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文章摘要
一种基于半监督学习的多维条件下电能表误差插值方法
An Electrical Energy Meters Error Interpolation Method under Multidimensional Conditions based on Semi-supervised Learning
Received:January 04, 2020  Revised:January 06, 2020
DOI:10.19753/j.issn1001-1390.2021.02.024
中文关键词: 电能表误差  现场检定  半监督学习
英文关键词: electrical  energy meter  error, on-site  verification, Semi-Supervised  Learning
基金项目:国家自然科学基金项目( 51807143),中国博士后科学基金(2018T220797),中国博士后科学基金(2017M612499)
Author NameAffiliationE-mail
Lu Yuxin School of Electrical Engineering and Automation,Wuhan University,Wuhan,430072 lyuxinzn@whu.edu.cn 
Fang Yanjun* School of Electrical Engineering and Automation,Wuhan University,Wuhan,430072 yjfang@whu.edu.cn 
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中文摘要:
      目前电能表现场检定的研究中有一个关键问题,在于如何利用相互独立的电能表单维实验误差获得多维实验误差。本文首先搭建了分别包括温度、谐波、磁场在内的三个独立实验平台,且每个平台均可控制电能表负载参数。然后设计了虚拟的多维交叉实验点,并提出一种半监督学习方法,实现单维实测误差数据向多维交叉实验数据的插值,获得电能表在多维条件实验下的误差数据。最后在综合实验平台中验证该方法的有效性和泛化性。
英文摘要:
      At present, there is a key problem in the field verification of electricity meters, which is how to obtain multi-dimensional experimental errors by using the electricity energy meter error from many unidimensional experiments which are independent of each other. In this paper, three independent experimental platforms, including temperature, harmonics and magnetic field, are built, and each platform can control the load parameters of the electricity meter. Then many virtual multi-dimensional experimental intersection are designed, and a semi-supervised learning method is proposed to obtain the electricity meter error under the multi-dimensional condition experiment. Finally, the effectiveness and generalization of the method are verified in a comprehensive experimental platform.
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