This paper presents a model for the generation ofpartems of phenomena associated to power quuliiy in electric iiwtworh. Zkis model is based on wavelet theory and on the use of wovelet tools mailable in M4 Iz4B version 6.0. The method was developed by means of the DWT (Discrete Wmelet Tronsforni) anabsis. f i e DWT decomposes the entry signal and any di&ence with the pure sine signal of 60 Hz with the corresponding amplitude k detected i%en the signal's power curve b analyzed and the deviation with the corresponding power curve of the fundamental sipui i~ obtained. ?%is deviation determines a pattem for each of the phenomena and it becomes easib recognizabIe and ident@abIe. Finally the foundution to train a neurul network with these pattems is loid so the network can identifi the phenomena, its risk undp0ssibI.e saktiom.
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