A Two-Terminal Fault Location Fusion Model of Transmission Line Based on CNN-Multi-Head-LSTM with an Attention Module

A Two-Terminal Fault Location Fusion Model of Transmission Line Based on CNN-Multi-Head-LSTM with an Attention Module

Most traditional artificial intelligence-based fault location methods are very dependent on fault signal selection and feature extraction, which is often based on prior knowledge. Further, these methods are usually very sensitive to line parameters and selected fault characteristics, so the generali...

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Bibliographic Details
Main Authors: Chao Su, Qiang Yang, Xiaomei Wu, Chun Sing Lai, Loi Lei Lai
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Energies
Subjects:
fault location
convolutional neural network
long short-term memory
attention module
Online Access:https://www.mdpi.com/1996-1073/16/4/1827

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https://www.mdpi.com/1996-1073/16/4/1827

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