A lightweight power quality disturbance recognition model based on CNN and Transformer

A lightweight power quality disturbance recognition model based on CNN and Transformer

A lightweight power quality disturbances (PQDs) recognition model that integrates convolutional neural network (CNN) and Transformer (CaT) is proposed to address the high number of parameters and computational complexity in existing deep learning-based models. Depthwise separable convolutions are fi...

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Bibliographic Details
Main Authors: ZHANG Bide, QIU Jie, LOU Guangxin, ZHOU Can, LUO Qingqing, LI Tianqian
Format: Article
Language:zho
Published: Editorial Department of Electric Power Engineering Technology 2025-01-01
Series:电力工程技术
Subjects:
power quality disturbances (pqds)
lightweight
number of parameters
efficient soft threshold block
depthwise separable convolution
transformer model
Online Access:https://www.epet-info.com/dlgcjsen/article/abstract/240907889
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