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982 KiB

Open AccessArticle

Microwave Radiometers for Fire Detection in Trains: Theory and Feasibility Study

by Federico Alimenti, Luca Roselli and Stefania Bonafoni

Sensors 2016, 16(6), 906; https://doi.org/10.3390/s16060906 - 17 Jun 2016

Cited by 12 | Viewed by 7540

Abstract

This paper introduces the theory of fire detection in moving vehicles by microwave radiometers. The system analysis is discussed and a feasibility study is illustrated on the basis of two implementation hypotheses. The basic idea is to have a fixed radiometer and to [...] Read more.

This paper introduces the theory of fire detection in moving vehicles by microwave radiometers. The system analysis is discussed and a feasibility study is illustrated on the basis of two implementation hypotheses. The basic idea is to have a fixed radiometer and to look inside the glass windows of the wagon when it passes in front of the instrument antenna. The proposed sensor uses a three-pixel multi-beam configuration that allows an image to be formed by the movement of the train itself. Each pixel is constituted by a direct amplification microwave receiver operating at 31.4 GHz. At this frequency, the antenna can be a 34 cm offset parabolic dish, whereas a 1 K brightness temperature resolution is achievable with an overall system noise figure of 6 dB, an observation bandwidth of 2 GHz and an integration time of 1 ms. The effect of the detector noise is also investigated and several implementation hypotheses are discussed. The presented study is important since it could be applied to the automatic fire alarm in trains and moving vehicles with dielectric wall/windows. Full article

(This article belongs to the Special Issue Sensors for Fire Detection)

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3184 KiB

Open AccessArticle

Efficient Forest Fire Detection Index for Application in Unmanned Aerial Systems (UASs)

by Henry Cruz, Martina Eckert, Juan Meneses and José-Fernán Martínez

Sensors 2016, 16(6), 893; https://doi.org/10.3390/s16060893 - 16 Jun 2016

Cited by 130 | Viewed by 27230

Abstract

This article proposes a novel method for detecting forest fires, through the use of a new color index, called the Forest Fire Detection Index (FFDI), developed by the authors. The index is based on methods for vegetation classification and has been adapted to [...] Read more.

This article proposes a novel method for detecting forest fires, through the use of a new color index, called the Forest Fire Detection Index (FFDI), developed by the authors. The index is based on methods for vegetation classification and has been adapted to detect the tonalities of flames and smoke; the latter could be included adaptively into the Regions of Interest (RoIs) with the help of a variable factor. Multiple tests have been performed upon database imagery and present promising results: a detection precision of 96.82% has been achieved for image sizes of 960 × 540 pixels at a processing time of 0.0447 seconds. This achievement would lead to a performance of 22 f/s, for smaller images, while up to 54 f/s could be reached by maintaining a similar detection precision. Additional tests have been performed on fires in their early stages, achieving a precision rate of p = 96.62%. The method could be used in real-time in Unmanned Aerial Systems (UASs), with the aim of monitoring a wider area than through fixed surveillance systems. Thus, it would result in more cost-effective outcomes than conventional systems implemented in helicopters or satellites. UASs could also reach inaccessible locations without jeopardizing people’s safety. On-going work includes implementation into a commercially available drone. Full article

(This article belongs to the Special Issue Sensors for Fire Detection)

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5075 KiB

Open AccessArticle

Fire Source Localization Based on Distributed Temperature Sensing by a Dual-Line Optical Fiber System

by Miao Sun, Yuquan Tang, Shuang Yang, Jun Li, Markus W. Sigrist and Fengzhong Dong

Sensors 2016, 16(6), 829; https://doi.org/10.3390/s16060829 - 6 Jun 2016

Cited by 34 | Viewed by 7059

Abstract

We propose a method for localizing a fire source using an optical fiber distributed temperature sensor system. A section of two parallel optical fibers employed as the sensing element is installed near the ceiling of a closed room in which the fire source [...] Read more.

