Power quality disturbance classification using Hilbert transform and RBF networks

Application of Signal Processing in Power Quality Monitoring

“…The output of the HT is 90 degree phase shift of the original signal (Shukla et al, 2009). A pattern recognition system has been proposed in (Jayasree et al, 2010) based on HT. The envelope of the power quality disturbances are calculated by using HT.…”

“…Data generation is done by MATLAB/simulink. Sag, swell, transients, harmonics and voltage fluctuation along with normal signal were considered in (Jayasree et al, 2010). 500 samples from each class which were sample at 256 point/cycle with normal frequency 50 Hz.…”

“…500 samples from each class which were sample at 256 point/cycle with normal frequency 50 Hz. The method of (Jayasree et al, 2010) shows the HT features less sensitive to noise level. The combination of EMD and HT are suggested in (Shukla et al, 2009).…”

Pre-Processing Tools and Intelligent Systems Applied to Power Quality Analysis

“…Actually, in literature, a diversity of papers can be found concerning detection and identification of power quality disturbances by applying intelligent systems, such as Artificial Neural Networks (ANN) (Janik & Lobos, 2006;Oleskovicz et. al., 2009;Jayasree, Devaraj & Sukanesh, 2010) and Fuzzy Inference Systems (Zhu, Tso & Lo, 2004;Hooshmand & Enshaee, 2010;Meher & Pradhan, 2010;Behera, Dash & Biswal, 2010). However, only some papers use data pre-processing tools before the application of intelligent systems.…”

Power Quality Disturbances Classification and Recognition Using S-transform Based Neural classifier

“…As Hilbert transform shows greater immunity towards noise, it has been used for the detection and classification of different types of power quality events along with ANN in [13]. S-transform based fuzzy and PSO classifier has been presented in [14] and this identified and classified the PQ disturbance in time domain.…”