, a method of identifying the tracking was developed by using neural network. Fluoscent lamp, witch was mostly used in indoor, was chosen as the load used in this study. When the learning number in neural network was more then 30,000 times, an excellent neural net-work which could correctly identify the tracking was established. Therefore, the result of this study can be utilized as a basic material in various measuring instruments, such as an hotline inslation tester, earth tester in vehicles, and tracking fire alarm device, witch can detect the tracking under the condition of hotline.

• Fire Science and Engineering
• /
• v.29 no.2
• /
• pp.1-7
• /
• 2015

Tracking, which is one of main reasons of the electric fire, progresses gradually, and therefore, the possibility of fire caused by tracking can be predicted by analyzing the stage of its progress. This paper is conducted in order to predict possibility of the electric fire caused by the tracking in the simulated electric equipment with load. Non-inductive resistance is used as the load. The tracking is happened in a Polyvinyl-chloride-sheathed flat cord, which is a part of the simulated electric equipment by means of dropping of electrolyte droplet. In order to predict the possibility of electric fire caused by tracking, we detect the whole current waveforms of the simulated electric equipment. The time-energy analysis and probability distribution are used for analysis of the tracking progress from the whole current waveforms. In accordance with the results is used for input date of Neural networks, the neural networks can be predict possibility of the electric fire in the electric equipment by 4 stages.

• Journal of Korean Institute of Fire Investigation
• /
• v.10 no.1
• /
• pp.37-45
• /
• 2007

In this paper, the possibility of arc tracking, caused by combustion at the circuit breaker, was discussed. The arc tracking, occurred at the source terminals of all the circuit breakers, when we burned electric leakage circuit breakers with 220V applied. We had a same results of the experiment to simulate fire scene, in the circumstance of fire, all of the circuit breakers had arc tracking caused by combustion. Therefore we confirmed that the arc tracking at the source terminal of circuit breaker could be occurred by just combustion in the fire scene, and it was impossible to decide the cause of fire for reason of discriminating arc tracking at the terminals of circuit breaker.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.1
• /
• pp.1-8
• /
• 2022

In this paper, we propose a fire detection system based on CCTV images using an object tracking technology with YOLOv4 model capable of real-time object detection and a DeepSORT algorithm. The fire detection model was learned from 10800 pieces of learning data and verified through 1,000 separate test sets. Subsequently, the fire detection rate in a single image and fire detection maintenance performance in the image were increased by tracking the detected fire area through the DeepSORT algorithm. It is verified that a fire detection rate for one frame in video data or single image could be detected in real time within 0.1 second. In this paper, our AI fire detection system is more stable and faster than the existing fire accident detection system.

• Fire Science and Engineering
• /
• v.23 no.2
• /
• pp.62-66
• /
• 2009

In this study, we study the damage by burning characteristics of insulating material of RCD (Residual Current Device) used in Korea. The insulating materials of RCD manufactured by three manufacturers are used as the sample. We compare and analyze the thermal decomposition characteristics, combustion characteristics and tracking characteristics of samples. The TGA and Mass Loss Calorimeter meeting the requirements for the ISO5660 (Fire tests-Reaction to Fire, part 1) are used for analyzing the thermal decomposition characteristics and combustion characteristics respectively. In addition, the tracking characteristics are analyzed according to standard of KSC IEC 60112 known as the test used for measuring the resistance tracking and comparison tracking indexes. The study results show that the resistance tracking property of insulating material provided by A Company is highest. Also, the test results show that the resistance tracking property of insulating material provided by B Company is lowest. However, the thermal stability of insulating material provided by this company is excellent at high temperature of above $350^{\circ}C$. In addition, the test results show that the thermal stability of insulating material provided by C Company is highest at temperature of below $400^{\circ}C$.

• Fire Science and Engineering
• /
• v.29 no.5
• /
• pp.57-66
• /
• 2015

This thesis is based on a research to investigate the electrical fire risk due to the single and composite cause in a terminal block. This paper analyzed the thermal characteristics depending on the screw torque change and contact resistance change to measure the fire risk due to the poor contact from single cause first. To measure the fire risk due to the composite cause, the acceleration tracking depending on the contact resistance change was experimented to check the correlation of poor contact and tracking to fire. The experiment result showed that the thermal characteristics were clearer as the screw torque in poor contact status and magnitude of contact resistance increased and that the thermal characteristics of terminal block depending on the contact resistance change was more reliable than the thermal characteristics depending on the screw torque change. Moreover, the terminal block poor contact and tracking were correlated in the case of the composite cause, and when two composite causes were interacted, the electrical fire risk was higher than the single cause.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
• /
• 2003.04a
• /
• pp.204-209
• /
• 2003

• International Journal of Advanced Culture Technology
• /
• v.11 no.1
• /
• pp.320-324
• /
• 2023

As urbanization accelerates and facilities that use energy increase, human life and property damage due to fire is increasing. Therefore, a fire monitoring system capable of quickly detecting a fire is required to reduce economic loss and human damage caused by a fire. In this study, we aim to develop an improved artificial intelligence model that can increase the accuracy of low fire alarms by mixing DeepSORT, which has strengths in object tracking, with the YOLOv5s model. In order to develop a fire detection model that is faster and more accurate than the existing artificial intelligence model, DeepSORT, a technology that complements and extends SORT as one of the most widely used frameworks for object tracking and YOLOv5s model, was selected and a mixed model was used and compared with the YOLOv5s model. As the final research result of this paper, the accuracy of YOLOv5s model was 96.3% and the number of frames per second was 30, and the YOLOv5s_DeepSORT mixed model was 0.9% higher in accuracy than YOLOv5s with an accuracy of 97.2% and number of frames per second: 30.