DC Arc Failure Detection based on Division of Time and Frequency Components using Intelligence Models
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s42835-024-02001-8.pdf
Reference22 articles.
1. S. Lu, B. T. Phung and D. Zhang. 2017 "Study on DC series arc fault in photovoltaic systems for condition monitoring purpose". Australasian Universities Power Engineering Conference (AUPEC). Melbourne. VIC. Australia. 1 6
2. H. Chen, X. Liu, H. Shi, M. Chen and J. Zheng, "DC Series Arc Fault Diagnosis and Feature Extraction," 2023 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices (ASEMD), Tianjin, China, 2023, pp. 1-2, https://doi.org/10.1109/ASEMD59061.2023.10369057.
3. SN Ananthan "Signatures of Series Arc Faults to Aid Arc Detection in Low-Voltage DC Systems," et al 2020 IEEE Power & Energy Society General Meeting (PESGM) Montreal, QC, Canada 2020 1 5 https://doi.org/10.1109/PESGM41954.2020.9281618
4. Psaras V et al (2022) Review of DC series Arc fault testing methods and capability assessment of test platforms for more-electric aircraft. IEEE Transa Transp Electrific 8(4):4654–4667. https://doi.org/10.1109/TTE.2022.3189970
5. Chae S, Park J, Oh S (2016) Series DC Arc fault detection algorithm for DC microgrids using relative magnitude comparison. IEEE J Emerg Sel Top Power Electron 4(4):1270–1278. https://doi.org/10.1109/JESTPE.2016.2592186
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