Optimal Denoising and Feature Extraction Methods Using Modified CEEMD Combined with Duffing System and Their Applications in Fault Line Selection of Non-Solid-Earthed Network

被引:19
作者
Hou, Sizu [1 ]
Guo, Wei [1 ]
机构
[1] North China Elect Power Univ, Sch Elect & Elect Engn, Baoding 071003, Peoples R China
来源
SYMMETRY-BASEL | 2020年 / 12卷 / 04期
基金
国家重点研发计划;
关键词
MCEEMD; trisection symmetry phase estimation; generalized composite multiscale permutation entropy; fault line selection; smooth denoising model; MULTISCALE PERMUTATION ENTROPY; FEEDER;
D O I
10.3390/sym12040536
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
As the non-solid-earthed network fails, the zero-sequence current of each line is highly non-stationary, and the noise component is serious. This paper proposes a fault line selection method based on modified complementary ensemble empirical mode decomposition (MCEEMD) and the Duffing system. Here, based on generalized composite multiscale permutation entropy (GCMPE) and support vector machine (SVM) for signal randomness detection, the complementary ensemble empirical mode decomposition is modified. The MCEEMD algorithm has good adaptability, and it can restrain the modal aliasing of empirical mode decomposition (EMD) at a certain level. The Duffing system is highly sensitive when the frequency of the external force signal is the same as that of the internal force signal. For automatically identifying chaotic characteristics, by using the texture features of the phase diagram, the method can quickly obtain the numerical criterion of the chaotic nature. Firstly, the zero-sequence current is decomposed into a series of intrinsic mode functions (IMF) to complete the first noise-reduction. Then an optimized smooth denoising model is established to select optimal IMF for signal reconstruction, which can complete the second noise-reduction. Finally, the reconstructed signal is put into the Duffing system. The trisection symmetry phase estimation is used to determine the relative phase of the detection signal. The faulty line in the non-solid-earthed network is selected with the diagram outputted by the Duffing system.
引用
收藏
页数:27
相关论文
共 42 条
[1]  
[Anonymous], SHOCK
[2]   Chaotic Motion in Forced Duffing System Subject to Linear and Nonlinear Damping [J].
Chang, Tai-Ping .
MATHEMATICAL PROBLEMS IN ENGINEERING, 2017, 2017
[3]   Real-Time Detection of Transients Induced by High-Impedance Faults Based on the Boundary Wavelet Transform [J].
Costa, Flavio B. ;
Souza, B. A. ;
Brito, N. S. D. ;
Silva, J. A. C. B. ;
Santos, W. C. .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2015, 51 (06) :5312-5323
[4]   Identifying single-phase-to-ground fault feeder in neutral noneffectively grounded distribution system using wavelet transform [J].
Dong, Xinzhou ;
Shi, Shenxing .
IEEE TRANSACTIONS ON POWER DELIVERY, 2008, 23 (04) :1829-1837
[5]   A New Fuzzy Logic Classifier Based on Multiscale Permutation Entropy and Its Application in Bearing Fault Diagnosis [J].
Du, Wenhua ;
Guo, Xiaoming ;
Wang, Zhijian ;
Wang, Junyuan ;
Yu, Mingrang ;
Li, Chuanjiang ;
Wang, Guanjun ;
Wang, Longjuan ;
Guo, Huaichao ;
Zhou, Jinjie ;
Shao, Yanjun ;
Xue, Huiling ;
Yao, Xingyan .
ENTROPY, 2020, 22 (01) :27
[6]   Independent Analysis of Decelerations and Resting Periods through CEEMDAN and Spectral-Based Feature Extraction Improves Cardiotocographic Assessment [J].
Fuentealba, Patricio ;
Illanes, Alfredo ;
Ortmeier, Frank .
APPLIED SCIENCES-BASEL, 2019, 9 (24)
[7]   A Novel Intelligent Method for Bearing Fault Diagnosis Based on EEMD Permutation Entropy and GG Clustering [J].
Hou, Jingbao ;
Wu, Yunxin ;
Gong, Hai ;
Ahmad, A. S. ;
Liu, Lei .
APPLIED SCIENCES-BASEL, 2020, 10 (01)
[8]   Refined Composite Multiscale Permutation Entropy to Overcome Multiscale Permutation Entropy Length Dependence [J].
Humeau-Heurtier, Anne ;
Wu, Chiu-Wen ;
Wu, Shuen-De .
IEEE SIGNAL PROCESSING LETTERS, 2015, 22 (12) :2364-2367
[9]   A New Bearing Fault Diagnosis Method Based on Fine-to-Coarse Multiscale Permutation Entropy, Laplacian Score and SVM [J].
Huo, Zhiqiang ;
Zhang, Yu ;
Shu, Lei ;
Gallimore, Michael .
IEEE ACCESS, 2019, 7 :17050-17066
[10]  
[康小宁 Kang Xiaoning], 2012, [电力系统自动化, Automation of Electric Power Systems], V36, P88