Feature Enhancement Method for Weak Photovoltaic Series Arc Fault Signals

Silei Chen; Yu Meng; Jing Wang; Xingwen Li

doi:10.1109/HLM49214.2020.9307900

Feature Enhancement Method for Weak Photovoltaic Series Arc Fault Signals

Silei Chen
, Yu Meng
, Jing Wang
, Xingwen Li

School of Electrical Engineering

Xi'an University of Technology
Xi'an Jiaotong University
Shenzhen Power Supply Corporation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

For intensely burning photovoltaic (PV) series arc faults without strong noise interferences, their time-frequency features are easily to be discovered. However, various PV systems would generate noise interferences to the arc fault signal, causing difficulties to distinguish the arc fault and normal states. To solve this kind of problem, new measurements should be taken to acquire obvious arc fault features even from the weak arc fault electrical signals.In this paper, weak PV series arc fault electrical signals are acquired from the designed experimental setup with different load types firstly. Then it is found that the performance of arc fault features are not that satisfying in higher frequency bands after directly applying the existing Db9 based wavelet transform, causing the arc fault detection problem. Next, arc fault features are enhanced in most frequency bands by conducting the proposed Rbio3.1 based wavelet transform. Finally, the stochastic resonance (SR) method is proposed to further enhance Rbio3.1-based arc fault feature. The compared results prove that the combination between SR method and Rbio3.1 wavelet transform show the effective feature enhancement ability facing weak PV series arc fault electrical signals with different inverters and resistors.

Original language	English
Title of host publication	ELECTRICAL CONTACTS 2020 - Proceedings of the 66th IEEE Holm Conference on Electrical Contacts and Intensive Course, HLM 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	42-49
Number of pages	8
ISBN (Electronic)	9780738123592, 9781665422208
DOIs	https://doi.org/10.1109/HLM49214.2020.9307900
State	Published - 30 Sep 2020
Event	66th IEEE Holm Conference on Electrical Contacts and Intensive Course, HLM 2020 - San Antonio, United States Duration: 30 Sep 2020 → 7 Oct 2020

Publication series

Name	Electrical Contacts, Proceedings of the Annual Holm Conference on Electrical Contacts
Volume	2020-September
ISSN (Print)	0361-4395

Conference

Conference	66th IEEE Holm Conference on Electrical Contacts and Intensive Course, HLM 2020
Country/Territory	United States
City	San Antonio
Period	30/09/20 → 7/10/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Weak arc fault signal
different load types
feature enhancement
stochastic resonance
wavelet transform

Access to Document

10.1109/HLM49214.2020.9307900

Cite this

Chen, S., Meng, Y., Wang, J., & Li, X. (2020). Feature Enhancement Method for Weak Photovoltaic Series Arc Fault Signals. In ELECTRICAL CONTACTS 2020 - Proceedings of the 66th IEEE Holm Conference on Electrical Contacts and Intensive Course, HLM 2020 (pp. 42-49). Article 9307900 (Electrical Contacts, Proceedings of the Annual Holm Conference on Electrical Contacts; Vol. 2020-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HLM49214.2020.9307900

Chen, Silei ; Meng, Yu ; Wang, Jing et al. / Feature Enhancement Method for Weak Photovoltaic Series Arc Fault Signals. ELECTRICAL CONTACTS 2020 - Proceedings of the 66th IEEE Holm Conference on Electrical Contacts and Intensive Course, HLM 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 42-49 (Electrical Contacts, Proceedings of the Annual Holm Conference on Electrical Contacts).

@inproceedings{8b0d4e5063104c6f945de42c8699f2f0,

title = "Feature Enhancement Method for Weak Photovoltaic Series Arc Fault Signals",

abstract = "For intensely burning photovoltaic (PV) series arc faults without strong noise interferences, their time-frequency features are easily to be discovered. However, various PV systems would generate noise interferences to the arc fault signal, causing difficulties to distinguish the arc fault and normal states. To solve this kind of problem, new measurements should be taken to acquire obvious arc fault features even from the weak arc fault electrical signals.In this paper, weak PV series arc fault electrical signals are acquired from the designed experimental setup with different load types firstly. Then it is found that the performance of arc fault features are not that satisfying in higher frequency bands after directly applying the existing Db9 based wavelet transform, causing the arc fault detection problem. Next, arc fault features are enhanced in most frequency bands by conducting the proposed Rbio3.1 based wavelet transform. Finally, the stochastic resonance (SR) method is proposed to further enhance Rbio3.1-based arc fault feature. The compared results prove that the combination between SR method and Rbio3.1 wavelet transform show the effective feature enhancement ability facing weak PV series arc fault electrical signals with different inverters and resistors.",

