Low-Voltage Biological Electric Shock Fault Diagnosis Based on the Attention Mechanism Fusion Parallel Convolutional Neural Network/Bidirectional Long Short-Term Memory Model

Low-Voltage Biological Electric Shock Fault Diagnosis Based on the Attention Mechanism Fusion Parallel Convolutional Neural Network/Bidirectional Long Short-Term Memory Model

Electric shock protection is critical for ensuring power safety in low-voltage grids, and robust fault diagnosis methods provide an essential foundation for the accurate operation of such protection devices. However, current low-voltage electric shock protection devices often suffer from limitations...

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Bibliographic Details
Main Authors: Meijin Lin, Yuliang Luo, Senjie Chen, Zhirong Qiu, Zibin Dai
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Mathematics
Subjects:
deep learning
fault diagnosis
low-voltage power grid
attention mechanism
biological electric shock
Online Access:https://www.mdpi.com/2227-7390/12/24/3984
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