Research on appliance recognition system based on improved transformer

Man Wang; Chenchen Jian; Yong Xiong; Cunliang Cheng

doi:10.1117/12.3039362

4 September 2024 Research on appliance recognition system based on improved transformer

Man Wang, Chenchen Jian, Yong Xiong, Cunliang Cheng

Author Affiliations +

Proceedings Volume 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024); 1325926 (2024) https://doi.org/10.1117/12.3039362
Event: Fourth International Conference on Automation Control, Algorithm, and Intelligent Bionics (ICAIB 2024), 2024, Yinchuan, China

Abstract

In response to the need for controlling unauthorized electrical appliances, we have developed a deep learning-based smart appliance recognition system. This paper proposes an innovative approach that effectively extracts features of appliance usage current, such as instantaneous fluctuations, peak currents, and transient changes caused by the starting or shutting down of appliances, using the Transformer's encoding layer. We refined the multi-head attention mechanism and removed the decoding module to simplify the model and focus on feature extraction. After the feature extraction phase, we employed ResNet as the feature mapping module, in conjunction with the enhanced Transformer. This model surpasses all previous models in identifying incremental current produced by appliances and is capable of adapting to the recognition of a large scale of appliances.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Man Wang, Chenchen Jian, Yong Xiong, and Cunliang Cheng "Research on appliance recognition system based on improved transformer", Proc. SPIE 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024), 1325926 (4 September 2024); https://doi.org/10.1117/12.3039362

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