We propose a method for localizing a fire source using an optical fiber distributed temperature sensor system. A section of two parallel optical fibers employed as the sensing element is installed near the ceiling of a closed room in which the fire source is located. By measuring the temperature of hot air flows, the problem of three-dimensional fire source localization is transformed to two dimensions. The method of the source location is verified with experiments using burning alcohol as fire source, and it is demonstrated that the method represents a robust and reliable technique for localizing a fire source also for long sensing ranges. Full article

(This article belongs to the Special Issue Sensors for Fire Detection)

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5577 KiB

Open AccessArticle

A Novel Arc Fault Detector for Early Detection of Electrical Fires

by Kai Yang, Rencheng Zhang, Jianhong Yang, Canhua Liu, Shouhong Chen and Fujiang Zhang

Sensors 2016, 16(4), 500; https://doi.org/10.3390/s16040500 - 9 Apr 2016

Cited by 64 | Viewed by 15546

Abstract

Arc faults can produce very high temperatures and can easily ignite combustible materials; thus, they represent one of the most important causes of electrical fires. The application of arc fault detection, as an emerging early fire detection technology, is required by the National [...] Read more.

Arc faults can produce very high temperatures and can easily ignite combustible materials; thus, they represent one of the most important causes of electrical fires. The application of arc fault detection, as an emerging early fire detection technology, is required by the National Electrical Code to reduce the occurrence of electrical fires. However, the concealment, randomness and diversity of arc faults make them difficult to detect. To improve the accuracy of arc fault detection, a novel arc fault detector (AFD) is developed in this study. First, an experimental arc fault platform is built to study electrical fires. A high-frequency transducer and a current transducer are used to measure typical load signals of arc faults and normal states. After the common features of these signals are studied, high-frequency energy and current variations are extracted as an input eigenvector for use by an arc fault detection algorithm. Then, the detection algorithm based on a weighted least squares support vector machine is designed and successfully applied in a microprocessor. Finally, an AFD is developed. The test results show that the AFD can detect arc faults in a timely manner and interrupt the circuit power supply before electrical fires can occur. The AFD is not influenced by cross talk or transient processes, and the detection accuracy is very high. Hence, the AFD can be installed in low-voltage circuits to monitor circuit states in real-time to facilitate the early detection of electrical fires. Full article

(This article belongs to the Special Issue Sensors for Fire Detection)

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1228 KiB

Open AccessArticle

Multi-Stage Feature Selection Based Intelligent Classifier for Classification of Incipient Stage Fire in Building

by Allan Melvin Andrew, Ammar Zakaria, Shaharil Mad Saad and Ali Yeon Md Shakaff

Sensors 2016, 16(1), 31; https://doi.org/10.3390/s16010031 - 19 Jan 2016

Cited by 20 | Viewed by 8160

Abstract

In this study, an early fire detection algorithm has been proposed based on low cost array sensing system, utilising off- the shelf gas sensors, dust particles and ambient sensors such as temperature and humidity sensor. The odour or “smellprint” emanated from various fire [...] Read more.

In this study, an early fire detection algorithm has been proposed based on low cost array sensing system, utilising off- the shelf gas sensors, dust particles and ambient sensors such as temperature and humidity sensor. The odour or “smellprint” emanated from various fire sources and building construction materials at early stage are measured. For this purpose, odour profile data from five common fire sources and three common building construction materials were used to develop the classification model. Normalised feature extractions of the smell print data were performed before subjected to prediction classifier. These features represent the odour signals in the time domain. The obtained features undergo the proposed multi-stage feature selection technique and lastly, further reduced by Principal Component Analysis (PCA), a dimension reduction technique. The hybrid PCA-PNN based approach has been applied on different datasets from in-house developed system and the portable electronic nose unit. Experimental classification results show that the dimension reduction process performed by PCA has improved the classification accuracy and provided high reliability, regardless of ambient temperature and humidity variation, baseline sensor drift, the different gas concentration level and exposure towards different heating temperature range. Full article

