Fault Diagnosis of Power Quality

Abstract:

The proposed method in this paper indicates two issues, selection of discriminative features and classifies event classes with minimum error. Wavelets features (WF) of power quality (PQ) events are extracted using wavelet transform (WT) and fuzzy classifiers classify events using these features. The captured signals are often corrupted by noise; the non-linear and non-stationary behaviors of PQ events make the detection and classification tasks more cumbersome. Performance comparison of the proposed method is made with three other fuzzy classifiers using different wavelets and superiority is verified. In the proposed approach of event classification, fuzzy product aggregation reasoning rule based method has been used.

• Periodical: Applied Mechanics and Materials (Volumes 128-129)
• Pages: 870-873
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.128-129.870
• Online since: October 2011
• Authors: Yang Lan Ou
• Keywords: Fault Diagnosis, Fuzzy Classifiers, Fuzzy System, Power Quality (PQ)

References

[1] U.D. Dwivedi, S.N. Singh, A robust energy features estimation for detection and classification of power quality disturbances, Proc. IEEE Power India Conf. (2006).

DOI: 10.1109/poweri.2006.1632542

[2] C.H. Lin, M.C. Tsao, Power quality detection with classification enhancible wavelet-probabilistic network in a power system, IEE Proc. Gener. Transm. Distrib. 152 (2005) 969–976.

DOI: 10.1049/ip-gtd:20045177

[3] A. Ghosh, S.K. Meher, B. Uma Shankar, A novel fuzzy classifier based on product aggregation operator, Pattern Recogn. 41 (2008) 961–971.

DOI: 10.1016/j.patcog.2007.08.002

[4] M.B.I. Reaz, F. Choong M.S. Sulaiman, F. Mohd-Yasin,A. Kamada, Fault detection and classification in transmission lines based on wavelet transform and ANN, IEEE Trans. Power Deliv. 21 (2006) 2058–(2063).

DOI: 10.1109/tpwrd.2006.876659

[5] B. Bizjak, P. Planinsic, Classification of power disturbances using fuzzy logic, Proc. IEEE Int. Conf. Power Electron. Motion Control (2006) 1356–1360.

DOI: 10.1109/epepemc.2006.283352

[6] S.K. Meher, B. Uma Shankar, A. Ghosh, Wavelet-feature-based classifiers for multispectral remote-sensing images, IEEE Trans. Geosci. Remote Sens. 45 (2007) 1881–1886.

DOI: 10.1109/tgrs.2007.895836