Abstract Non-intrusive load monitoring (NILM) techniques estimate the consumption of individual appliances in a household or facility, based on readings of a centralized meter. Usually, NILM techniques are shown to be improved when various power features and additional power quality parameters are included. However, adding power features leads to increased time complexity which is a disadvantage to real-time operation. Therefore, in this work we offer a process based on principal component analysis (PCA) which reduces the dimension of NILM power features. The suggested method can be used with any NILM classification technique, and shows good performance in terms of standard measures and time complexity when tested on popular datasets.

中文翻译：

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基于主成分分析的NILM分类降维

摘要 非侵入式负载监测 (NILM) 技术根据中央仪表的读数估计家庭或设施中单个电器的消耗。通常，当包含各种电源特性和附加电源质量参数时，NILM 技术会得到改进。但是，添加电源功能会导致时间复杂度增加，这不利于实时操作。因此，在这项工作中，我们提供了一个基于主成分分析 (PCA) 的过程，它减少了 NILM 功率特征的维度。建议的方法可以与任何 NILM 分类技术一起使用，并且在流行数据集上进行测试时，在标准度量和时间复杂度方面表现出良好的性能。