Abstract
Aiming to the fire detection, a fire detection system based on temperature and pyroelectric infrared sensors is designed in this paper. According to the National Fire Detection Standard, a great number of test data are acquired. A model based on Levenberg-Marquardt Back Propagation (LM-BP) neutral network is established to recognize the fire status using the acquired data. Among the data, 200 groups of samples are used to train the established LM-BP networks while 1500 groups of samples test the LM-BP model. A 90% recognition rate is obtained by the LM-BP model. Compared with the other neutral networks such as Radial Basis Function (RBF) network, the LM-BP neural network has a significantly higher recognition rate (90%) than the RBF net (70%). The initial results show that the LM-BP recognition method has a favourable performance, which provides an effective way for fire detection.
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References
James, A.M.: Using Multiple Sensors for Discriminating Fire Detection. J. FL. USA, 150–164 (1999)
Okayama, Y.: A Primitive Study of a Fire Detection Method Controlled by Artificial Neural Net. J. Fire Safety Journal 17, 535–553 (1991)
Pfister, G.: Multisensor fire detection: A new trend rapidly becomes state of art. J. Fire Technology 33, 115–139 (1997)
James, A.M., Thomas, J.: Analysis of signature patterns for discriminating fire detection with multiple sensors. J. Fire Technology 31, 120–136 (1998)
Moghavvemi, M., Seng, L.C.: Pyroelectric infrared sensor for intruder detection. J. Analog and Digital Techniques in Electrical Engineering, 656–659 (2004)
Thuilldar, M.: New method for reducing the number of false alarms in fire detection systems. J. Fire Technology 31, 250–268 (1994)
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Banghua, Y., Zheng, D., Yonghuai, Z., Xiaoming, Z. (2010). Recognition of Fire Detection Based on Neural Network. In: Li, K., Fei, M., Jia, L., Irwin, G.W. (eds) Life System Modeling and Intelligent Computing. ICSEE LSMS 2010 2010. Lecture Notes in Computer Science, vol 6329. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15597-0_28
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DOI: https://doi.org/10.1007/978-3-642-15597-0_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15596-3
Online ISBN: 978-3-642-15597-0
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