摘要
根据当今火灾探测的现状和实现对火灾的早期探测的需求,本文提出了一种多传感器火灾检测系统。本系统利用多传感器对火灾的多个参数进行检测,克服了传统单一传感器的不足。单一传感器采用阈值法监测火灾,漏报和误报的概率很高。本文采用了多传感器检测,对火灾发生的初期进行全面的检测,弥补了单一传感器的不足,扩展了时间和空间的观测范围。本系统采用自适应加权融合估算法配合BP神经网络智能判别技术,增强了系统报警输出的灵敏度和可靠性,使系统实现了提前预警。
According to the present situation of fire detection and the requirement of early detection of fire, this paper presents a multi-sensor fire detection system. The system uses multiple sensors to detect multiple parameters of the fire, to overcome the traditional single sensor deficiencies. So if we use single threshold method to monitor the probability of fire, it will lead to missing and false alarm. This paper uses multi-sensor detection.It detects fire comprehensively on the occurrence of early fire.it overcomes the shortcomings of single sensor detection and extends the range of time and space observation. The system adopts self-adaptive weighted fusion algorithm and BP neural network intelligent discriminant technology to enhance the system alarm output sensitivity and reliability, and makes it achieve alarm early.
出处
《智慧工厂》
2018年第1期62-65,共4页
Smart Factory