keywords = "Weak arc fault signal, different load types, feature enhancement, stochastic resonance, wavelet transform",

author = "Silei Chen and Yu Meng and Jing Wang and Xingwen Li",

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Chen, S, Meng, Y, Wang, J & Li, X 2020, Feature Enhancement Method for Weak Photovoltaic Series Arc Fault Signals. in ELECTRICAL CONTACTS 2020 - Proceedings of the 66th IEEE Holm Conference on Electrical Contacts and Intensive Course, HLM 2020., 9307900, Electrical Contacts, Proceedings of the Annual Holm Conference on Electrical Contacts, vol. 2020-September, Institute of Electrical and Electronics Engineers Inc., pp. 42-49, 66th IEEE Holm Conference on Electrical Contacts and Intensive Course, HLM 2020, San Antonio, United States, 30/09/20. https://doi.org/10.1109/HLM49214.2020.9307900

Feature Enhancement Method for Weak Photovoltaic Series Arc Fault Signals. / Chen, Silei; Meng, Yu; Wang, Jing et al.
ELECTRICAL CONTACTS 2020 - Proceedings of the 66th IEEE Holm Conference on Electrical Contacts and Intensive Course, HLM 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 42-49 9307900 (Electrical Contacts, Proceedings of the Annual Holm Conference on Electrical Contacts; Vol. 2020-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Feature Enhancement Method for Weak Photovoltaic Series Arc Fault Signals

AU - Chen, Silei

AU - Meng, Yu

AU - Wang, Jing

AU - Li, Xingwen

PY - 2020/9/30

Y1 - 2020/9/30

N2 - For intensely burning photovoltaic (PV) series arc faults without strong noise interferences, their time-frequency features are easily to be discovered. However, various PV systems would generate noise interferences to the arc fault signal, causing difficulties to distinguish the arc fault and normal states. To solve this kind of problem, new measurements should be taken to acquire obvious arc fault features even from the weak arc fault electrical signals.In this paper, weak PV series arc fault electrical signals are acquired from the designed experimental setup with different load types firstly. Then it is found that the performance of arc fault features are not that satisfying in higher frequency bands after directly applying the existing Db9 based wavelet transform, causing the arc fault detection problem. Next, arc fault features are enhanced in most frequency bands by conducting the proposed Rbio3.1 based wavelet transform. Finally, the stochastic resonance (SR) method is proposed to further enhance Rbio3.1-based arc fault feature. The compared results prove that the combination between SR method and Rbio3.1 wavelet transform show the effective feature enhancement ability facing weak PV series arc fault electrical signals with different inverters and resistors.

AB - For intensely burning photovoltaic (PV) series arc faults without strong noise interferences, their time-frequency features are easily to be discovered. However, various PV systems would generate noise interferences to the arc fault signal, causing difficulties to distinguish the arc fault and normal states. To solve this kind of problem, new measurements should be taken to acquire obvious arc fault features even from the weak arc fault electrical signals.In this paper, weak PV series arc fault electrical signals are acquired from the designed experimental setup with different load types firstly. Then it is found that the performance of arc fault features are not that satisfying in higher frequency bands after directly applying the existing Db9 based wavelet transform, causing the arc fault detection problem. Next, arc fault features are enhanced in most frequency bands by conducting the proposed Rbio3.1 based wavelet transform. Finally, the stochastic resonance (SR) method is proposed to further enhance Rbio3.1-based arc fault feature. The compared results prove that the combination between SR method and Rbio3.1 wavelet transform show the effective feature enhancement ability facing weak PV series arc fault electrical signals with different inverters and resistors.

KW - Weak arc fault signal

KW - different load types

KW - feature enhancement

KW - stochastic resonance

KW - wavelet transform

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DO - 10.1109/HLM49214.2020.9307900

M3 - 会议稿件

AN - SCOPUS:85099702274

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EP - 49

BT - ELECTRICAL CONTACTS 2020 - Proceedings of the 66th IEEE Holm Conference on Electrical Contacts and Intensive Course, HLM 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 66th IEEE Holm Conference on Electrical Contacts and Intensive Course, HLM 2020

Y2 - 30 September 2020 through 7 October 2020

ER -

Chen S, Meng Y, Wang J, Li X. Feature Enhancement Method for Weak Photovoltaic Series Arc Fault Signals. In ELECTRICAL CONTACTS 2020 - Proceedings of the 66th IEEE Holm Conference on Electrical Contacts and Intensive Course, HLM 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 42-49. 9307900. (Electrical Contacts, Proceedings of the Annual Holm Conference on Electrical Contacts). doi: 10.1109/HLM49214.2020.9307900

Feature Enhancement Method for Weak Photovoltaic Series Arc Fault Signals

Abstract

Publication series

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UN SDGs

Keywords

Access to Document

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