A Study on the Localization of Partial Discharge Using Ngccphat CNN
Author:
Affiliation:
1. Lanzhou Jiaotong University,Institute of Digital Signal Processing and Software Defined Radio, School of Electronics and Information Engineering,Lanzhou,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10428934/10429048/10429100.pdf?arnumber=10429100
Reference15 articles.
1. Feature Engineering and Classification Models for Partial Discharge in Power Transformers;Wang;arXiv,2022
2. Initial Experience with Acoustic Imaging of PD on High Voltage Equipment
3. BeamLearning: An end-to-end deep learning approach for the angular localization of sound sources using raw multichannel acoustic pressure data
4. Deep Ensemble Model for Unknown Partial Discharge Diagnosis in Gas-Insulated Switchgears Using Convolutional Neural Networks
5. Research on TDOA calculation algorithms of ultrasonic signal for PD
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