摘要
针对目前智能建筑火灾探测的复杂性,采用离子感烟探测器、光电感烟探测器、温度探测器、火焰探测器来探测复杂的火灾场地,使用BP神经网络和基于D-S证据理论的多传感器数据融合技术对探测到的数据进行处理和仿真。从仿真结果可以看出,数据融合技术能提高火灾识别率。
Aiming at the complexity of intelligent building fire detection,this paper presented ion sensing smoke detector,photoelectric smoke detector,temperature detector,flame and smoke detector,gas detector to detect complex fire site,adopt BP neural network and multi sensor data fusion technology of based on D-S evidence theory to process and simulate the detected data.From the simulation results,data fusion technology can improve the recognition rate of fire,reduce the false alarm rate of fire.
出处
《工业控制计算机》
2012年第8期77-78,共2页
Industrial Control Computer
