Research on Switchgear Partial Discharge Signal Type Identification Based on Composite Neural Network
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-7393-4_15
Reference14 articles.
1. Heli NI, Weiqiang YAO, Chenzhao FU et al (2022) Review of the status of technical standards for partial discharge of power equipment. High Voltage Apparatus 58(03):1–15 (in Chinese)
2. Pan W, Chen X, Zhao K (2022) Cable-partial-discharge recognition based on a data-driven approach with optical-fiber vibration-monitoring signals. Energies 15(15):5686–5686
3. Jianfeng Z et al (2022) GIS partial discharge pattern recognition based on time-frequency features and improved convolutional neural network. Energies 15(19):7372–7372
4. He J, Tian T, Song X et al (2020) Research on the identification method of partial discharge in switchgear based on UHF method. High Voltage Apparatus 56(11):90–95+101. (in Chinese)
5. Xi C et al (2022) Feature extraction of partial discharge in low-temperature composite insulation based on VMD-MSE-IF. CAAI Trans Intell Technol 7(2):301–312
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