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地下电缆通道的无线温湿度传感网与BP评估
引用本文:文溢,赵振刚,宋维彬,李川.地下电缆通道的无线温湿度传感网与BP评估[J].传感器与微系统,2016(10):63-66.
作者姓名:文溢  赵振刚  宋维彬  李川
作者单位:昆明理工大学 信息工程及自动化学院,云南 昆明,650500
摘    要:无线传感网技术线路较少,串绕简单等特点,使得短距离的无线传感技术能很好地解决地下电缆通道电缆线路繁多、运营维护监测困难等问题。通过建立基于无线温湿度传感网的地下电缆通道系统,用温湿度传感器对其进行监测,监测的实时数据用无线传感网技术传回,并通过BP神经网络模型对监测数据进行网格训练,建立优化模型,得到优化前后的权值和阈值训练误差曲线,优化前的训练样本和测试样本的仿真误差分别为0.19和0.30,优化后这两个数值分别为0.17和0.024。随机选取楚雄腰站变电站20组监测数据带入BP模型,得到结果与电缆通道温湿度安全等级对比,准确度达到93.3%。

关 键 词:无线传感网  地下电缆通道  温湿度传感器  实时监测  BP神经网络

Wireless temperature and humidity sensor networks of underground cable channels and BP evaluation
WEN Yi,ZHAO Zhen-gang,SONG Wei-bin,LI Chuan.Wireless temperature and humidity sensor networks of underground cable channels and BP evaluation[J].Transducer and Microsystem Technology,2016(10):63-66.
Authors:WEN Yi  ZHAO Zhen-gang  SONG Wei-bin  LI Chuan
Abstract:Due to wireless sensor networks( WSNs)technology route is less and simple,short distance wireless sensing technology can solve problems of complex line difficulty of maintain caused by the underground cable channel. Through establishment of underground cable channel system based on WSNs,use temperature and humidity sensor for monitoring. The real-time monitoring data is transmitted back by WSNs technology,and through BP neural network model for grid training on monitoring data,set up optimization model and get weights before and after optimization and error curve of threshold training,simulation error of training samples and test samples before optimization are 0. 19 and 0. 30,respectively,these two values are 0. 17 and 0. 024 after optimization. Select 20 set of monitoring data of ChuXiong transformer substation randomly to BP model,compare the obtained results with cable channel temperature and humidity security levels,accuracy up to 93. 3%.
Keywords:wireless sensor networks( WSNs)  underground cable channels  temperature and humidity sensor  real-time monitoring  BP neural network
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