کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
705626 891348 2008 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Detection and classification of power quality disturbances using S-transform and modular neural network
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی مهندسی انرژی و فناوری های برق
پیش نمایش صفحه اول مقاله
Detection and classification of power quality disturbances using S-transform and modular neural network
چکیده انگلیسی

This paper presents an S-transform based modular neural network (NN) classifier for recognition of power quality disturbances. The excellent time—frequency resolution characteristics of the S-transform makes it an attractive candidate for the analysis of power quality (PQ) disturbances under noisy condition and has the ability to detect the disturbance correctly. On the other hand, the performance of wavelet transform (WT) degrades while detecting and localizing the disturbances in the presence of noise. Features extracted by using the S-transform are applied to a modular NN for automatic classification of the PQ disturbances that solves a relatively complex problem by decomposing it into simpler subtasks. Modularity of neural network provides better classification, model complexity reduction and better learning capability, etc. Eleven types of PQ disturbances are considered for the classification. The simulation results show that the combination of the S-transform and a modular NN can effectively detect and classify different power quality disturbances.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Electric Power Systems Research - Volume 78, Issue 1, January 2008, Pages 122–128
نویسندگان
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