作　　者： ; ; ;

机构地区： 湖南师范大学物理与信息科学学院电子信息工程系

出　　处： 《传感器技术》 2005年第11期68-70,共3页

摘　　要： 为降低火灾报警系统的漏检、误报率,利用神经网络良好的非线性映射能力,对多传感器(温度传感器、烟雾传感器和CO传感器)同时探测到的数据进行智能化处理。仿真结果表明:基于神经网络的多传感器火灾报警系统能准确地识别各种火灾信号,减少了误报,增强了系统的抗干扰能力和对环境的适应性能. In order to reduce the leak-check and error rate of the fire alarm system, the nonlinear reflecting capability of neural network is applied to intelligently process the data synchronously detected by muhi-sensors （the temperature sensor,the smog sensor and the CO sensor）. The result of simulation shows that the different kinds of signals related to fire disaster can be accurately recognized by the fire alarm system with multi-sensors based on neural network, and the false-alarm can be decreased. The suitability of this system to environmental variation and anti-interference capability can be obviously improved.

关 键 词： 火灾预测 多传感器 神经网络 数据处理

领　　域： [自动化与计算机技术] [自动化与计算机技术]