Y. Wang, F. Zhang, X. Zhang and S. Zhang, “Series AC Arc Fault Detection Method Based on Hybrid Time and Frequency Analysis and Fully Connected Neural Network,” IEEE Trans. Ind. Informat., vol. 15, no. 12, pp. 6210-6219, Dec. 2019.

S. A. Saleh, M. E. Valdes, C. S. Mardegan and B. Alsayid, “The State-of-the-Art Methods for Digital Detection and Identification of Arcing Current Faults,” IEEE Trans. Industry Appl., vol. 55, no. 5, pp. 4536-4550, Sept.-Oct. 2019.

Y. Wang, D. Sheng, H. Hu, K. Han, J. Zhou and L. Hou, “A Novel Series Arc Fault Detection Method Based on Mel-Frequency Cepstral Coefficients and Fully Connected Neural Network,” IEEE Access, vol. 10, pp. 97983-97994, Sep. 2022.

Y. Wang, L. Hou, K. C. Paul, Y. Ban, C. Chen and T. Zhao, “ArcNet: Series AC Arc Fault Detection Based on Raw Current and Convolutional Neural Network,” IEEE Trans. Ind. Informat., vol. 18, no. 1, pp. 77-86, Jan. 2022.

P. Qi, S. Jovanovic, J. Lezama and P. Schweitzer, “Discrete wavelet transform optimal parameters estimation for arc fault detection in low-voltage residential power networks,” Elect. Power Syst. Res., vol. 143, pp. 130-139, Feb. 2017.

General Requirements for Arc Fault Detection Devices, no. IEC 62606, 2013.

Z. Wang, S. Tian, H. Gao, C. Han and F. Guo, “An On-Line Detection Method and Device of Series Arc Fault Based on Lightweight CNN,” IEEE Trans. Ind. Informat., vol. 19, no. 10, pp. 9991-10003, Oct. 2023.

F. A. S. Borges, R. A. S. Fernandes, I. N. Silva and C. B. S. Silva, “Feature Extraction and Power Quality Disturbances Classification Using Smart Meters Signals,” IEEE Trans. Ind. Informat., vol. 12, no. 2, pp. 824-833, April 2016.