Improved Control Strategy for Carbonized Cable Preparation in Low-voltage Arc Fault Test*

doi:10.23919/CJEE.2023.000038

中国电气工程学报（英文） ›› 2023, Vol. 9 ›› Issue (4): 122-131.doi: 10.23919/CJEE.2023.000038

收稿日期:2023-07-07 修回日期:2023-08-12 接受日期:2023-09-01 发布日期:2024-01-08

Improved Control Strategy for Carbonized Cable Preparation in Low-voltage Arc Fault Test^*

Liwei Du^1,2,3,4, Zhihong Xu^1,2,3,*, Duanyu Chen⁴

1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China;
2. Fujian Key Laboratory of New Energy Generation and Power Conversion, Fuzhou University, Fuzhou 350108, China;
3. Fujian Province University Engineering Research Center of Smart Distribution Grid Equipment, Fuzhou University, Fuzhou 350108, China;
4. Department of Electrical Engineering, Yuan Ze University, Taiwan 32003, China

Received:2023-07-07 Revised:2023-08-12 Accepted:2023-09-01 Published:2024-01-08
Contact: *E-mail: fdxzh@fzu.edu.cn
About author:Liwei Du received the B.S. degree in Electrical Engineering and Automation from Henan Polytechnic University, Jiaozuo, China, in 2016, and M.S. degree from the Solar Energy Research Institute, Kunming, Yunnan Normal University, Kunming, China, in 2019. Since 2020, he has been working toward a Ph.D. at the School of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China. Since 2023, he has been pursuing his Ph.D. degree in the Department of Electrical Engineering, Yuan Ze University, Taiwan, China. His research interests include arc-fault diagnosis, electrical fires, and power quality.
Zhihong Xu (Member, IEEE) received the B.S. and M.S. degrees in Electrical Engineering and Ph.D. degrees in Electric Machines and Electric Apparatus from Fuzhou University, Fuzhou, China in 1983, 1998, and 2006, respectively.
She is currently the Dean of the College of Electrical Engineering and Automation, Fuzhou University. Her research interests include the intelligent control of electrical appliances and online monitoring.
Professor Xu was a recipient of the Science and Technology Innovation Leadership in Fujian Province in 2018.
Duanyu Chen (Member, IEEE) received the B.S. degree in Computer Science and Information Engineering from Chaio-Tung University, Taiwan, China in 1996, an M.S. degree in Computer Science from Sun Yat-Sen University, Taiwan, China in 1998, and a Ph.D. degree in Computer Science and Information Engineering from Chiao-Tung University, Taiwan, China in 2004. He was a Postdoctoral Research Fellow with Academia Sinica, Taipei, China, between 2004-2008. He was an Assistant Professor with the Department of Electrical Engineering, Yuan Ze University, Taiwan, China, from 2009 to 2013. He is currently a Professor and the Chairman with the Department of Electrical Engineering, Yuan Ze University, Taiwan, China. His research interests include computer vision, video-signal processing, content-based video indexing and retrieval, and multimedia information systems.
Prof. Chen is a recipient of the Young Scholar Research Award presented by Yuan Ze University, Taiwan, China, in 2012.
Supported by:
* National Natural Science Foundation of China (52277136), the University Production-Study Cooperation Project of Science and Technology Department of Fujian Province (2021Y4002), the 2018 Funding Program for Leading Talents in Scientific and Technological Innovation of Fujian (038000387024), and Natural Science Foundation of Fujian Province (2020J05170).

摘要/Abstract

Abstract: Outdated testing methods hinder the success rate of carbonized cable preparation in low-voltage arc fault tests, leading to incomplete tests and high failure rates. To address this issue, we finely categorized the preparation results of carbonized cable specimens by analyzing the experimental phenomena during the carbonization process and assessing the impact of high-voltage energization time on the outcomes, presenting a process control strategy aimed at optimizing the preparation results of carbonized cable specimens. This method utilizes three periodic moving algorithms (root-mean-square, average, and shoulder percentage) to classify the cable specimens into four preparation categories: open-circuit carbonization, under-carbonization, short-circuit carbonization, and successful carbonization. The high-voltage energization time during carbonization or secondary carbonization was adjusted to optimize the preparation of the carbonized cables by considering different discrimination outcomes. Finally, the proposed method was tested on a purpose-built carbonized cable experimental platform, which confirmed its effectiveness in differentiating the preparation outcomes of the carbonized cable specimens and improving the success rate of the carbonized cable preparation. The proposed method has significant potential for application in low-voltage arc fault test systems.

Key words: Arc fault test, carbonized cable preparation, carbonized conductive path, process control strategy

. [J]. 中国电气工程学报（英文）, 2023, 9(4): 122-131.

