Series AC Arc Fault Detection Using Decision Tree-Based Machine Learning Algorithm and Raw Current

Author:

Paul Kamal Chandra1,Schweizer Linus2,Zhao Tiefu1,Chen Chen3,Wang Yao4

Affiliation:

1. University of North Carolina at Charlotte,Dept. of Electrical and Computer Engineering,Charlotte,NC,USA

2. Karlsruhe Institute of Technology,Dept. Industrial Engineering & Management,Karlsruhe,Germany

3. University of Central Florida,Center for Research in Computer Vision,Orlando,FL,USA

4. School of Electrical Engineering, Hebei University of Technology,Tianjin,China

Publisher

IEEE

Cited by 6 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. Investigating THD for Series Arc Fault Detection in Single-phase Electrical Networks;2024 6th International Conference on Energy, Power and Environment (ICEPE);2024-06-20

2. Advanced Anomaly Detection in Manufacturing Processes: Leveraging Feature Value Analysis for Normalizing Anomalous Data;Electronics;2024-04-05

3. Detection of Arc Fault by using ML Algorithm;2024 Fourth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT);2024-01-11

4. Research on AC Arc Fault Detection Method Based on Wigner-Hough Transform and NG-Boost;2023 IEEE 4th International Conference on Electrical Materials and Power Equipment (ICEMPE);2023-05-07

5. A Comparative Study for the Detection of Stator Inter-Turn Faults in Induction Motors Using Shallow Neural Networks and Non-Neural Based Techniques;2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET);2023-04-29

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