摘要
介绍了采用温度传感器、烟雾传感器和CO传感器等构成的复合型火灾探测器,并应用设置在该探测器内部的软件算法对各传感器采集到的输入信号进行智能分析和处理。对BP神经网络进行了训练。模拟火灾试验结果表明,所设计的复合型智能火灾探测器能快速、准确地判别各类火情,进一步增强火灾探测的灵敏度和可靠性。
A compound fire detector composed of temperature sensor, smoke sensor and CO sensor was introduced, and input signals obtained from each sensor were intelligently, analyzed and processed by using software algorithm inside the detector. The BP neural network was trained. The simulation fire experimental results indicated that the designed compound intelligent fire detector could distinguish all kinds of fire accident rapidly and accurately, and futher enhanced the sensitivity and reliability of lire detecting.
出处
《低压电器》
北大核心
2009年第24期25-28,共4页
Low Voltage Apparatus
基金
湖南省教育厅资助项目(08C615)
关键词
火灾
复合型
探测器
软件算法
训练
BP神经网络
fire
compound
detector
software algorithm
train
back propagation neural network （ BPNN ）
