Power quality disturbance detection based on S-transform and PNN

Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument

Volumn 30, Issue 8, 2009, Pages 1668-1673

  Tang, Qiu ^a   Wang, Yaonan ^a   Guo, Siyu ^a   Teng, Zhaosheng ^a  

^a HUNAN UNIVERSITY   (China)

Author keywords

Classification; Disturbance; PNN; Power quality; S transform

Indexed keywords

CLASSIFICATION; CLASSIFICATION ACCURACY; CLASSIFICATION METHODS; DISTURBANCE; DISTURBANCE CLASSIFICATION; PNN; POWER QUALITY DISTURBANCES; PROBABILISTIC NEURAL NETWORKS; S TRANSFORMS; S-TRANSFORM; SIMULATION RESULT; SMALL TRAINING; SYSTEM STRUCTURES; TIME FREQUENCY ANALYSIS; TRAINING SPEED; VIRTUAL INSTRUMENT; WORK-FLOWS;

EXTRACTION; NEURAL NETWORKS;

ELECTRIC MEASURING INSTRUMENTS;

EID: 70249103149     PISSN: 02543087     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (13)

1. DUGAN R C, MEGRANGHAN M F, BENTY H W. Electrical power system quality[M]. New York: MC Graw-Hill, 1996.
2. DASH P K, MISHRA S, SALAMA M A, et al. Classification of power system disturbances using a fuzzy expert system and a Fourier linear combiner[J]. IEEE Trans. on Power Delivery, 2001, 15(2): 72-477.
3. HEYDT G T, FJELD P S, LIU C C, et al. Application of the windowed FFT to electric power quality assessment[J]. IEEE Trans. on Power Delivery, 1999, 14(4): 1411-1416.
4. GENG Y L, WANG Q, HE Y G. Wavelet detection and location of power quality and its classification based on multi-scale energy curve[J]. Chinese Journal of Scientific Instrument, 2006, 27(2): 180-182, 217.
5. LU G Y, CHENG H ZH, ZHENG J J, et al. Power quality disturbances detection and identification based on S transform and multi-lay SVMs[J]. Transactions of China Electrotechnical Society, 2006, 21(1): 121-126.
6. EMMANOUIL S, MATH H J, IRENE Y H. Expert system for classification and analysis of power system events[J]. IEEE Trans. on Power Delivery, 2002, 17(2): 423-428.
7. SANTOSO S, POWERS E J, GRADY W M, et al. Power quality disturbance wavelet-based neural classifier-part 1: theoretical foundation[J]. IEEE Trans. on Power Delivery, 2000, 15(1): 222-228.
8. ZHANG Q M, LIU H J. Application of LS-SVM in classification of power quality disturbances[J]. Proceedings of the CSEE, 2008, 28(1): 106-110.
9. KEZUNOVIC M, LIAO Y. A novel software implementation concept for power quality study[J]. IEEE Tran. on Power Delivery, 2002, 17(2): 998-1001.
10. ZHAN Y, CHENG H ZH, DING Y F, et al. S-transform-based classification of Power quality disturbance signals by support vector machines[J]. Proceedings of the CSEE, 2005, 25(4): 51-56.
11. PECHT D F. Probabilistic neural networks[J]. Neural Network, 1990, 3(1): 109-118.
12. TOCKWELL R G., MANSINHA L, LOWE R P. Localization of the complex spectrum: The S-transform[J]. IEEE Trans. Signal Process, 1996, 44(4): 998-1001.
13. HILUKURI M V, DASH P K. Multiresolution S-transform-based fuzzy recognition system for power quality events[J]. IEEE Tran. on Power Delivery, 2004, 19(1): 323-330.