146 citations · 165 across the 2 of their papers we have counts for
6 papers
Fault Detection for Covered Conductors With High-Frequency Voltage Signals: From Local Patterns to Global Features
Kunjin Chen, Tomáš Vantuch, Yu Zhang +2
The detection and characterization of partial discharge (PD) are crucial for the insulation diagnosis of overhead lines with covered conductors. With the release of a large dataset…
Scale- and Context-Aware Convolutional Non-intrusive Load Monitoring
Kunjin Chen, Yu Zhang, Qin Wang +3
Non-intrusive load monitoring addresses the challenging task of decomposing the aggregate signal of a household's electricity consumption into appliance-level data without installi…
Fault Location in Power Distribution Systems via Deep Graph Convolutional Networks
Kunjin Chen, Jun Hu, Yu Zhang +2
This paper develops a novel graph convolutional network (GCN) framework for fault location in power distribution networks. The proposed approach integrates multiple measurements at…
Predicting Streamer Discharge Front Splitting by Ionization Seed Profiling
Yujie Zhu, Xuewei Zhang, Chijie Zhuang +2
Previous studies of streamer discharge branching mechanisms have mainly been generative other than predictive. To predict or even control branching, a reliable connection between e…
Convolutional Sequence to Sequence Non-intrusive Load Monitoring
Kunjin Chen, Qin Wang, Ziyu He +3
A convolutional sequence to sequence non-intrusive load monitoring model is proposed in this paper. Gated linear unit convolutional layers are used to extract information from the…
Short-term Load Forecasting with Deep Residual Networks
Kunjin Chen, Kunlong Chen, Qin Wang +3
We present in this paper a model for forecasting short-term power loads based on deep residual networks. The proposed model is able to integrate domain knowledge and researchers' u…