基于语义网络的列车无线烟雾报警系统的设计与实现

Passenger Train Wireless Smoke Alarm System Design Based on Semantic Network[HS)]

摘要:

当前的列车无线烟雾报警系统无法对多变环境下的烟雾复杂信息特征进行准确地描述与提取,列车无线烟雾报警系统报警精度较低；设计并实现了一种基于语义网络的列车无线烟雾报警系统,采用语义网络作为综合信息描述烟雾属性之间的内部联系,将ARMS3C2440当成主控芯片,语义网络节点当成数据交换模块,总体列车无线烟雾报警系统中ZigBee无线模块同语义网络相融合,采用可伸缩语义网络距离准确描述烟雾浓度信息特征阀值,进行报警,提高了报警的准确率与及时性；验设置烟雾流速为1.0 g/s,浓度是2 g/s,设置烟雾浓度报警阀值小于或等于25%火灾下限,而总体气体中烟雾火灾下限是5%,因此设置烟雾气体报警高限是1%；真实验结果说明,该种语义网络的列车无线烟雾报警系统能够准确分析列车中烟雾特征,对异常烟雾进行及时准确地报警,相比传统报警系统,报警精确度提高了42%左右,报警时间降低2~3 s,具有很强的应用前景。

Abstract:

Was designed and implemented a train wireless smoke alarm system based on semantic network, by using semantic network as a comprehensive information to describe the internal connection between the smoke properties, ARMS3C2440 as main control chip, semantic network nodes as a data exchange module, ZigBee wireless module of the overall train wireless smoke alarm system combined with the semantic network, accurate description of smoke concentration by using scalable semantic network distance threshold information characteristics, alarm, improve the alarm accuracy and timeliness. Setup smoke flow rate of 1.0 kg/s, the concentration is 2 kg/s, set the alarm valve value less than or equal to 25% of fire smoke concentration lower limit, and the overall gas fire smoke in the lower limit is 5%, so the smoke gas alarm upper limit is 1%. The result of simulation experiment shows that this kind of semantic network train wireless smoke alarm system can accurately analyzing the characteristic of smoke in the train, to timely and accurate warning of abnormal smoke, compared to the traditional alarm system, alarm accuracy increased by about 42%, and the alarm time reduce 2~3 s, have very strong application prospects.