Fire Detection Algorithm Combined with Image Processing and Flame Emission Spectroscopy

Fire Detection Algorithm Combined with Image Processing and Flame Emission Spectroscopy Fire poses a significant risk to the safety, health, and property of people around the world. However, traditional ‘‘point sensor’’ fire detection techniques for indoor buildings based on air particles, air temperatures, and smoke have a low sensitivity, long response time, and poor stability. Therefore, video-based fire detection has become a particularly efficient and important method for detecting the early signs of a fire. Due to image blur, low illumination, flame-like interference and other factors, there is a certain error rate of fire recognition using video flame recognition methods. According to our previous study of a multi-feature flame recognition algorithm, a novel flame recognition algorithm based on free radical emission spectroscopy during combustion is investigated in this paper. First, multiple features are extracted from the video images by employing our proposed processing scheme. Then, the features are post-processed by a temporal smoothing algorithm to eliminate the error recognition rate, which is caused by the similar characteristics of objects between flame-like and real flame areas. In the temporal smoothing experiments, the proposed method achieves the true positive rates of 0.965 and 0.937 for butane flames and forest fire, respectively. Additionally, the spectral signals of OH, CH, C2 and other free radicals in the combustion objects were acquired by the spectrometer. The vibrational temperature and rotational temperature are calculated after identification of the A 2 Δ → X 2 Π transition of the CH (410–440 nm). The flames-like are completely rejected by the proposed method in the validation experiment. In the subsequent butane combustion experiment, the vibrational temperature of the butane was 4896 K, and the rotational temperature was 2290 K. The experimental results show that real fires can be precisely recognized and that the combustion temperature can be determined from the CH emission spectroscopy. This novel method provides a new viewpoint for fire detection and recognition. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Fire Technology Springer Journals

Fire Detection Algorithm Combined with Image Processing and Flame Emission Spectroscopy

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Engineering; Civil Engineering; Classical Mechanics; Characterization and Evaluation of Materials; Physics, general
ISSN
0015-2684
eISSN
1572-8099
D.O.I.
10.1007/s10694-018-0727-x
Publisher site
See Article on Publisher Site

Abstract

Fire poses a significant risk to the safety, health, and property of people around the world. However, traditional ‘‘point sensor’’ fire detection techniques for indoor buildings based on air particles, air temperatures, and smoke have a low sensitivity, long response time, and poor stability. Therefore, video-based fire detection has become a particularly efficient and important method for detecting the early signs of a fire. Due to image blur, low illumination, flame-like interference and other factors, there is a certain error rate of fire recognition using video flame recognition methods. According to our previous study of a multi-feature flame recognition algorithm, a novel flame recognition algorithm based on free radical emission spectroscopy during combustion is investigated in this paper. First, multiple features are extracted from the video images by employing our proposed processing scheme. Then, the features are post-processed by a temporal smoothing algorithm to eliminate the error recognition rate, which is caused by the similar characteristics of objects between flame-like and real flame areas. In the temporal smoothing experiments, the proposed method achieves the true positive rates of 0.965 and 0.937 for butane flames and forest fire, respectively. Additionally, the spectral signals of OH, CH, C2 and other free radicals in the combustion objects were acquired by the spectrometer. The vibrational temperature and rotational temperature are calculated after identification of the A 2 Δ → X 2 Π transition of the CH (410–440 nm). The flames-like are completely rejected by the proposed method in the validation experiment. In the subsequent butane combustion experiment, the vibrational temperature of the butane was 4896 K, and the rotational temperature was 2290 K. The experimental results show that real fires can be precisely recognized and that the combustion temperature can be determined from the CH emission spectroscopy. This novel method provides a new viewpoint for fire detection and recognition.

Journal

Fire TechnologySpringer Journals

Published: Jun 2, 2018

References

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