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A Method of DC Arc Detection in All-Electric Aircraft

Author

Listed:
  • Teng Li

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Zhijie Jiao

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Lina Wang

    (School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China)

  • Yong Mu

    (Tangshan Power Supply Company of State Grid Jibei Electric Power Co., Ltd., Tangshan 063000, China)

Abstract

Arc faults in an aircraft’s power distribution system (PDS) often leads to cable and equipment damage, which seriously threatens the personal safety of the passengers and pilots. An accurate and real-time arc fault detection method is needed for the Solid-State Power Controller (SSPC), which is a key protection equipment in a PDS. In this paper, a new arc detection method is proposed based on the improved LeNet5 Convolutional Neural Network (CNN) model after a Time–Frequency Analysis (TFA) of the DC currents was obtained, which makes the arc detection more real-time. The CNN is proposed to detect the DC arc fault for its advantage in recognizing more time–frequency joint details in the signals; the new structure also combines the adaptive and multidimensional advantages of the TFA and image intelligent recognition. It is confirmed by experimental data that the combined TFA–CNN can distinguish arc faults accurately when the whole training database has been repeatedly trained 3 to 5 times. For the TFA, two kinds of methods were compared, the Short-Time Fourier Transform (STFT) and Discrete Wavelet Transform (DWT). The results show that DWT is more suitable for DC arc fault detection. The experimental results demonstrated the effectiveness of the proposed method.

Suggested Citation

  • Teng Li & Zhijie Jiao & Lina Wang & Yong Mu, 2020. "A Method of DC Arc Detection in All-Electric Aircraft," Energies, MDPI, vol. 13(16), pages 1-14, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:16:p:4190-:d:398643
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    References listed on IDEAS

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    1. Xinran Li & Chenyun Pan & Dongmei Luo & Yaojie Sun, 2020. "Series DC Arc Simulation of Photovoltaic System Based on Habedank Model," Energies, MDPI, vol. 13(6), pages 1-16, March.
    2. Lu, Shibo & Phung, B.T. & Zhang, Daming, 2018. "A comprehensive review on DC arc faults and their diagnosis methods in photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 88-98.
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    Cited by:

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    2. Othman Alshamrani & Adel Alshibani & Awsan Mohammed, 2022. "Operational Energy and Carbon Cost Assessment Model for Family Houses in Saudi Arabia," Sustainability, MDPI, vol. 14(3), pages 1-18, January.
    3. Chenying Li & Jie Chen & Wei Zhang & Libing Hu & Jingying Cao & Jianjun Liu & Zhenyu Zhu & Shuqun Wu, 2021. "Influence of Arc Size on the Ignition and Flame Propagation of Cable Fire," Energies, MDPI, vol. 14(18), pages 1-14, September.

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