Deep Domain-Invariant Long Short-Term Memory Network for Partial Discharge Localization in Gas-Insulated Switchgear
Author:
Affiliation:
1. State Key Laboratory of Electrical Insulation and Power Equipment, Department of Electrical Engineering, Xi'an Jiaotong University, Xi'an, China
2. Department of Computer Science, Xi'an Jiaotong University, Xi'an, China
Funder
National Key Research and Development Program of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology
Link
http://xplorestaging.ieee.org/ielx7/61/10192508/10086670.pdf?arnumber=10086670
Reference34 articles.
1. A novel adversarial transfer learning in deep convolutional neural network for intelligent diagnosis of gas‐insulated switchgear insulation defect
2. Gas-insulated switchgear insulation defect diagnosis via a novel domain adaptive graph convolutional network;wang;IEEE Trans Instrum Meas,2022
3. Remaining useful life prediction of bearings under different working conditions using a deep feature disentanglement based transfer learning method
4. Transfer learning for remaining useful life prediction of multi-conditions bearings based on bidirectional-GRU network
5. Deep residual LSTM with domain-invariance for remaining useful life prediction across domains
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3. Domain-alignment multitask learning network for partial discharge condition assessment with digital twin in gas-insulated switchgear;Measurement Science and Technology;2024-03-21
4. Mutitask Learning Network for Partial Discharge Condition Assessment in Gas-Insulated Switchgear;IEEE Transactions on Industrial Informatics;2024
5. Simultaneous Partial Discharge Diagnosis and Localization in Gas-Insulated Switchgear via a Dual-Task Learning Network;IEEE Transactions on Power Delivery;2023-12
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