基于云计算的电力异常大数据检测系统设计  

Design of power anomaly big data detection system based on cloud computing

作　　者：罗兰溪 李科[1] 孔德诗 荣功立 彭小庆[1] LUO Lanxi;LI Ke;KONG Deshi;RONG Gongli;PENG Xiaoqing(State Grid Sichuan Electric Power Corporation Power Supply Service Center,Chengdu 610041,China)

机构地区：[1]国网四川省电力公司供电服务中心,四川成都610041

出　　处：《电子设计工程》2021年第2期81-84,89,共5页Electronic Design Engineering

基　　金：国家重点研究计划项目(2017YFA0500301);四川省自然科学基金项目(SGSCKE00JYJS1600059)。

摘　　要：为了解决传统电力异常大数据检测系统存在检测精准度低的问题,提出基于云计算的电力异常大数据检测系统。根据系统总体结构设计系统硬件,使用Android和IOS原生开发框架作为移动端底层框架,利用H5技术实现Web端代码共用。使用两个二进制数码“0”和“1”展示数据,使用RabbitMQ技术作为消息队列存储大数据,依据数据缓冲器承载电容负载。根据异常数据分析处理流程,对异常数据展开分析。使用Spring Restdocs技术设计标准服务接口文档,保证系统文档质量,进而实现电力异常大数据检测。由实验结果可知,该系统检测精准度较高,可实时检测电力异常大数据。In order to solve the problem of low detection accuracy in traditional power anomaly big data detection system,a cloud computing based power anomaly big data detection system is proposed.According to the overall structure of the system,the hardware of the system is designed.Android and IOS native development framework are used as the bottom framework of the mobile terminal,and H5 technology is used to realize the code sharing of the Web terminal.Use two binary numbers"0"and"1"to present the data.RabbitMQ technology is used as message queue to store big data,which carries capacitance load according to data buffer.According to the process of abnormal data analysis and processing,analyze the abnormal data.Using Spring Restdocs technology to design standard service interface documents,to ensure the quality of system documents,and then to realize the detection of power abnormal big data.It can be seen from the experimental results that the system has high detection accuracy and can detect the abnormal big data in real time.

关 键 词：云计算 电力异常 大数据 检测 

分 类 号：TN919[电子电信—通信与信息系统]