scholarly journals Fire Detection Technology for Turbine-Powered Transportation

1970 ◽  
Author(s):  
T. M. Trumble
Keyword(s):  
High Temperature ◽  
Detection System ◽  
Fire Detection ◽  
Vehicle Design ◽  
Design Phase ◽  
Detection Systems ◽  
Detection Technology ◽  
Operational Envelope

The problems of providing a fire and overheat detection system for turbine-powered vehicles must be solved during the design phase of the vehicle. In order to accomplish this goal the vehicle design engineer must be aware of the basic constraints involved in the application of fire detection technology. This paper presents a condensed method for understanding, designing and evaluating fire and overheat detection systems. Advanced concepts and technologies such as optical redundancy and high temperature ultraviolet sensors are discussed. Performance of fire and overheat detection systems designed using this approach will provide maximum safety for those using the vehicles, as well as those in its operational envelope.

scholarly journals An Early Flame Detection System Based on Image Block Threshold Selection Using Knowledge of Local and Global Feature Analysis

2020 ◽  
Vol 12 (21) ◽  
pp. 8899
Author(s):  
Ting Wei Hsu ◽  
Shreya Pare ◽  
Mahendra Singh Meena ◽  
Deepak Kumar Jain ◽  
Dong Lin Li ◽  
...  
Keyword(s):  
Detection System ◽  
Global Analysis ◽  
Computation Time ◽  
Fire Detection ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Image Block ◽  
Detection Systems ◽  
Spatial Features ◽  
Flame Detection

Fire is one of the mutable hazards that damage properties and destroy forests. Many researchers are involved in early warning systems, which considerably minimize the consequences of fire damage. However, many existing image-based fire detection systems can perform well in a particular field. A general framework is proposed in this paper which works on realistic conditions. This approach filters out image blocks based on thresholds of different temporal and spatial features, starting with dividing the image into blocks and extraction of flames blocks from image foreground and background, and candidates blocks are analyzed to identify local features of color, source immobility, and flame flickering. Each local feature filter resolves different false-positive fire cases. Filtered blocks are further analyzed by global analysis to extract flame texture and flame reflection in surrounding blocks. Sequences of successful detections are buffered by a decision alarm system to reduce errors due to external camera influences. Research algorithms have low computation time. Through a sequence of experiments, the result is consistent with the empirical evidence and shows that the detection rate of the proposed system exceeds previous studies and reduces false alarm rates under various environments.

Fiber Optic Temperature and Gas Concentration Sensor for Mine Goaf Area Inner Detecting

2012 ◽  
Vol 524-527 ◽  
pp. 302-305
Author(s):  
Yu Bin Wei ◽  
Xu You Wang ◽  
Min Xin ◽  
Tong Yu Liu ◽  
Chang Wang
Keyword(s):  
Spontaneous Combustion ◽  
Detection System ◽  
Fire Detection ◽  
Tunable Diode Laser ◽  
Gas Concentration ◽  
Beam Tube ◽  
Sensing Technology ◽  
Detection Technology ◽  
Primary Means ◽  
On Line

Spontaneous combustion in coal goaf area is one of major disasters in coal mines. Detection technology based on signature Gas and Temperature is the primary means of spontaneous combustion forecasting of coal goaf area. A real-time remote fire detection system is proposed based on tunable diode laser absorption spectroscopy technology and FBG temperature sensing technology, to achieve valid detect of gas concentration and temperature. The System include fiber mathen concentration sensor and fiber temperature sensor based FBG. The system achieved remote on-line monitoring of gas concentration and temperature in mine goaf, meet the fire forecast need for Coal goaf area. There are obvious advantages Compared with the existing beam tube monitoring system in coal mine.

scholarly journals Dependable Fire Detection System with Multifunctional Artificial Intelligence Framework

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2025 ◽  
Author(s):  
Jun Hong Park ◽  
Seunggi Lee ◽  
Seongjin Yun ◽  
Hanjin Kim ◽  
Won-Tae Kim
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Transfer ◽  
Detection System ◽  
Smart Cities ◽  
Fire Detection ◽  
Machine Learning Algorithms ◽  
Detection Accuracy ◽  
Detection Systems ◽  
Fire Detection System

A fire detection system requires accurate and fast mechanisms to make the right decision in a fire situation. Since most commercial fire detection systems use a simple sensor, their fire recognition accuracy is deficient because of the limitations of the detection capability of the sensor. Existing proposals, which use rule-based algorithms or image-based machine learning can hardly adapt to the changes in the environment because of their static features. Since the legacy fire detection systems and network services do not guarantee data transfer latency, the required need for promptness is unmet. In this paper, we propose a new fire detection system with a multifunctional artificial intelligence framework and a data transfer delay minimization mechanism for the safety of smart cities. The framework includes a set of multiple machine learning algorithms and an adaptive fuzzy algorithm. In addition, Direct-MQTT based on SDN is introduced to solve the traffic concentration problems of the traditional MQTT. We verify the performance of the proposed system in terms of accuracy and delay time and found a fire detection accuracy of over 95%. The end-to-end delay, which comprises the transfer and decision delays, is reduced by an average of 72%.

