摘要
为了克服传统有线监测和人工离线式监测高压设备温度数据的高复杂度、高成本及布线难等弊端,该文设计了一种基于物联网的高压带电体温度预警系统。通过物联网技术对温度数据进行采集、传输,利用BP神经网络对高压带电体温度进行预测,并对BP神经网络建立的预测模型进行优化。实验结果表明,该系统实现了高压设备温度的预测预警和设备的安全控制,具有较高的工程应用价值。
In order to overcome the traditional artificial off-line monitoring and high voltage cable monitoring equipment temperature data of the disadvantages of high cost and high complexity and wiring difficult ,this paper designed a kind of high voltage charged body temperature warning system. The BP neural network is used to predict the temperature of the high voltage charged body,and the prediction method of the BP neural network is optimized. The experimental results show that the system can realize the prediction and early warning of the temperature of the high pressure equipment and the safety control of the equipment,which has high engineering application value.
出处
《自动化与仪表》
2017年第4期42-47,76,共7页
Automation & Instrumentation
基金
国家自然科学基金项目(51277023)
商洛学院科研项目(15SKY008)
关键词
物联网
高压带电体
BP神经网络
预警
internet of things（IoT）
high voltage electrified body
BP neural network
early warning
