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。文章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。
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. Multi-dimensional 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 detection results of the three algorithms. The simulation results show that adding the appropriate two-dimensional signal can improve the overall detection accuracy,and the applicable conditions of different algorithms are obtained,which means the CUSUM algorithm is suitable for high threshold detection,and GLRT algorithm is suitable for low threshold detection.
作者
张露
Francois Auger
荆朝霞
Sarra Houidi
Huu Kien Bui
肖江
Zhang Lu;Franois Auger;Jing Zhaoxia;Sarra Houidi;Huu Kien Bui;Xiao Jiang(School of Electric Power,South China University of Technology,Guangzhou 510640,China;Universitéde Nantes,Nantes 44600,France)
出处
《电测与仪表》
北大核心
2020年第1期106-112,120,共8页
Electrical Measurement & Instrumentation
基金
国家自然科学基金资助项目(51437006)
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
non-intrusive load monitoring
abrupt change detection
multi-dimensional signal
decision function
statistical assessment
