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Article Dans Une Revue Electrical Measurement and Instrumentation Année : 2020

Statistical assessment of abrupt change detections for NILM

Résumé

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 twodimensional 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.
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Dates et versions

hal-04085555 , version 1 (29-04-2023)

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Lu Zhang, François Auger, Zhaoxia Jing, Huu Kien Bui, Jiang Xiao. Statistical assessment of abrupt change detections for NILM. Electrical Measurement and Instrumentation, 2020, 57 (1), pp.1-8. ⟨10.19753/j.issn1001-1390.2020.001.014⟩. ⟨hal-04085555⟩
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