Liwei Du, Zhihong Xu, Duanyu Chen. Improved Control Strategy for Carbonized Cable Preparation in Low-voltage Arc Fault Test^*[J]. Chinese Journal of Electrical Engineering, 2023, 9(4): 122-131.

参考文献

[1] J Yang, H Fang, R Zhang, et al.An arc fault diagnosis algorithm using multiinformation fusion and support vector machines.Royal Society Open Science, 2018, 5(9): 180160.
[2] J Andrea, P Schweitzer, E Carvou.Comparison of equations of the VI characteristics of an electric arc in open air. 2019 IEEE Holm Conference on Electrical Contacts, September 14-18, 2019, Milwaukee, WI, USA. IEEE, 2019: 76-81.
[3] S Jovanovic, A Chahid, J Lezama, et al.Shunt active power filter-based approach for arc fault detection.Electric Power Systems Research, 2016, 141: 11-21.
[4] F Ferracuti, P Schweitzer, A Monteriù.Arc fault detection and appliances classification in AC home electrical networks using recurrence quantification plots and image analysis.Electric Power Systems Research, 2021, 201: 107503.
[5] Y Wang, L Hou, K C Paul, et al.ArcNet: Series AC arc fault detection based on raw current and convolutional neural network.IEEE Transactions on Industrial Informatics, 2021, 18(1): 77-86.
[6] Y Wang, D Sheng, H Hu, et al.A novel series arc fault detection method based on mel-frequency cepstral coefficients and fully connected neural network.IEEE Access, 2022. 10: 97983-97994.
[7] W S Moon, J C Kim, A Jo, et al.Ignition characteristics of residential series arc faults in 220-V HIV wires.IEEE Transactions on Industry Applications, 2014, 51(3): 2054-2059.
[8] K Takenaka, Y Ishikawa, Y Mizuno, et al.Arc discharge-induced ignition of combustibles placed on a damaged AC power supply cord.Energies, 2020, 13(3): 681.
[9] Underwriters Laboratories Inc.UL standard for safety for arc-fault circuit-interrupters (Third Edition). UL 1699. New York: Underwriters Laboratories Inc., 2017.
[10] General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China, Standardization Administration of the People's Republic of China. General requirements for arc fault detection devices (AFDD). GB/T 31143. Beijing: Standards Press of China, 2014.
[11] J Su, Z Xu, C Zhang.Design of test system for arc fault protection switch. 2018 3rd International Conference on Intelligent Green Building and Smart Grid (IGBSG), April 22-25, 2018, Yilan, Taiwan, China. IEEE, 2018: 1-4.
[12] G A Qabbani.Tests of series arcing and arc fault detection devices in low voltage systems. Stockholm: KTH Royal Institute of Technology, 2021.
[13] International Electrotechnical Commission.General requirements for arc fault detection devices (Edition 1.1). IEC 62606. Geneva: International Electrotechnical Commission, 2017.
[14] J Su, Z Xu.Test and analysis system for action characteristics of arc fault detection device.Electric Power Automation Equipment, 2019, 39(10): 194-200.
[15] J Shea.Comparing 240 Vrms to 120 Vrms series arcing faults in residential wire. 2008 Proceedings of the 54th IEEE Holm Conference on Electrical Contacts (HOLM), October 27-29, 2008, Orlando, FL, USA. IEEE, 2008: 218-224.
[16] L Du, Z Xu.Analysis and judgment of cable carbonization path based on arc fault test system.Electric Power Automation Equipment, 2022, 42(12): 217-224.
[17] L Lv, C Duan, S Ji, et al.Overview of ignition mechanism and combustion characteristic of wire and cable.High Voltage Engineering, 2022, 48(2): 612-625.
[18] J Shea.Identifying causes for certain types of electrically initiated fires in residential circuits.Fire and Materials, 2011, 35(1): 19-42.
[19] L Du, M Li, Z Tang, et al.A fast positive sequence components extraction method with noise immunity in unbalanced grids.IEEE Transactions on Power Electronics, 2019, 35(7): 6682-6685.
[20] L Xiong, X Liu, Y Liu.Decaying DC and harmonic components detection for absorbing impact load currents in weak grids.IEEE Transactions on Power Delivery, 2020, 36(3): 1907-1910.
[21] L Du, L Xiong, M Li, et al.Detection scheme of positive sequence components based on operation period delay filter.CSEE Journal of Power and Energy Systems, 2023, 9(1): 235-243.
[22] Z Zhang, J Ren, X Tang, et al.Novel approach for arc fault identification with transient and steady state based time-frequency analysis.IEEE Transactions on Industry Applications, 2022, 58(4): 4359-4369.

Improved Control Strategy for Carbonized Cable Preparation in Low-voltage Arc Fault Test^*

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics

本文评价