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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2002
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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 |
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Universiti Teknologi MARA |
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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 |
_version_ |
1794192057357565952 |