低功耗无线智能设备在线监测数据压缩方法  

Low power wireless intelligent device online monitoring data compression method

作　　者：张超杰 李轶 沈峰 刘昊 吴子渊 ZHANG Chaojie;LI Yi;SHEN Feng;LIU Hao;WU Ziyuan(Qingpu Power Supply Company of State Grid Shanghai Municipal Electric Power Company,Shanghai 201700,China)

机构地区：[1]国网上海市电力公司青浦供电公司,上海201700

出　　处：《电子设计工程》2024年第16期191-195,共5页Electronic Design Engineering

基　　金：国网上海市电力公司科技项目资助(520934230007)。

摘　　要：为释放数据存储空间,提升数据压缩率,提出低功耗无线智能设备在线监测数据压缩方法。分析低功耗无线智能设备在线监测数据采集过程,并传输至控制单元内。采用卡尔曼滤波算法,抑制所采集监测数据内的噪声。通过二乘规划与线性特征拟合的过程,获取滤波后低功耗无线智能设备在线监测数据的特征约束点,实现低功耗无线智能设备在线监测数据压缩。实验结果表明,该方法滤波后的监测数据更贴近实际数据,可最大限度释放数据存储空间。In order to free up data storage space and improve data compression rate,a low⁃power wireless intelligent device online monitoring data compression method is proposed.Analyze the online monitoring data collection process of low⁃power wireless intelligent devices and transmit it to the control unit.Using Kalman filtering algorithm to suppress noise within the collected monitoring data.Through the process of quadratic programming and linear feature fitting,obtain the feature constraint points of low⁃power wireless intelligent device online monitoring data after filtering,and compress the filtered monitoring data in real time.The experimental results show that the filtered monitoring data of this method is closer to the actual data and can maximize the release of data storage space.

关 键 词：无线智能设备 在线监测 数据压缩 卡尔曼滤波 特征约束点 

分 类 号：TN929.5[电子电信—通信与信息系统]