摘要
以烟雾、温度、CO气体作为火灾特征参量设计复合火灾探测器;利用Labview设计复合火灾探测系统监控客户端,实现对火灾的实时监控;以模糊神经网络算法代替简单的阈值法实现对火灾的判别。为验证系统的性能,进行不同方位火灾响应时间实验、抗干扰实验、分布式火灾探测实验。实验结果表明:火灾探测器平均响应时间为19.8s,探测器与火源的水平距离比垂直距离对火灾响应时间的影响程度大;抗干扰实验中,火灾误报率为0.375%;由三路探测器组成的火灾探测系统能够实现单点和多点火灾探测。
The composite fire detector was designed with smoke,temperature and CO as the characteristic parameters of fire.The labview was used to design the monitoring client of the composite fire detection system to realize real-time monitoring of fire.The fuzzy neural network algorithm was used to replace the simple threshold method to realize the fire identification.In order to verify the performance of the system,different azimuth fire response time experiments,anti-interference experiments,distributed fire detection experiments were carried out.The experimental results showed that the average response time of the fire detector is 19.8 s.The horizontal distance between the detector and the fire source has a greater impact on the fire response time than the vertical distance.In the anti-interference experiment,the fire false alarm rate is 0.375%.A fire detection system consisting of three detectors enables single-point and multi-point fire detection.
作者
何志祥
王立纲
孟超
钱伟
HE Zhi-xiang;WANG Li-gang;MENG Chao;QIAN Wei(Civil Aviation Flight University of China,Sichuan Guanghan 618307,China)
出处
《消防科学与技术》
CAS
北大核心
2019年第7期977-980,共4页
Fire Science and Technology
基金
中国民航飞行学院科研基金项目(Q2018-105)
作者简介
何志祥(1990-),男,安徽池州人,中国民航飞行学院助理工程师,主要从事航空电子设备智能检测与故障诊断的研究,四川省广汉市中国民航飞行学院广汉分院,618307。
