Error Analysis of UHF Partial Discharge Monitoring System Based on Ensemble Empirical Mode Decomposition

被引：0

作者：

Liang, Xing ^{[1
]}

Shi, Meng-Qi ^{[2
]}

Wu, Hua ^{[1
]}

Wang, Xian-Pei ^{[3
]}

Zhou, Wei ^{[4
]}

Wang, Quan ^{[4
]}

机构：

[1] State Grid Chongqing Elect Power CO, Elect Power Res Inst, Chongqing, Peoples R China

[2] China Three Gorges Univ, Coll Elect Engn & New Energy, Yichang, Peoples R China

[3] Wuhan Univ, Sch Elect Informat, Wuhan, Hubei, Peoples R China

[4] China Elect Power Res Inst, Wuhan, Hubei, Peoples R China

来源：

2017 9TH INTERNATIONAL CONFERENCE ON MODELLING, IDENTIFICATION AND CONTROL (ICMIC 2017) | 2017年

关键词：

UHF partial discharge monitoring system; error analysis; Ensemble Empirical Mode Decomposition; error signal decomposition;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The ultra-high frequency (UHF) partial discharge monitoring device which is now used in power grid has the phenomenon of lacking the accuracy of measurement as well as the outcome reliability. In order to improve the metrical precision of UHF partial discharge monitoring system and analyze the features of its error, the analytical method of dynamic measurement system based on Ensemble Empirical Mode Decomposition is provided in this paper. When mutation or interval exists in the signal component of the original signal, using Empirical Mode Decomposition may lead to modal aliasing phenomenon. Otherwise, the Ensemble Empirical Mode Decomposition overcomes the defect in truncated signal and restrained the modal aliasing phenomenon at a certain extent. By using simulation, the Ensemble Empirical Mode Decomposition can make the error signal adaptively decompose into several simple signal so it brings us some convenient in research and finally validates the availability of our method.

引用

页码：1003 / 1007

页数：5

共 50 条

[1] Ensemble Empirical Mode Decomposition for the denoising of partial discharges measured in UHF
Rojas-Moreno, M. V.
Robles, G.
Martinez-Tarifa, J. M.
Fresno, J. M.
2016 IEEE INTERNATIONAL CONFERENCE ON DIELECTRICS (ICD), VOLS 1-2, 2016, : 963 - 966
[2] Partial Discharge Feature Extraction Based on Ensemble Empirical Mode Decomposition and Sample Entropy
Shang, Haikun
Lo, Kwok Lun
Li, Feng
ENTROPY, 2017, 19 (09):
[3] Parallel Ensemble Empirical Mode Decomposition and Its Application in Feature Extraction of Partial Discharge Signals
Zhu Y.
Wang L.
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, 2018, 33 (11): : 2508 - 2519
[4] Reflection Wave Analysis Based on Ensemble Empirical Mode Decomposition
Kao, Sheng-Chi
Hsiao, Tzu-Chien
Chang, Chia-Chi
Hsu, Hung-Yi
2013 E-HEALTH AND BIOENGINEERING CONFERENCE (EHB), 2013,
[5] UHF partial discharge monitoring and expert system diagnosis
Huecker, T
Gorablenkow, J
IEEE TRANSACTIONS ON POWER DELIVERY, 1998, 13 (04) : 1162 - 1167
[6] A Human ECG Identification System Based on Ensemble Empirical Mode Decomposition
Zhao, Zhidong
Yang, Lei
Chen, Diandian
Luo, Yi
SENSORS, 2013, 13 (05) : 6832 - 6864
[7] Analysis of Acoustic Signal Based on Modified Ensemble Empirical Mode Decomposition
Kwon, Sundeok
Cho, Sangjin
TRANSACTIONS ON ENGINEERING TECHNOLOGIES: SPECIAL ISSUE OF THE WORLD CONGRESS ON ENGINEERING AND COMPUTER SCIENCE 2013, 2014, : 377 - 386
[8] Ensemble modeling of mill load based on empirical mode decomposition and partial least squares
Zhao, Lijie
Tang, Jian
Zheng, Wengrong
Journal of Theoretical and Applied Information Technology, 2012, 45 (01) : 179 - 191
[9] Pipeline Trajectory Reconstruction Based on Ensemble Empirical Mode Decomposition With Partial Adaptive Noise
Yuan, Shijiao
Chen, Qiang
Li, Hao
Xu, Yixiong
IEEE SENSORS JOURNAL, 2023, 23 (19) : 22857 - 22866
[10] Ubiquitous UHF Monitoring System for Partial Discharge Detection and Trending
Andle, Jeffrey C.
Murray, Jonathan P.
Chap, Maly
Baquero, Elkin
Jordan, Jeffrey T.
2015 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT ASIA), 2015,

← 1 2 3 4 5 →