ASEAN Journal on Science and Technology for Development
Vol. 25 No. 2 (2008): ASEAN Journal on Science and Technology for Development (AJSTD)

POWER SIGNAL DISTURBANCE CLASSIFICATION USING WAVELET BASED NEURAL NETWORK

S. Suja (Coimbatore Institute of Technology. Coimbatore - 14, TN)
Jovitha Jerome (PSG College of Technology, Coimbatore - 4, TN)

Article Info

Publish Date
22 Nov 2017

Abstract

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 power signal disturbances. The second component is a detector which uses the technique of DWT to detect the power signal disturbances. DWT is used to extract disturbance features in the power signal. The third component is neural network architecture to classify the power signal disturbances.    

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Journal Info
ASEAN Journal on Science and Technology for Development
Website

Abbrev

ajstd

Publisher

Universitas Gadjah Mada

Subject

Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Mathematics

Description

The coverage is focused on, but not limited to, the main areas of activity of ASEAN COST, namely: Biotechnology, Non-Conventional Energy Research, Materials Science and Technology, Marine Sciences, Meteorology and Geophysics, Food Science and Technology, Microelectronics and Information Technology, ...