Abstract
In this paper a power quality classification problem has been addressed. A proposed technique using Adaptive Neuro Fuzzy Inference System has been introduced to classify different type of disturbance events. The proposed technique uses fast Fourier transform and wavelet transform to extract five distinguish features of power disturbances types. The system considers four types of disturbances: sag, swell, harmonic and flicker.
| Original language | English |
|---|---|
| Title of host publication | 2017 9th IEEE-GCC Conference and Exhibition, GCCCE 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Print) | 9781538627563 |
| DOIs | |
| State | Published - 27 Aug 2018 |
Publication series
| Name | 2017 9th IEEE-GCC Conference and Exhibition, GCCCE 2017 |
|---|
Bibliographical note
Publisher Copyright:© 2017 IEEE.
Keywords
- Adaptive Neuro Fuzzy Inference System
- Classification
- Discreet Wavelet
- Fast Fourier
- Power Quality
ASJC Scopus subject areas
- Computer Networks and Communications
- Signal Processing
- Information Systems and Management
- Media Technology
- Instrumentation
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