- Turkish Journal of Electrical Engineering and Computer Science
- Vol: 21 Issue: 6
- Classification of power quality disturbances using S-transform and TT-transform based on the artific...
Classification of power quality disturbances using S-transform and TT-transform based on the artificial neural network
Authors : Sajad Jashfar, Saeid Esmaeili, Mehdi Zareian-jahromi
Pages : 1528-1538
Doi:10.3906/elk-1112-51
View : 6 | Download : 4
Publication Date : 9999-12-31
Article Type : Makaleler
Abstract :The classification of power quality (PQ) disturbances to improve the PQ is an important issue in utilities and industrial factories. In this paper, an approach to classify PQ disturbances is presented. First, a signal containing one of the PQ disturbances, like sag, swell, flicker, interruption, transient, or harmonics, is evaluated using the proposed approach. Afterwards, S-transform and TT-transform are applied to the signal and an artificial neural network is used to recognize the disturbance using S-transform and TT-transform data, like the variance and mean values of S-transform and TT-transform matrices. The main features of the proposed approach are the real-time and very fast recognition of the PQ disturbances. Finally, the proposed method's results are compared with the support vector machine and k-nearest neighbor classification methods to verify the results. The results show the effectiveness of this state-of-the-art approach.Keywords : Power quality, disturbances, short-time Fourier transform, S-transform, TT-transform, artificial neural network