摘要
采用物联网技术,基于云-边融合策略,设计开发了一种监测变压器整体状态与评估的系统。该系统首先,通过变压器全息状态感知,增加数据多样性;其次,采用边缘计算,实现计算能力下沉,提高站内数据计算的时效性,减少网络传输压力,提高高价值数据传输效率;再次,建立多源数据融合的变压器状态感知云模型,应用深度网络加机器学习等技术手段,对变压器状态进行实时监测和分析,增强监测系统的鲁棒性;最后,通过实际案例验证了系统的有效性。
Using the Internet of Things technology,based on the cloud-side integration strategy,a system for monitoring and evaluating the overall status of the transformer is designed and developed.The system firstly senses the holographic state of the transformer to increase data diversity;secondly,it adopts edge computing to realize the sinking of computing power,improve the timeliness of data calculation in the station,reduce network transmission pressure,and transmit high-value data.Then a multi-source data fusion transformer state perception cloud model is build,and deep network plus machine learning and other technical means is applied to monitor and analyze the transformer state in real time,and enhance the robustness of the monitoring system.Finally,actual cases have verified the effectiveness of the system.
作者
江友华
易罡
黄荣昌
王春吉
杨兴武
JIANG Youhua;YI Gang;HUANG Rongchang;WANG Chunji;YANG Xingwu(School of Electronics and Information Engineering,Shanghai University of Electric Power,Shanghai 201306,China)
出处
《上海电力大学学报》
CAS
2021年第3期226-230,共5页
Journal of Shanghai University of Electric Power
基金
上海市科技创新行动计划(19DZ1205402)。
关键词
物联网
云-边融合
变压器状态评估
多元信息感知
Internet of Things
cloud-edge fusion
transformer status assessment
multiple information perception
