A quantitative comparison of wavelet based feature vectors for classification of power quality disturbances.

被引：0
|
作者：
Dash, PK [1 ]
Lee, IWC [1 ]
Basu, KP [1 ]
Morris, S [1 ]
Sharaf, AM [1 ]
机构：
[1] Silicon Inst Technol, Bhubaneswar, Orissa, India
来源：
IECON'03: THE 29TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, VOLS 1 - 3, PROCEEDINGS | 2003年
关键词：
wavelet transform; S-Transform; power quality;
D O I：
10.1109/IECON.2003.1280023
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a comparison between different wavelet feature vectors for power quality disturbance classification problems. Three different wavelet algorithms are simulated and applied on nine classes of power quality disturbances. Neural networks are then used to compute the classification accuracy of the feature vectors. Certain characteristics of the wavelet feature vectors are apparent from the results.
引用
收藏
页码：454 / 459
页数：6
相关论文
共 50 条
  • [21] Power quality disturbances classification using wavelet and support vector machines
    Gao, Peisheng
    Wu, Weilin
    ISDA 2006: SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, VOL 1, 2006, : 201 - 206
  • [22] Wavelet-based detection, localization, quantification and classification of short duration power quality disturbances
    Chen, XG
    2002 IEEE POWER ENGINEERING SOCIETY WINTER MEETING, VOLS 1 AND 2, CONFERENCE PROCEEDINGS, 2002, : 931 - 936
  • [23] Evaluation and Classification of Power Quality Disturbances Based on Discrete Wavelet Transform and Artificial Neural Networks
    Alshahrani, Saeed
    Abbod, Maysam
    Alamri, Basem
    Taylor, Gareth
    2015 50TH INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE (UPEC), 2015,
  • [24] Detection and classification of power quality disturbances based on wavelet packet decomposition and support vector machines
    Tong, Weiming
    Song, Xuelei
    Lin, Jingbo
    Zhao, Zhiheng
    2006 8TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, VOLS 1-4, 2006, : 3015 - +
  • [25] Recognition and classification of power quality disturbances based on self-adaptive wavelet neural network
    Tong, Wei-Ming
    Song, Xue-Lei
    Zhang, Dong-Zhong
    ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 2, PROCEEDINGS, 2006, 3972 : 1386 - 1394
  • [26] Automatic power quality disturbances detection and classification based on discrete wavelet transform and artificial intelligence
    Cesar, Duarte G.
    Valdomiro, Vega G.
    Gabriel, Ordonez P.
    2006 IEEE/PES TRANSMISSION & DISTRIBUTION CONFERENCE & EXPOSITION: LATIN AMERICA, VOLS 1-3, 2006, : 1515 - +
  • [27] Wavelet-Based Power Quality Disturbances Detection and Classification Using RBFNN and Fuzzy Logic
    Kanirajan, P.
    Kumar, V. Suresh
    INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2015, 17 (04) : 623 - 634
  • [28] Wavelet-Based Power Quality Disturbances Detection and Classification Using RBFNN and Fuzzy Logic
    P. Kanirajan
    V. Suresh Kumar
    International Journal of Fuzzy Systems, 2015, 17 : 623 - 634
  • [29] Feature extraction of power quality disturbances using adaptive harmonic wavelet transform
    Chand, Pramod
    Davari, Asad
    Liu, Bao
    Sedghisigarchi, Kourosh
    Proceedings of the Thirty-Ninth Southeastern Symposium on System Theory, 2007, : 266 - 269
  • [30] Comparison of Empirical Mode Decomposition and Wavelet Based Classification of Power Quality Events
    Manjula, M.
    Sarma, A. V. R. S.
    2011 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN ENERGY ENGINEERING (ICAEE), 2012, 14 : 1156 - 1162
12345