Reducing False Alarms in Vision-Based Fire Detection

2017 ◽  
pp. 263-290
Author(s):  
Neethidevan Veerapathiran ◽  
Anand S.
Keyword(s):  
Video Processing ◽  
Detection System ◽  
Chemical Properties ◽  
Fire Detection ◽  
False Alarms ◽  
Video Signals ◽  
Detection Systems ◽  
Physical Sensors ◽  
Single Feature ◽  
Fire Detection System

Computer vision techniques are mainly used now a days to detect the fire. There are also many challenges in trying whether the region detected as fire is actually a fire this is perhaps mainly because the color of fire can range from red yellow to almost white. So fire region cannot be detected only by a single feature and many other features (i.e.) color have to be taken into consideration. Early warning and instantaneous responses are the preventing ideas to avoid losses affecting environment as well as human causalities. Conventional fire detection systems use physical sensors to detect fire. Chemical properties of particles in the air are acquired by sensors and are used by conventional fire detection systems to raise an alarm. However, this can also cause false alarms. In order to reduce false alarms of conventional fire detection systems, system make use of vision based fire detection system. This chapter discuss about the fundamentals of videos, various issues in processing video signals, various algorithms for video processing using vision techniques.

A Forest Fire Detection System

2013 ◽  
pp. 179-190
Author(s):  
Vassileios Tsetsos ◽  
Odysseas Sekkas ◽  
Evagellos Zervas
Keyword(s):  
Forest Fires ◽  
Detection System ◽  
Fire Detection ◽  
Decision Fusion ◽  
Visible Range ◽  
Detection Algorithms ◽  
Integrated Technology ◽  
Detection Systems ◽  
Individual Decisions ◽  
Fusion Scheme

Forest fires cause immeasurable damages to indispensable resources for human survival, destroy the balance of earth ecology, and worst of all they frequently cost human lives. In recent years, early fire detection systems have emerged to provide monitoring and prevention of the disasterous forest fires. Among them, the Meleager1 system aims to offer one of the most advanced and integrated technology solutions for fire protection worldwide by integrating several innovative features. This chapter outlines one of the major components of the Meleager system, that is the visual fire detection sybsystem. Groundbased visible range PTZ cameras monitor the area of interest, and a low level decision fusion scheme is used to combine individual decisions of numerous fire detection algorithms. Personalized alerts and induced feedback is used to adapt the detection process and improve the overall system performance.

Oil and Gas Offshore Pipeline Leak Detection System: A Feasibility Study

2014 ◽  
Vol 699 ◽  
pp. 891-896 ◽  
Author(s):  
Mohamad Fani Sulaima ◽  
F. Abdullah ◽  
Wan Mohd Bukhari ◽  
Fara Ashikin Ali ◽  
M.N.M. Nasir ◽  
...  
Keyword(s):  
Evaluation Method ◽  
Oil And Gas ◽  
Detection System ◽  
Leak Detection ◽  
Inspection Time ◽  
Related Data ◽  
Detection Systems ◽  
System A ◽  
Detection Technology ◽  
Offshore Pipeline

Pipelines leaks normally begin at poor joints, corrosions and cracks, and slowly progress to a major leakage. Accidents, terror, sabotage, or theft are some of human factor of pipeline leak. The primary purpose of Pipeline leak detection systems (PLDS) is to assist pipeline operators in detecting and locating leaks earlier. PLDS systems provide an alarm and display other related data to the pipeline operators for their decision-making. It is also beneficial because PLDS can enhance their productivity by reduced downtime and inspection time. PLDS can be divided into internally based or computational modeling PLDS Systems and external hardware based PLDS. The purpose of this paper is to study the various types of leak detection systems based on internally systemtodefine a set of key criteria for evaluating the characteristics of this system and provide an evaluation method of leak detection technology as a guideline of choosing the appropriate system.

