数据融合在物联网火灾监测系统中的应用研究$  

Application of data fusion technology in fire detection system based on the Internet of things

作　　者：杨晓萍[1,2] 孙继玮 牛超[2] 王瑞[2] 

机构地区：[1]吉林大学汽车仿真与控制国家重点实验室,长春130012 [2]吉林大学通信工程学院,长春130012

出　　处：《电子测量技术》2016年第3期100-105,共6页Electronic Measurement Technology

基　　金：吉林省科委重点科技攻关项目(No:20140204087GX);国家自然科学基金青年基金项目(No:6140020296)

摘　　要：利用数据融合技术,可以弥补单一传感器数据所造成的结果不完整以及片面的缺陷。为了保证火灾判断的准确性,提出神经网络和模糊理论相结合的火灾监测算法,并将算法应用在火灾监测系统中。通过利用神经网络工具箱以及模糊推理工具箱,对两种算法分别进行了MATLAB仿真和分析,得出将两种算法结合适用于火灾监测的结论。最后在火灾监测开发平台上利用VS2010实现对火灾数据的处理,得出火灾发生概率,而后判断火灾发生的可能性,实现了火灾监测算法功能,保证了判断的准确性。The method of data fusion can make up for the results of single sensor data,which is incomplete and partial defects.A fire detection algorithm based on neural network and fuzzy theory is proposed and applied to the fire detection system in order to ensure the accuracy of the judgment.Through the use of neural network toolbox and fuzzy logic toolbox,MATLAB simulation and analysis are carried out on two kinds of algorithms.The conclusion is drawn that the combination of two algorithms is suitable for fire detection.Finally,using VS2010 to realize the function of fire detection algorithm based on the development platform of the detection system.The algorithm realizes the process of fire data,obtains the probability of fire occurrence,judges the possibility of fire and ensure the accuracy of the judgment.

关 键 词：火灾监测 数据融合技术 BP神经网络 模糊推理 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]