摘要
利用当前方法监控无人值守变电所过程层设备运行状态时,所设置的通信波特率偏小,导致数据传输质量下降,提出基于CAN总线的无人值守变电所过程层设备运行状态智能监控方法。利用CAN信息采集卡采集无人值守变电所过程层设备运行数据,计算CAN总线通信波特率,根据计算结果确定通信波特率值,并对数据采集结果进行传输处理。引入BP神经网络模型,设置BP神经网络模型参数,利用该模型对数据进行深入挖掘,设置过程层设备运行状态监控模式,结合所有数据实现无人值守变电所过程层设备运行状态智能监控。实验结果表明,该方法的数据传输网络节点供电电压变化更接近于实际,通信延时较短以及通信灵敏度高,可实现过程层设备运行状态智能监控。
When the current method is used to monitor the running state of the equipment in the process layer of the unattended substation,the quality of data transmission is reduced due to the small communication baud rate set.Therefore,an intelligent monitoring method for the running state of the equipment in the process layer of the unattended substation based on CAN bus was proposed.The CAN information acquisition card is used to collect the operation data of the equipment in the process layer of the unmanned substation,calculate the communication baud rate of CAN bus,determine the communication baud rate value according to the calculation results,and transmit and process the data acquisition results.BP neural network model was introduced,parameters of BP neural network model were set,and the model was used to conduct in-depth data mining.The operation state monitoring mode of equipment in process layer was set.Combined with all data,intelligent monitoring of the operation state of equipment in process layer of unattended substation was realized.The experimental results showed that the variation of the power supply voltage of the data transmission network nodes is closer to the reality,the communication delay is shorter and the communication sensitivity is higher,and the intelligent monitoring of the running state of the equipment in the process layer can be realized.
作者
郭东明
Guo Dongming(School of Computer and Communication Engineering,Jiangsu Vocational College of Electronics and Information,Huai′an 223003,China)
出处
《能源与环保》
2021年第10期288-293,共6页
CHINA ENERGY AND ENVIRONMENTAL PROTECTION
基金
内蒙古科技厅科技创新引导奖励资金项目(20181912)。
关键词
CAN总线
无人值守
变电所
过程层设备
运行状态
智能监控
CAN bus
unattended
substation
process layer equipment
operation status
intelligent monitoring