Spectral Spatio-Temporal Fire Model for Video Fire Detection

2018 ◽  
Vol 32 (05) ◽  
pp. 1850013 ◽  
Author(s):  
Zhaohui Wu ◽  
Tao Song ◽  
Xiaobo Wu ◽  
Xuqiang Shao ◽  
Yan Liu
Keyword(s):  
Color Space ◽  
Fire Detection ◽  
Svm Classifier ◽  
False Alarms ◽  
Surveillance Video ◽  
Detection Systems ◽  
Main Challenge ◽  
Detection Technology ◽  
Spatio Temporal ◽  
Candidate Regions

Fire detection technology aroused people’s attention increasingly. The main challenge of the fire detection systems is how to reduce false alarms caused by objects like fire’s colors. Most existing algorithms used only features of fire in visual field. In this work, we put forward a new algorithm to detect dynamic fire from the surveillance video based on the combination of radiation domain features model. First, a fire color model is used to extract flame-like pixels as candidate areas in YCbCr space. Second, we convert the candidate regions from the traditional color space into radiation domain in advance by camera calibration. And we use seven features to model the spectral spatio-temporal model of the fire to more accurately characterize the physical and optical properties of the fire. Finally, we choose a two-class SVM classifier to identify the fire from the candidate areas and use a radial basis function kernel to improve the accuracy of the recognition. Two different sets of data are used to validate the algorithm we proposed. And the experimental results indicate that our method performs well in video fire surveillance.

Analysis of Intrusion Detection System

2011 ◽  
Vol 460-461 ◽  
pp. 451-454
Author(s):  
Yue Sheng Gu ◽  
Hong Yu Feng ◽  
Jian Ping Wang
Keyword(s):  
Information Security ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Intrusion Detection Systems ◽  
Future Research ◽  
Detection Model ◽  
Detection Systems ◽  
Detection Technology ◽  
Technology Concepts

Intrusion detection system is an important device of information security. This article describes intrusion detection technology concepts, classifications and universal intrusion detection model, and analysis of the intrusion detection systems weaknesses and limitations. Finally, some directions for future research are addressed.

scholarly journals Sistemas de detección de disparos: ¿son eficaces para controlar la violencia con armas de fuego en América Latina?/ Gunshot detection systems: Are they effective in controlling firearms violence in Latin America?

2018 ◽  
pp. 128-141 ◽  
Author(s):  
Juan R Aguilar
Keyword(s):  
Latin America ◽  
Latin American ◽  
Fire Detection ◽  
Gun Violence ◽  
Detection Systems ◽  
Detection Technology ◽  
Technological Tool ◽  
America Latina ◽  
Latin American Countries ◽  
Main Operating

La violencia con armas de fuego es uno de los problemas sociales más grandes de América Latina. Desde hace algunos años, los sistemas de detección de disparos están cobrando relevancia en la región como una herramienta tecnológica que puede reducirla. Este artículo presenta una revisión de la tecnología de detección de disparos, e intenta examinar su utilización en algunos países de América Latina. Se resumen los principales atributos de funcionamiento de estos sistemas y se revisan investigaciones para evaluar su eficacia en el apoyo a la labor policial, la reducción de la violencia y los crímenes con armas de fuego. Con base en sus principios de funcionamiento y las diferencias urbanísticas y demográficas de las ciudades donde se utilizan, se examina cualitativamente el desempeño de los sistemas de detección de disparos en la región. Abstract Gun violence is one of the biggest social problems in Latin America. In recent years gunshot detection systems have been gaining relevance in the region as a technological tool that may reduce it. This article presents a review of gunshot detection technology, and attempt to examine its use in some Latin American countries. The main operating attributes of these systems are described, and researches conducted to evaluate their effectiveness in supporting police work and reducing gun violence and crimes are reviewed. Based upon the operating principles of these systems and considering the urban and demographic differences of the cities where they are used, the performance and effectiveness of the fire detection systems in the region are qualitatively examined.

A Forest Fire Detection System

2013 ◽  
pp. 1088-1098
Author(s):  
Vassileios Tsetsos ◽  
Odysseas Sekkas ◽  
Evagellos Zervas
Keyword(s):  
Forest Fires ◽  
Detection System ◽  
Fire Detection ◽  
Decision Fusion ◽  
Visible Range ◽  
Detection Algorithms ◽  
Integrated Technology ◽  
Detection Systems ◽  
Individual Decisions ◽  
Fusion Scheme

Forest fires cause immeasurable damages to indispensable resources for human survival, destroy the balance of earth ecology, and worst of all they frequently cost human lives. In recent years, early fire detection systems have emerged to provide monitoring and prevention of the disasterous forest fires. Among them, the Meleager1 system aims to offer one of the most advanced and integrated technology solutions for fire protection worldwide by integrating several innovative features. This chapter outlines one of the major components of the Meleager system, that is the visual fire detection sybsystem. Groundbased visible range PTZ cameras monitor the area of interest, and a low level decision fusion scheme is used to combine individual decisions of numerous fire detection algorithms. Personalized alerts and induced feedback is used to adapt the detection process and improve the overall system performance.

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