Open Access
Issue |
Int. J. Metrol. Qual. Eng.
Volume 13, 2022
|
|
---|---|---|
Article Number | 11 | |
Number of page(s) | 8 | |
DOI | https://doi.org/10.1051/ijmqe/2022013 | |
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]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.