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Multichannel Spatio-Temporal Feature Fusion Method for NILM | IEEE Journals & Magazine | IEEE Xplore

Multichannel Spatio-Temporal Feature Fusion Method for NILM


Abstract:

The main task of noninvasive load monitoring is to disaggregate the power consumption of a single household appliance from an electricity meter that detects the power con...Show More

Abstract:

The main task of noninvasive load monitoring is to disaggregate the power consumption of a single household appliance from an electricity meter that detects the power consumption of all household appliances. The deep neural network method has achieved leading results in this field. In this article, a multichannel spatio-temporal feature fusion method is proposed, where the spatial features extracted by convolution neural network and the temporal features extracted by the recurrent neural network are fused. And the attention module is introduced to further improve the performance of the model. Finally, the effectiveness and superiority of the proposed method are verified on three public datasets.
Published in: IEEE Transactions on Industrial Informatics ( Volume: 18, Issue: 12, December 2022)
Page(s): 8735 - 8744
Date of Publication: 04 February 2022

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