Discrete Wavelet Analysis Based Processing of Short-Duration Voltage Variations
M.S. Priyadarshini1, M. Sushama.2
1M.S. Priyadarshini, Research Scholar, Assistant Professor, J.N.T.U Anantapur A.I.T.S Kadapa (Andhra Pradesh), India.
2Dr. M. Sushama, Professor, J.N.T.U.H College of Engineering, Hyderabad (Telangana), India.
Manuscript received on 24 March 2019 | Revised Manuscript received on 05 April 2019 | Manuscript Published on 18 April 2019 | PP: 510-514 | Volume-7 Issue-6S March 2019 | Retrieval Number: F02980376S19/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The aim of this paper is to obtain information about sinusoidal voltage signals, in which variations occur for a short duration, using wavelet analysis based signal processing methods. Sag, swell and interruption are short-duration voltage variations. The changes that occur in supply voltage are to be analyzed properly to initiate correct preventive measures. Multiresolution analysis based discrete wavelet transform is used for decomposing the original signals into five levels of approximations and details. Energy for wavelet decomposition and entropy are used for feature extraction and an attempt is made to obtain an information from the disturbance signals. Pure sinusoidal signal is used as reference and all the voltage variations are generated using SIMULINK in MATLAB environment. Energy values of one approximation and of details corresponding to all levels one to five are obtained. Shannon, log energy and norm entropy values are obtained for five level approximations and details. The term level refers to decomposition level. An observation is made between the obtained energy and entropy values of all the signals and for each variation, energy and entropy values are distinguishable for different disturbances.
Keywords: Approximations, Details, Discrete Wavelet Transform, Energy, Entropy.
Scope of the Article: Image analysis and Processing