Wave shape recognition of spikes using MATLAB application in power quality analysis / Osaizam Izwan Othman

Power quality has become an issue of increasing interest since the late 1980s. The interest in PQ involves all three parties concerned with the power business: utility companies, equipment manufacturers, and electric power customers. This paper describes a method for recognition of spike disturbance...

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Main Author: Othman, Osaizam Izwan
Format: Thesis
Language:English
Published: 2002
Online Access:https://ir.uitm.edu.my/id/eprint/84831/1/84831.pdf
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spelling my-uitm-ir.848312024-01-16T08:49:34Z Wave shape recognition of spikes using MATLAB application in power quality analysis / Osaizam Izwan Othman 2002 Othman, Osaizam Izwan Power quality has become an issue of increasing interest since the late 1980s. The interest in PQ involves all three parties concerned with the power business: utility companies, equipment manufacturers, and electric power customers. This paper describes a method for recognition of spike disturbance by using the Learning Vector Quantization (LVQ) and Probabilistic Neural Network (PNN) incorporated with wavelet processing. The spike that occurs in the power supplies that cause voltage current or frequency deviations causing the malfunction of the user appliance is one of the major issues that have been experienced by the utility and consumer parties. The capabiUty of Wavelet to detect the spike is being exposed. The finally stage is to classify spike using the Learning Vector Quantization (LVQ) or Probabilisitc Neural Network (PNN) has being proposed. This paper would be guided for the using of the self-detecting and classification by using the MATLAB application in monitoring system. 2002 Thesis https://ir.uitm.edu.my/id/eprint/84831/ https://ir.uitm.edu.my/id/eprint/84831/1/84831.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Yahya, Muhammad
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
advisor Yahya, Muhammad
description Power quality has become an issue of increasing interest since the late 1980s. The interest in PQ involves all three parties concerned with the power business: utility companies, equipment manufacturers, and electric power customers. This paper describes a method for recognition of spike disturbance by using the Learning Vector Quantization (LVQ) and Probabilistic Neural Network (PNN) incorporated with wavelet processing. The spike that occurs in the power supplies that cause voltage current or frequency deviations causing the malfunction of the user appliance is one of the major issues that have been experienced by the utility and consumer parties. The capabiUty of Wavelet to detect the spike is being exposed. The finally stage is to classify spike using the Learning Vector Quantization (LVQ) or Probabilisitc Neural Network (PNN) has being proposed. This paper would be guided for the using of the self-detecting and classification by using the MATLAB application in monitoring system.
format Thesis
qualification_level Bachelor degree
author Othman, Osaizam Izwan
spellingShingle Othman, Osaizam Izwan
Wave shape recognition of spikes using MATLAB application in power quality analysis / Osaizam Izwan Othman
author_facet Othman, Osaizam Izwan
author_sort Othman, Osaizam Izwan
title Wave shape recognition of spikes using MATLAB application in power quality analysis / Osaizam Izwan Othman
title_short Wave shape recognition of spikes using MATLAB application in power quality analysis / Osaizam Izwan Othman
title_full Wave shape recognition of spikes using MATLAB application in power quality analysis / Osaizam Izwan Othman
title_fullStr Wave shape recognition of spikes using MATLAB application in power quality analysis / Osaizam Izwan Othman
title_full_unstemmed Wave shape recognition of spikes using MATLAB application in power quality analysis / Osaizam Izwan Othman
title_sort wave shape recognition of spikes using matlab application in power quality analysis / osaizam izwan othman
granting_institution Universiti Teknologi MARA (UiTM)
granting_department Faculty of Electrical Engineering
publishDate 2002
url https://ir.uitm.edu.my/id/eprint/84831/1/84831.pdf
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