POWER SIGNAL DISTURBANCE CLASSIFICATION USING WAVELET BASED NEURAL NETWORK
In this paper, the power signal disturbances are detected using discrete wavelet transform (DWT) and categorized using neural networks. This paper presents a prototype of power quality disturbance recognition system. The prototype contains three main components. First a simulator is used to generate...
Main Authors: | S. Suja, Jovitha Jerome |
---|---|
Format: | Article |
Language: | English |
Published: |
Universiti Brunei Darussalam
2017-11-01
|
Series: | ASEAN Journal on Science and Technology for Development |
Subjects: | |
Online Access: | http://www.ajstd.org/index.php/ajstd/article/view/243 |
Similar Items
-
Disturbance Recognition of Power Quality Based on Wavelet Packet-Energy Entropy
by: LI Ning, et al.
Published: (2010-08-01) -
Location and classification of power quality disturbance based on wavelet packet and PN
by: GONG Maofa, et al.
Published: (2016-05-01) -
Classification of Multiple Power Quality Disturbances by Tunable-Q Wavelet Transform with Parameter Selection
by: Lin Yang, et al.
Published: (2022-05-01) -
Classification of Electrical Power Disturbances on Hybrid-Electric Ferries Using Wavelet Transform and Neural Network
by: Aleksandar Cuculić, et al.
Published: (2022-08-01) -
Methodology for the Detection and Classification of Power Quality Disturbances Using CWT and CNN
by: Eduardo Perez-Anaya, et al.
Published: (2024-02-01)