Identification of Multiple Power Quality Disturbances using S-Transform and Rule Based Classification Technique

A novel method for power quality multiple disturbance decomposition based on Independent Component Analysis

“…There are two indeterminacies when estimating the ICA model given by (10). These indeterminacies occur due to the fact that both sources s as the mixture matrix A are unknown.…”

“…In [10], a method for classifying power quality single and multiple disturbances based on S-transform feature extraction and a rule based classifier is proposed. In [11], a classifier is proposed consisting of several processing components arranged in a cascade form, including amplitude estimator (to recognize sags, swells or interruptions), Wavelet Transform, transient detector and neural networks to recognize other multiple disturbances (harmonics and flickers, in this case).…”

An image processing based method for power quality event identification

“…It is fully convertible from the time domain to the two dimensional frequency translation domain, and to the familiar Fourier frequency domain. Researchers [11][12][13][14] have utilized S-transform to extract features such as amplitude factor, frequency factor, etc., from the PQ disturbance signals. In [15], the power signal disturbances in time-time transformation (TT-transform) are derived from the S-transform.…”

Comparison of modified teaching–learning-based optimization and extreme learning machine for classification of multiple power signal disturbances

“…Several authors have presented different signal processing techniques based on discrete wavelet transform (DWT) [5][6][7], S-Transform (ST) [8][9][10], in order to identify the type of disturbance present in the power signal more effectively. By this method, it is possible to extract important information from a disturbance signal and determine the type of disturbance that has caused a power quality problem to occur.…”