基于UHF-RFID/RBF的电力电缆温度监测研究

Research on temperature monitoring of power cable based on UHF-RFID/RBF

电缆是城市建设中的重要设备,据统计电缆事故中大部分源于电缆温度过高而引发损坏,因此监测电缆温度有很重要的意义。由于实际情况中电缆安装的环境比较复杂,选择采用无线UHF-RFID技术监测温度,既有效节约成本,又提高效率,还可以系统内供电,同时搭建实验平台收集数据并用于温度预测研究。首先将UHF-RFID技术应用于电缆温度监测,然后根据电缆表皮温度、环境湿度、环境温度、电缆载流量和运行时间五个影响因子用RBF神经网络算法对测得的压接接头、插拔接头和电缆本体的缆芯温度进行训练与预测,最后用MATLAB仿真出温度图,与实际温度对比误差很小,证明UHF-RFID/RBF预测可靠性强。

Cable is an important equipment in urban construction.According to statistics,most cable accidents are caused by damage caused by cable temperature.Therefore,monitoring cable temperature is of great significance.Due to the complex environment of cable installation in actual situation,wireless UHF-RFID technology is chosen to monitor temperature,which can not only effectively save cost,but also improve efficiency,but also power supply within the system.At the same time,an experimental platform is built to collect data and used for temperature prediction research.This paper will be the UHF RFID technology is applied to the cable temperature monitoring,and then use RBF neural network algorithm to the measured pressure joint,plug connector and cable core temperature of the ontology,accord-ing to the cable skin temperature,environment humidity,environment temperature,cable current carrying capacity,operation time,five impact factor for training and prediction,the MATLAB simulation temperature figure,The com-parison error with actual temperature is very small,which proves that UHF-RFID/RBF prediction is reliable.