Applying Wavelet Entropy Principle in Fault Classification
The ability to detect and classify the type of fault
plays a great role in the protection of power system. This procedure
is required to be precise with no time consumption. In this paper
detection of fault type has been implemented using wavelet analysis
together with wavelet entropy principle. The simulation of power
system is carried out using PSCAD/EMTDC. Different types of
faults were studied obtaining various current waveforms. These
current waveforms were decomposed using wavelet analysis into
different approximation and details. The wavelet entropy of such
decompositions is analyzed reaching a successful methodology for
fault classification. The suggested approach is tested using different
fault types and proven successful identification for the type of fault.
[1] M. Kezunovic and I. Rikalo, "Detect and classify faults using neural
nets," IEEE Comput. Appl. Power, vol. 9, pp. 42-47, Oct. 1996.
[2] W. A. Wilkinson and M. D. Cox, "Discrete wavelet analysis of power
system transients," IEEE Trans. Power Syst., vol. 11, pp. 2038-2044.
[3] Bin Zhang, Zhengyou He and Qingquan Qian, "Application of wavelet
entropy and adaptive nerve-fuzzy inference to fault classification", Proc.
Int. Conf. on Power System Technology, 2006.
[4] Zhengyou He, Yumei Cai and Qingquan Qian, "A study of wavelet
entropy theory and its applications in power system", Proc. of Int. Conf.
on Intelligent Mechatronics and Automation, China, Aug. 2004.
[5] Zhimin Li, Weixing Li and Ruiye Liu, "Applications of entropy
principles in power system: A survey", IEEE/PES Transmission and
Distribution conference and Exhibition, China, 2005.
[6] H.Zheng-you, C.Xiaoqing and L.Guoming, "Wavelet Entropy Definition
and its Application for Transmission Line Fault Detection and
Identification (Part I: Definition and Methodology), Proc. Int. Conf. on
Power System Technology, 2006.
[7] H.Zheng-you, C.Xiaoqing and L.Guoming, "Wavelet Entropy Definition
and its Application for Transmission Line Fault Detection and
Identification (Part III: Transmission line faults transients identification),
Proc. Int. Conf. on Power System Technology, 2006.
[8] MATLAB reference manual, The Mathworks Inc., 2002.
[1] M. Kezunovic and I. Rikalo, "Detect and classify faults using neural
nets," IEEE Comput. Appl. Power, vol. 9, pp. 42-47, Oct. 1996.
[2] W. A. Wilkinson and M. D. Cox, "Discrete wavelet analysis of power
system transients," IEEE Trans. Power Syst., vol. 11, pp. 2038-2044.
[3] Bin Zhang, Zhengyou He and Qingquan Qian, "Application of wavelet
entropy and adaptive nerve-fuzzy inference to fault classification", Proc.
Int. Conf. on Power System Technology, 2006.
[4] Zhengyou He, Yumei Cai and Qingquan Qian, "A study of wavelet
entropy theory and its applications in power system", Proc. of Int. Conf.
on Intelligent Mechatronics and Automation, China, Aug. 2004.
[5] Zhimin Li, Weixing Li and Ruiye Liu, "Applications of entropy
principles in power system: A survey", IEEE/PES Transmission and
Distribution conference and Exhibition, China, 2005.
[6] H.Zheng-you, C.Xiaoqing and L.Guoming, "Wavelet Entropy Definition
and its Application for Transmission Line Fault Detection and
Identification (Part I: Definition and Methodology), Proc. Int. Conf. on
Power System Technology, 2006.
[7] H.Zheng-you, C.Xiaoqing and L.Guoming, "Wavelet Entropy Definition
and its Application for Transmission Line Fault Detection and
Identification (Part III: Transmission line faults transients identification),
Proc. Int. Conf. on Power System Technology, 2006.
[8] MATLAB reference manual, The Mathworks Inc., 2002.
@article{"International Journal of Electrical, Electronic and Communication Sciences:61609", author = "S. El Safty and A. El-Zonkoly", title = "Applying Wavelet Entropy Principle in Fault Classification", abstract = "The ability to detect and classify the type of fault
plays a great role in the protection of power system. This procedure
is required to be precise with no time consumption. In this paper
detection of fault type has been implemented using wavelet analysis
together with wavelet entropy principle. The simulation of power
system is carried out using PSCAD/EMTDC. Different types of
faults were studied obtaining various current waveforms. These
current waveforms were decomposed using wavelet analysis into
different approximation and details. The wavelet entropy of such
decompositions is analyzed reaching a successful methodology for
fault classification. The suggested approach is tested using different
fault types and proven successful identification for the type of fault.", keywords = "Fault classification, wavelet transform, waveletentropy.", volume = "2", number = "4", pages = "681-3", }