Incipient Fault Detection in Power Distribution System: A Time–Frequency Embedded Deep-Learning-Based Approach
Author:
Affiliation:
1. School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, China
2. Department of Computer and Network Engineering, The University of Electro-Communications, Chofu, Japan
Funder
National Natural Science Foundation of China
Anhui Provincial Natural Science Foundation
111 Project
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/19/10012124/10056403.pdf?arnumber=10056403
Reference46 articles.
1. Series Arc Fault Detection and Localization in DC Distribution System
2. High-Frequency Fault Analysis-Based Pilot Protection Scheme for a Distribution Network With High Photovoltaic Penetration
3. Novel Method Based on Variational Mode Decomposition and a Random Discriminative Projection Extreme Learning Machine for Multiple Power Quality Disturbance Recognition
4. High-impedance Fault Detection Method based on Stochastic Resonance for a Distribution Network with Strong Background Noise
5. A Sequential Bayesian Approach to Online Power Quality Anomaly Segmentation
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