摘要
国内对民用飞机机载烟雾探测器的故障检测仍处于较低水平,烟雾探测器的故障检测技术完全依赖于国外。本文基于神经网络算法,分析机载烟雾探测器的故障诊断方法,实现对机载烟雾探测器故障的测试与定位,测试平台经调试运行可以达到实际应用水平。
The test ability of airplane airborne smoke detector is still in the low level in China. It almost depends on overseas technology for fault diagnosis. This thesis bases on the neural network algorithm, analyses fault diagnosis method of airborne smoke detector, and realizes the airborne smoke detector troubleshooting. Through debugging and testing, this system gets positive results for practical application.
出处
《中国民航飞行学院学报》
2012年第1期43-46,共4页
Journal of Civil Aviation Flight University of China
关键词
机载烟雾探测器
检测系统
智能
Airborne smoke detector Testing system Intelligent
