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作 者:孙芳杰 霍青瑶 丁纪峰 张笑彤 常新 王宗恩泽 Sun Fangjie;Huo Qingyao;Ding Jifeng;Zhang Xiaotong;Chang Xin;Wangzong Enze(School of Information and Communication Engineering,Dalian Minzu University,Dalian Liaoning 116600,China)
机构地区:[1]大连民族大学信息与通信工程学院,辽宁大连116600
出 处:《山西电子技术》2024年第5期4-7,116,共5页Shanxi Electronic Technology
摘 要:随着能源危机不断加剧,电能节约和高效利用至关重要。基于此,提出一种家用电器识别系统及方法。系统以STM32F103为核心,应用传感技术和无线通信技术,通过非侵入式负荷监测方法,实现了电参数测量、用电器识别、电参数自学习和无线数据传输等功能。采用欧氏距离的判别方法,识别电器种类,算法简单,算力要求低,识别准确率较高。通过移动互联网,实现远程云平台数据监测及数据可视化,系统使用灵活,效果良好。With the aggravation of energy crisis,the saving and efficient use of electric energy is vital.To solve the problem of effective monitoring of household appliances and improving the utilization efficiency of electric energy,this paper proposes a household appliances identification system and method.With STM32F103 as the core processor,the system uses sensor technology and wireless communication technology,and realizes the functions of electrical parameter measurement,electrical appliance identification,electrical parameter self-learning and wireless data transmission through non-invasive load monitoring method.The identification method of Euclidean distance is used to identify the types of electrical appliances.The algorithm is simple,the computing power is low and the recognition accuracy is high.Through the mobile Internet,remote cloud platform data monitoring and data visualization,the system is flexible and works well.
关 键 词:用电器种类识别 非侵入式负荷监测 STM32核心处理器 欧氏距离
分 类 号:TP273[自动化与计算机技术—检测技术与自动化装置]
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