摘要
研发了一种基于智能无线传感器网络的电力铁塔山火监测分析系统,系统通过对楚雄腰站变电站输电线路周围山地火灾诱发参数情况进行远程在线监测,对监测数据进行趋势分析,对山火发生情况下产生的数据变化进行分析。并采用径向基函数(RBF)神经网络进行回归拟合,预测火灾危险等级。经过测试样本的验证,表明RBF神经网络对于山火监测有较高的准确率,可以对监测数据进行预测分析,适用于山火预测。
A tower fire monitoring and analysis system is developed based on intelligent wireless sensor networks（ WSNs）,remote online monitoring on mountain fire induced parameters around is carried out by Chuxiongyao station substation transmission lines and trend analysis on monitoring data and fire occurrence conditions analysis on data changes. Use RBF neural network for regression fitting,predict fire danger grade. After verification of test sample,indicates the RBF has higher accuracy for fire monitoring and suitable for fire forecast,the monitoring data can be predicting analyzed.
出处
《传感器与微系统》
CSCD
2016年第11期71-73,共3页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(51567013)
