An unsupervised Gaussian mixer model for detection and localization of partial discharge sources using RF sensors
Author:
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/94/8032560/08035436.pdf?arnumber=8035436
Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Machine Learning Applications for Online Partial Discharge Detection, Classification, and Localization in Power Transformers: A Review;2024 4th International Conference on Smart Grid and Renewable Energy (SGRE);2024-01-08
2. PCA-Enhanced Methodology for the Identification of Partial Discharge Locations;Energies;2023-09-11
3. Clustering by communication with local agents for noise and multiple partial Discharges discrimination;Expert Systems with Applications;2023-09
4. Improved Methods for UHF Localization of Partial Discharge in Air-Insulated Substations;Energies;2023-05-20
5. Partial Discharge Localization Techniques: A Review of Recent Progress;Energies;2023-03-20
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