摘要
目前设计的低占用率电力大数据识别系统信息的融合效果较差,导致识别效率低,为此引入多源异构技术,设计了一种新的低占用率电力大数据识别系统。系统硬件由采集模块、分析模块和管理模块三部分组成,采集模块选取CPLD/FPGA数据采集控制器为核心,在管理器内部引入译码电路,连接多个RAM。利用多源异构完成数据的融合,通过离散化处理、来源及特点分析、准确率定义、信息识别完成软件识别。实验结果表明,该设计识别系统能够很好地完成信息融合,识别效率提高了20%,能有效降低数据冗余。
At present,the information fusion effect of the designed low occupancy power big data identif⁃ication system is poor,resulting in low identification efficiency.Therefore,a new low occupancy power big data identification system is designed by introducing multi⁃source heterogeneous technology.The system hardware consists of acquisition module,analysis module and management module.The acquisition module selects CPLD/FPGA data acquisition controller as the core,introduces decoding circuit in the manager and connects multiple RAM.Multi source heterogeneous data fusion is used to complete data fusion,and software identification is completed through discrete processing,source and characteristic analysis,accuracy definition and information identification.The experimental results show that the designed recognition system can complete the information fusion well,improve the recognition efficiency by 20%,and effectively reduce the data redundancy.
作者
马占海
严嘉正
张俊超
MA Zhanhai;YAN Jiazheng;ZHANG Junchao(Information and Communication Company,State Grid Qinghai Electric Power Company,Xining 810008,China)
出处
《电子设计工程》
2023年第20期86-90,共5页
Electronic Design Engineering
关键词
多源异构
低占用率
电力大数据
识别系统
multi⁃source heterogeneity
low occupancy rate
power big data
identification system
作者简介
马占海(1987-),男,回族,青海西宁人,高级工程师。研究方向:电网信息化应用。
