Int. J. Metrol. Qual. Eng.
Volume 13, 2022
|Number of page(s)||8|
|Published online||13 October 2022|
- T. Crnko, S. Dyrnes, Arcing fault hazards and safety suggestions for design and maintenance, IEEE Ind. Appl. Mag. 3 , 23–32 (2001) [CrossRef] [Google Scholar]
- J.H. Du, R. Tu, Y. Zeng, L. Pan, R.C. Zhang, An experimental study on the thermal characteristics and heating effect of arc-fault from Cu core in residential electrical wiring fires, PLoS ONE 12 , e0182811 (2017) [CrossRef] [PubMed] [Google Scholar]
- Y. Liu, J. Zheng, L. Li, Analysis of characteristics of fault arc in series under influence of ambient humidity, Proc. CSU- EPSA 08 , 7–12 (2019) [Google Scholar]
- J.P. Pulkkinen, Commercial arc fault detection devices in military electromagnetic environment, IEEE Electromagn. Compat. Mag. 4 , 49–52 (2018) [CrossRef] [Google Scholar]
- Q. Lu, Z. Ye, Y. Zhang, T. Wang, Z. Gao, Analysis of the effects of arc volt-ampere characteristics on different loads and detection methods of series arc faults, Energies 12 , 323 (2019) [CrossRef] [Google Scholar]
- X. Qin, Y. Liu, P. Sun, Study on the line fault root-cause identification method in distribution networks based on time-frequency characteristics of fault waveforms, Chinese J. Sci. Instrum. 1 , 41–49 (2017) [Google Scholar]
- G. Artale, A. Cataliotti, V. Cosentino, D. Di Cara, S. Nuccio, G. Tinè, Arc fault detection method based on CZT low-frequency harmonic current analysis, IEEE Trans. Instrum. Measur. 5 , 888–896 (2017) [CrossRef] [Google Scholar]
- Y. Abdullah, B. Hu, Z. Wei, J. Wang, A. Emrani, Adaptive detection of DC Arc faults based on hurst exponents and current envelope, IEEE Appl. Power Electr. Conf. Exposition (APEC), 3392–3397 (2018) [Google Scholar]
- H. Zhao, J. Liu, J. Lou, Series arc fault detection based on current fluctuation and zero-current features, Electr. Power Syst. Res. 202 , 107626 (2022) [CrossRef] [Google Scholar]
- K. Yang, R. Zhang, S. Chen, F. Zhang, J. Yang, X. Zhang, Series arc fault detection algorithm based on autoregressive bispectrum analysis, Algorithms 8 , 929–950 (2015) [CrossRef] [Google Scholar]
- S.B. Lu, B.T. Phung, D.M. Zhang, A comprehensive review on DC arc faults and their diagnosis methods in photovoltaic systems, Renew. Sustain. Energy Rev. 89 , 88–98 (2018) [CrossRef] [Google Scholar]
- Q. Yu, G. Huang, Y. Yang, Y. Sun, Series arc fault detection method based on AlexNet deep learning network, J. Electr. Meas. Instrum. 03 , 145–152 (2019) [Google Scholar]
- Z. Jiao, T. Li, L. Wang, L. Mou, A. Khalyasmaa, Dc series arc fault detection of photovoltaic system based on convolution neural network, Adv. Technol. Electr. Eng. Energy. 07 , 29–34 (2019) [Google Scholar]
- Y. Wang, F. Zhang, S. Zhang, A new methodology for identifying arc fault by sparse representation and neural network, IEEE Trans. Instrum. Meas. 11 , 2526–2537 (2018) [CrossRef] [Google Scholar]
- K. Yang, R. Chu, R. Zhang, J. Xiao, R. Tu, A novel methodology for series arc fault detection by temporal domain visualization and convolutional neural network, Sensors 1 , 162 (2020) [Google Scholar]
- Q. Yu, Y. Hu, Y. Yang, Identification method for series arc faults based on wavelet transform and deep neural network, Energies 13 , 142 (2020) [Google Scholar]
- Y. Wang, F. Zhang, S. Zhang, G. Yang, A novel diagnostic algorithm for AC series arcing based on correlation analysis of high-frequency component of wavelet, COMPEL. 1 , 271–288 (2017) [CrossRef] [Google Scholar]
- M.E. Torres, M.A. Colominas, G. Schlotthauer, P. Flandrin, A complete ensemble empirical mode decomposition with adaptive noise, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2011) pp. 4144–4147 [Google Scholar]
- W.-Y. Zhang, Z.-W. Wei, B.-H. Wang, X.-P. Han, Measuring mixing patterns in complex networks by Spearman rank correlation coefficient, Physica A 451 , 440–450 (2016) [CrossRef] [Google Scholar]
- D.E. Rumelhart, G.E. Hinton, R.J. Williams, Learning representations by back-propagating errors, Nature 323 , 533–53 (1986) [CrossRef] [Google Scholar]
- General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China: Electrical Fire Monitoring System-Part 4: Arcing Fault Detectors (GB 1428 7.4-2014) (Standards Press of China: Beijing, China, 2014) [Google Scholar]
- Underwriters Laboratories Inc., UL Standard for Arc-Fault Circuit-Interrupters, 2nd edn., (Underwriters Laboratories Inc.: New York, NY, 2011) [Google Scholar]
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