(This article belongs to the Special Issue Sensors for Fire Detection)

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3042 KiB

Open AccessArticle

A Real-Time Monitoring System of Industry Carbon Monoxide Based on Wireless Sensor Networks

by Jiachen Yang, Jianxiong Zhou, Zhihan Lv, Wei Wei and Houbing Song

Sensors 2015, 15(11), 29535-29546; https://doi.org/10.3390/s151129535 - 20 Nov 2015

Cited by 135 | Viewed by 12400

Abstract

Carbon monoxide (CO) burns or explodes at over-standard concentration. Hence, in this paper, a Wifi-based, real-time monitoring of a CO system is proposed for application in the construction industry, in which a sensor measuring node is designed by low-frequency modulation method to acquire [...] Read more.

Carbon monoxide (CO) burns or explodes at over-standard concentration. Hence, in this paper, a Wifi-based, real-time monitoring of a CO system is proposed for application in the construction industry, in which a sensor measuring node is designed by low-frequency modulation method to acquire CO concentration reliably, and a digital filtering method is adopted for noise filtering. According to the triangulation, the Wifi network is constructed to transmit information and determine the position of nodes. The measured data are displayed on a computer or smart phone by a graphical interface. The experiment shows that the monitoring system obtains excellent accuracy and stability in long-term continuous monitoring. Full article

(This article belongs to the Special Issue Sensors for Fire Detection)

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3034 KiB

Open AccessArticle

Low Power Wireless Smoke Alarm System in Home Fires

by Juan Aponte Luis, Juan Antonio Gómez Galán and Javier Alcina Espigado

Sensors 2015, 15(8), 20717-20729; https://doi.org/10.3390/s150820717 - 21 Aug 2015

Cited by 27 | Viewed by 22019

Abstract

A novel sensing device for fire detection in domestic environments is presented. The fire detector uses a combination of several sensors that not only detect smoke, but discriminate between different types of smoke. This feature avoids false alarms and warns of different situations. [...] Read more.

A novel sensing device for fire detection in domestic environments is presented. The fire detector uses a combination of several sensors that not only detect smoke, but discriminate between different types of smoke. This feature avoids false alarms and warns of different situations. Power consumption is optimized both in terms of hardware and software, providing a high degree of autonomy of almost five years. Data gathered from the device are transmitted through a wireless communication to a base station. The low cost and compact design provides wide application prospects. Full article

(This article belongs to the Special Issue Sensors for Fire Detection)

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Review

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1992 KiB

Open AccessReview

Airborne Optical and Thermal Remote Sensing for Wildfire Detection and Monitoring

by Robert S. Allison, Joshua M. Johnston, Gregory Craig and Sion Jennings

Sensors 2016, 16(8), 1310; https://doi.org/10.3390/s16081310 - 18 Aug 2016

Cited by 209 | Viewed by 23266

Abstract

For decades detection and monitoring of forest and other wildland fires has relied heavily on aircraft (and satellites). Technical advances and improved affordability of both sensors and sensor platforms promise to revolutionize the way aircraft detect, monitor and help suppress wildfires. Sensor systems [...] Read more.

For decades detection and monitoring of forest and other wildland fires has relied heavily on aircraft (and satellites). Technical advances and improved affordability of both sensors and sensor platforms promise to revolutionize the way aircraft detect, monitor and help suppress wildfires. Sensor systems like hyperspectral cameras, image intensifiers and thermal cameras that have previously been limited in use due to cost or technology considerations are now becoming widely available and affordable. Similarly, new airborne sensor platforms, particularly small, unmanned aircraft or drones, are enabling new applications for airborne fire sensing. In this review we outline the state of the art in direct, semi-automated and automated fire detection from both manned and unmanned aerial platforms. We discuss the operational constraints and opportunities provided by these sensor systems including a discussion of the objective evaluation of these systems in a realistic context. Full article

(This article belongs to the Special Issue Sensors for Fire Detection)

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