面向智能电表的并行多家电识别

Lien-Chun Wang, Wei-Ting Cho, Y. Chiu, Chin-Feng Lai
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引用次数: 2

摘要

本研究提出了一种非侵入式智能电表系统,该系统考虑了不熟悉电器的用户的用电习惯,并且可以通过将智能电表插入电路中使用。为了解决当前家电识别系统中数据量大的问题,本研究还建立了数据库机制、家电识别分类和波形识别方法。与其他家电识别系统相比,本研究采用的低端嵌入式系统芯片具有低功耗、高扩展性和易用性的特点。本实验不同于其他家电识别系统的研究环境,考虑了多家电并行识别和一般用户的用电习惯。本研究不会对实验中的功率利用率做任何假设。系统的总识别率为84.42%,单个电器的总识别率为93.82%,证明了本研究的高可行性。
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A Parallel Multi-appliance Recognition for Smart Meter
This study proposes a non-invasive smart meter system that considers the power use habits of users unfamiliar with electric appliances, and can be used by inserting the smart meter into an electrical circuit. This study also creates a database mechanism, appliance recognition classification, and a waveform recognition method, in order to solve the large data volume problem in current appliance recognition systems. In comparison to other appliance recognition systems, the low-end embedded system chip used in this study has low power consumption, as well as high expandability and ease of use. This experiment is different from the research environments of other appliance recognition systems by considering parallel multi-appliance recognition and general users' habit of using power. This study will not make any assumption of power utilization in the experiment. The total system recognition rate is 84.42%, and the total recognition rate of a single electric appliance is 93.82%, proving the high feasibility of this study.
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