POWER SIGNAL DISTURBANCE CLASSIFICATION USING WAVELET BASED NEURAL NETWORK

Authors

Suja S.
Jerome Jovitha

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.

Publication Date

11-22-2017

Recommended Citation

S., Suja and Jovitha, Jerome (2017) "POWER SIGNAL DISTURBANCE CLASSIFICATION USING WAVELET BASED NEURAL NETWORK," ASEAN Journal on Science and Technology for Development: Vol. 25: No. 2, Article 4.
DOI: https://doi.org/10.29037/ajstd.243
Available at: https://ajstd.ubd.edu.bn/journal/vol25/iss2/4