Friday 29 August 2008

Wseas Transactions

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Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 27-735
Full Name: Eng Eng Ngu
Position: Ph.D. Candidate
Age: ON
Sex: Female
Address: Faculty of Engineering, Multimedia University
Country: MALAYSIA
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E-mail address: eengu@mmu.edu.my
Other E-mails: octopus_ngu@yahoo.com
Title of the Paper: Fault characterisation and classification using wavelet and fast fourier transforms
Authors as they appear in the Paper: E. E. Ngu, K. Ramar, R. Montaño, V. Cooray
Email addresses of all the authors: eengu@mmu.edu.my, ramar@mmu.edu.my, raul.montano@highvoltagevalley.org, vernon.cooray@angstrom.uu.se
Number of paper pages: 11
Abstract: In order to improve the power quality maintenance and reliability of power supply, different types of faults on the transmission line namely: open-circuit (OC), short-circuit (SC), high impedance faults (HIF) and the fault caused by direct lightning strike (LS) have been investigated in this paper. The disturbances have been modelled and simulated using a well-known transient simulation tool - Alternative Transient Program/ Electromagnetic Transient Program (ATP/EMTP) and the resulting data are then imported into MATLAB for the investigation on the traveling wave (TW) reflection pattern and harmonic behaviour . Study on the characteristics of the faults in terms of their corresponding frequency spectrum, the polarities of the incident-wave and reflected-wave has been performed and the possibility to differentiate the type of fault is explored. For this purpose, the fault on the wave has been created at the moment when the voltage signal reaches its peak and also wh!
en it is close to zero. Both, Wavelet Transform (WT) and Fast Fourier Transform (FFT) methods have been used to analyze the transient signals generated by the fault. Model of the network used in this study is taken from [1]-[2].
Keywords: WT, FFT, ATP/EMTP, Current reflection pattern, Spectrum analysis
EXTENSION of the file: .pdf
Special (Invited) Session: A study on different fault characteristics using wavelet and fast fourier transforms
Organizer of the Session: 590 - 243
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