Power quality detection and classification using wavelet transform-multiresolution analysis / Mohd Shaihan Jusoh

Jusoh, Mohd Shaihan (2010) Power quality detection and classification using wavelet transform-multiresolution analysis / Mohd Shaihan Jusoh. Degree thesis, Universiti Teknologi MARA (UiTM).

Abstract

This thesis presents features that characterize power quality disturbances from recorded voltage waveforms using wavelet transform. The main objective of this thesis is to classify and categorize the power quality disturbances by establishing its unique pattern of power quality disturbances from the deviation of energy curves. Wavelet transform and multiresolution analysis is one of the techniques to classify and categorize power quality disturbance. Even though the main concern of this project is to classify and categorize power quality problems, it is being concentrated with sag and swell problems. The outputs of the feature extraction are the wavelet coefficients representing the power quality disturbance signal. Wavelet coefficients at different levels reveal the time localizing information about the variation of the signal. Wavelet transform will be used to detect the power quality disturbance while the multiresolution analysis will categorize and classify them.

Metadata

Item Type: Thesis (Degree)
Creators:
Creators
Email / ID Num.
Jusoh, Mohd Shaihan
2007270706
Contributors:
Contribution
Name
Email / ID Num.
Advisor
Zakaria, Zuhaina
UNSPECIFIED
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering
Programme: Bachelor in Electrical Engineering (Hons.)
Keywords: Waveforms, power quality, energy
Date: 2010
URI: https://ir.uitm.edu.my/id/eprint/79528
Edit Item
Edit Item

Download

[thumbnail of 79528.PDF] Text
79528.PDF

Download (298kB)

Digital Copy

Digital (fulltext) is available at:

Physical Copy

Physical status and holdings:
Item Status:
Processing

ID Number

79528

Indexing

Statistic

Statistic details