Power quality disturbance classification using Hilbert transform and RBF networks

Neurocomputing

Volumn 73, Issue 7-9, 2010, Pages 1451-1456

  Jayasree, T ^a   Devaraj, D ^b   Sukanesh, R ^c  

^a Govt Polytechnic College   (India)

^b KALASALINGAM UNIVERSITY   (India)

^c THIAGARAJAR COLLEGE OF ENGINEERING   (India)

Author keywords

Artificial neural network (ANN); Hilbert transform; Power quality

Indexed keywords

ARTIFICIAL NEURAL NETWORK; DISTURBANCE CLASSIFICATION; DISTURBANCE SIGNALS; FEATURE EXTRACTION TECHNIQUES; HILBERT TRANSFORM; INPUT FEATURES; POWER QUALITY DISTURBANCES; RADIAL BASIS FUNCTION NEURAL NETWORKS; RBF NETWORK; SIMULATION RESULT; TEST SYSTEMS;

FEATURE EXTRACTION; MATHEMATICAL TRANSFORMATIONS; RADIAL BASIS FUNCTION NETWORKS;

NEURAL NETWORKS;

ARTICLE; CLASSIFICATION ALGORITHM; DATA ANALYSIS; DATA EXTRACTION; HILBERT TRANSFORM; IMPEDANCE; INTERMETHOD COMPARISON; MATHEMATICAL ANALYSIS; POWER SUPPLY; PRIORITY JOURNAL; PROCESS DEVELOPMENT; RADIAL BASED FUNCTION; SIGNAL NOISE RATIO; SIMULATION; WAVEFORM;

EID: 77949267118     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2009.11.008     Document Type: Article

References (19)

1. Lev H., Stankovic A.M., and Lin S. Application of staggered under sampling to power quality monitoring. IEEE Trans. Power Delivery 15 3 (2000)
2. Gaing Z.L. Wavelet based neural network for power disturbance recognition and classification. IEEE Trans. Power Delivery 19 4 (2004) 1560-1568
3. He H., Janus, and Starzyk A. A self organizing learning array system for power quality classification based on wavelet transform. IEEE Trans. Power Delivery 21 1 (2006) 286-294
4. Gaouda A.M., Salam M.M.A., Sultan M.R., and Chikhani A.Y. Power quality detection and classification using wavelet multiresolution signal decomposition. IEEE Trans. Power Delivery 14 10 (1999) 1469-1476
5. Huang S.J., and Jou M.J. Application of arithmetic coding for electric power disturbance data compression with wavelet packet enhancement. IEEE Trans. Power Syst. 19 4 (2004) 1334-1341
6. Yang H.T., and Liao C.-C. A de-noising scheme for enhancing wavelet based power quality monitoring system. IEEE Trans. Power Delivery 16 7 (2001) 353-360
7. Mishra S., Bende C.N., and Ponogragi B.K. Detection and classification of power quality disturbances using S-transform and probabilistic neural networks. IEEE Trans. Power Delivery 23 1 (2008) 280-287
8. Dash P.K., Panigrahi B.K., and Panda G. Power quality analysis using S-transform. IEEE Trans. Power Delivery 18 2 (2003) 406-411
9. Bendhe C.N., Mistr S., and Panigahi P.K. Detection and classification of power quality disturbances using S-transform and modular neural network. Electric Power system Research 78 (2008) 122-128
10. D. Devaraj, J. Preetha Roselin, R. Uma Rani, Artificial Neural Network model for voltage security based contingency ranking, Journal of Applied Soft Computing (2006).
11. Lee I.W.C. S-Transform based intelligent system for classification of power quality disturbance signals. IEEE Trans. Ind. Electron. 50 (2003) 800-805
12. Zhao F., and Rengang. Power quality disturbance recognition using S-transform. IEEE Trans. Power Delivery 21 1 (2007) 944-950
13. Samantaray S.R., Dhas P.K., and Panda G. Power system events classification using pattern recognition approach. International Journal of Emerging Electric Power systems 6 1 (2006) article5
14. Vasillic S., and Kezunovic M. Fuzzy ART neural network algorithm for classifying the power system faults. IEEE Trans. Power Delivery 20 2 (2005) 1306-1314
15. Abdel-Galil T.K., and Sadaany E.L. On line tracking of voltage flicker utilizing energy operator and Hilbert transform. IEEE Trans. Power Delivery 19 2 (2004) 861-867
16. Uma, D. Zamrooth, S. Priya, On Line Tracking of Voltage Flicker using Hilbert Transform, in: Proceedings of International conference on Computational Intelligence in Power Apparatus and systems (CIPS 2008) pp. 663-669.
17. Yu D., Cheng J., and Yang Y. Application of EMD method and Hilbert spectrum to the fault diagnosis of bearings. Mechanical Systems and signal processing 19 (2005) 259-270
18. Qin Y., Qin S., and Mao Y. Research on iterated Hilbert transform and its application in mechanical fault diagnosis. Mechanical Systems and Signal Processing 22 (2008) 1967-1980
19. Junsheng Cheng, Yu Yang, Dejie Yu, The envelope order spectrum based on generalized demodulation time-frequency analysis and its application to gear fault diagnosis, Mechanical systems and signal processing, 24 (2) (2010) 508-521.