|本期目录/Table of Contents|

[1]邓力,刘全义,胡林,等.基于BP神经网络的受限空间火灾联合探测方法[J].中国安全生产科学技术,2020,16(1):158-162.[doi:10.11731/j.issn.1673-193x.2020.01.026]
　DENG Li,LIU Quanyi,HU Lin,et al.Joint detection method of fire in confined space based on BP neural network[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2020,16(1):158-162.[doi:10.11731/j.issn.1673-193x.2020.01.026]
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基于BP神经网络的受限空间火灾联合探测方法
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
16
期数:
2020年1期
页码:
158-162
栏目:
特邀专栏
出版日期:
2020-01-30

文章信息/Info

Title:
Joint detection method of fire in confined space based on BP neural network
文章编号:
1673-193X(2020)-01-0158-05
作者:
邓力; 刘全义; 胡林; 贺元骅
(1.中国民用航空飞行学院 民航安全工程学院,四川 广汉 618307；
2.南京理工大学,江苏 南京 210094)
Author(s):
DENG Li;  LIU Quanyi;  HU Lin;  HE Yuanhua
(1.College of Civil Aviation Safety Engineering,Civil Aviation Flight University of China,Guanghan Sichuan 618307,China;
2.Nanjing University of Science and Technology,Nanjing Jiangsu 210094,China)
关键词:
火灾探测; 受限空间; 神经网络; 联合探测
Keywords:
fire detection;  confined space;  neural network;  joint detection
分类号:
X951
DOI:
10.11731/j.issn.1673-193x.2020.01.026
文献标志码:
A
摘要:
针对航空受限空间火灾探测高误报的问题，在现有技术成果基础上对多种火灾探测方式进行研讨，并提出1种基于BP神经网络技术的飞机机身内部受限空间火灾联合探测报警方法。该方法结合现有烟雾感应、气体传感器探测等常用火灾探测技术，以红外热成像探测为辅助手段，采用神经网络实现数据融合，对模拟实验舱火灾烟雾进行联合探测，在单一火灾探测方式基础上提高了探测准确率。
Abstract:
Aiming at the problem of high false alarms in the fire detection of aviation confined space,various fire detection methods were discussed based on the existing technical achievements,and a joint detection and alarm method of fire in the confined space inside the aircraft fuselage based on the BP neural network technology was proposed.The method combined the existing smoke sensing technology,gas sensor detection and other common fire detection technologies,and used the infrared thermal imaging detection as an auxiliary means.The neural network was utilized to realize the data fusion,and the joint detection was carried out on the fire smoke in the simulated experimental cabin.The detection accuracy was improved on the basis of single fire detection mode.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期： 2020-01-16
* 基金项目： 国家重点研发计划项目（2018YFC0809503）；国家自然科学基金项目（U1633203）
作者简介： 邓力,硕士，讲师，主要研究方向为民航消防安全技术、民航信息处理技术。
通信作者： 贺元骅,硕士，教授，主要研究方向为航空安全理论、热失控理论。
更新日期/Last Update: 2020-03-02