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文章摘要
基于非侵入式的事件检测方法统计评估
Statistical assessment of abrupt change detections for NILM
Received:May 16, 2019  Revised:May 16, 2019
DOI:10.19753/j.issn1001-1390.2020.001.014
中文关键词: 非侵入式负荷监测  事件检测  二维信号  决策函数  统计评估
英文关键词: Non-intrusive Load Monitoring  Abrupt Change Detection  Multi-dimensional signal  Decision Function  Statistical
基金项目:国家自然科学(51437006);突尼斯高等教育与科学研究部资助项目
Author NameAffiliationE-mail
Zhang Lu Electric Power College,South China University of Technology 1204122793@qq.com 
Xiao Jiang Electric Power College,South China University of Technology xiaojiang@scutem.com 
Jing Zhaoxia* Electric Power College,South China University of Technology zxjing@scut.edu.cn 
Sarra Houidi Université de Nantes,Nantes ,France sarra.houidi@etu.univ-nantes.fr 
Huu Kien Bui Université de Nantes,Nantes ,France huu-kien.bui@univ-nantes.fr 
Xiao Jiang 1.华南理工大学;2.法国南特大学  
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中文摘要:
      非侵入式负荷监测是负荷监测的重要发展方向,事件检测是非侵入式负荷监测的重点研究内容。多维信号相比一维信号可以提供多源信息,若信号不同维度间相关度大,则可以提高检测精度。本文基于统计假设首次推导BIC、CUSUM和GLRT三种算法的决策函数,并以二维信号为例进行仿真实验,比较了三种算法的检测结果。仿真实验证明补充合适的第二维信号可以提高整体检测精度,且得到不同算法的适用条件,即CUSUM算法适用于高阈值检测,GLRT算法适用于低阈值检测。
英文摘要:
      Non-intrusive load monitoring is an important development direction of load monitoring, and event detection is the key research content of non-intrusive load monitoring. Multidimensional signals can provide multi-source information compared with one-dimensional signals. If the correlation between different dimensions of signals is large, the detection accuracy can be improved. In this paper, the decision functions of BIC, CUSUM and GLRT are deduced for the first time based on statistical hypothesis, and two-dimensional signals are simulated to compare the results of the three algorithms. The simulation results show that adding the appropriate second dimension signal can improve the overall detection accuracy, and the applicable conditions of different algorithms are obtained. That is, CUSUM algorithm is suitable for high threshold detection, and GLRT algorithm is suitable for low threshold detection.
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