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This paper presents a new methodology based on independent component analysis (ICA) for power quality disturbance analysis. The proposed methodology aims at analyzing power quality disturbances that appear as mixtures in the voltage signal. Such disturbances are commonly referred to as multiple disturbances. Results are obtained from both simulated and experimental data showing that disturbance classification...
This work presents the development of a system for analysis of power quality multiple disturbances using a recent non-supervised technique called independent component analysis. An application of the technique on an automatic power quality disturbance classification system, based on higher-order cumulants and artificial neural networks, is also presented. Promising results are achieved for simulated...
This paper outlines a novel method for detecting power quality (PQ) disturbance using higher order statistics (HOS). The main advantage introduced in this method refers to the detection capability of voltage disturbances in a data frame with, at least, N=32 samples. This improvement provides the detection of disturbances in sub-multiples or multiples of one cycle of the fundamental component if an...
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