GIS Partial Discharge Pattern Recognition Based on the Chaos Theory

被引：58

作者：

Zhang, Xiaoxing ^{[1
]}

Xiao, Song ^{[1
]}

Shu, Na ^{[1
]}

Tang, Ju ^{[1
]}

Li, Wei ^{[2
]}

机构：

[1] Chongqing Univ, State Key Lab Power Transmiss Equipment & Syst Se, Chongqing 400030, Peoples R China

[2] State Grid Elect Power Res Inst Xinjiang, Urumqi 830000, Peoples R China

来源：

IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION | 2014年 / 21卷 / 02期

关键词：

Partial discharge; feature extraction; Dempster-Shafer evidence theory; gas insulated switchgear; pattern recognition;

D O I：

10.1109/TDEI.2013.004020

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Partial discharge (PD) is a key parameter which describes insulation condition of gas-insulated switchgear GIS, GIS internal defects can be discovered in time with the interferences such as corona discharge from the power system using Ultra-high frequency (UHF) method. Traditional method based on statistical characteristics is limited to the analysis of image features that describe the PD pattern plot, causing low recognition rate of some kinds of PD. In this paper, the acquisition of the PD characteristics caused by four typical insulation defects forms phi-v-n 3D PRPD pattern plots sample matrix. The largest Lyapunov exponent of each column of matrix is calculated. A 36-dimension vector is then obtained as the chaotic characteristics of the PD in different voltage phases. The experimental results show that the recognition method based on the chaotic characteristics performs well on all four kinds of insulation defects and can satisfy the recognition order. The method based on the chaotic characteristics has a strong recognition ability for the discharge physical models of gas gap, which is an advantage over the traditional method. The two recognition methods have a good complementary property. Combining the complementary chaotic and statistical characteristics in a decision-making level by using the Dempster-Shafer evidence theory results in an accuracy of above 98%.

引用

页码：783 / 790

页数：8

共 23 条

[11] A comparison of methods for multiclass support vector machines [J].

Hsu, CW ;

Lin, CJ .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2002, 13 (02) :415-425

[12] The excitation of UHF signals by partial discharges in GIS [J].

Judd, MD ;

Farish, O ;

Hampton, BF .

IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION, 1996, 3 (02) :213-228

[13]

Lim Y, 2001, ISIE 2001: IEEE INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS PROCEEDINGS, VOLS I-III, P413, DOI 10.1109/ISIE.2001.931825

[14]

Lim YS, 2001, 2001 ANNUAL REPORT CONFERENCE ON ELECTRICAL INSULATION AND DIELECTRIC PHENOMENA, P324, DOI 10.1109/CEIDP.2001.963549

[15] A CONTINUOUS UHF MONITOR FOR GAS-INSULATED SUBSTATIONS [J].

PEARSON, JS ;

HAMPTON, BF ;

SELLARS, AG .

IEEE TRANSACTIONS ON ELECTRICAL INSULATION, 1991, 26 (03) :469-478

[16] CAN FRACTAL FEATURES BE USED FOR RECOGNIZING 3-D PARTIAL DISCHARGE PATTERNS [J].

SATISH, L ;

ZAENGL, WS .

IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION, 1995, 2 (03) :352-359

[17]

Takens F., 1981, Lecture Notes in Mathematics, P366, DOI [10.1007/bfb0091924, DOI 10.1007/BFB0091924, 10.1007/BFb0091924]

[18]

Vapnik V., 1995, NATURE STAT LEARNING, P138, DOI DOI 10.2307/1271368

[19]

Wahba G, 1999, ADVANCES IN KERNEL METHODS, P69

[20] DETERMINING LYAPUNOV EXPONENTS FROM A TIME-SERIES [J].

WOLF, A ;

SWIFT, JB ;

SWINNEY, HL ;

VASTANO, JA .

PHYSICA D, 1985, 16 (03) :285-317

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