摘要
设计了一种新型边缘感知自适应数据处理技术,通过边缘感知传感器完成电力物联网数据的实时采样,利用数据衰减记忆(MA-STUKF)算法完成样本数据的精确快速计算,利用逻辑加密标识(SHA-1)算法对计算出的数据进行分类标识。最后通过MATLAB对本研究和传统数据处理方法进行均值方差仿真比较,数据波动范围在20%~35%之间,而且电力数据的计算结果准确度达到98%,边缘数据的计算结果也能达到80%以上。
In the paper,a new edge-sensing adaptive data processing technology is designed,real-time sampling of power Internet of Things data is completed through edge-sensing sensors,data attenuation memory algorithm is used to complete accurate and fast calculation of sample data,and logical encryption identification algorithm is used classify and identify the calculated data.Finally,the mean variance simulation comparison between this research and traditional data processing methods is carried out through MATLAB.The data fluctuates between 20%and 35%,and the accuracy of the calculation results of the power data reaches 98%,and the calculation results of the edge data can reach 80%.
作者
赵珩
苗堃
李峙
王锋
张元东
张胜利
Zhao Heng;Miao Kun;Li Zhi;Wang Feng;Zhang Yuandong;Zhang Shengli(State Grid Henan Electric Power Company,Jiyuan Power Supply Company,Jiyuan 454650,China)
出处
《单片机与嵌入式系统应用》
2021年第11期34-37,41,共5页
Microcontrollers & Embedded Systems
