Power Quality Disturbance Classification Using Frequency Domain Features A

The authors would specially like to express their most sincere gratitude to their respected Supervisor, Hafiz Imtiaz, Assistant Professor, Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology for his continuous guidance, encouragement, valuable...

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主要な著者: Yousuf, Md. Adib Ibne, Shamim, S.M., Akanda, Md. Touhidur Rahman
フォーマット: 学位論文
言語:英語
出版事項: Department of Electrical Electronic and Communication Engineering Military Institute of Science and Technology 2015
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オンライン・アクセス:http://hdl.handle.net/123456789/122
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author Yousuf, Md. Adib Ibne
Shamim, S.M.
Akanda, Md. Touhidur Rahman
author_browse Akanda, Md. Touhidur Rahman
Shamim, S.M.
Yousuf, Md. Adib Ibne
author_facet Yousuf, Md. Adib Ibne
Shamim, S.M.
Akanda, Md. Touhidur Rahman
author_sort Yousuf, Md. Adib Ibne
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description The authors would specially like to express their most sincere gratitude to their respected Supervisor, Hafiz Imtiaz, Assistant Professor, Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology for his continuous guidance, encouragement, valuable suggestion and inspiration. His sincere and wise advice helped the authors greatly to make the work successful. Without his initiatives this work would not have been possible. The authors would like to express their thanks to their department for all types of help they offers.They are also grateful to their library & laboratories for lots of help.The authors acknowledge the help of the individuals who contributed to the successful completion of the whole work.
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spelling oai:localhost:123456789-1222015-06-29T08:33:51Z Power Quality Disturbance Classification Using Frequency Domain Features A Yousuf, Md. Adib Ibne Shamim, S.M. Akanda, Md. Touhidur Rahman Power, Quality, Disturbance Classification, Frequency, Domain Features . The authors would specially like to express their most sincere gratitude to their respected Supervisor, Hafiz Imtiaz, Assistant Professor, Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology for his continuous guidance, encouragement, valuable suggestion and inspiration. His sincere and wise advice helped the authors greatly to make the work successful. Without his initiatives this work would not have been possible. The authors would like to express their thanks to their department for all types of help they offers.They are also grateful to their library & laboratories for lots of help.The authors acknowledge the help of the individuals who contributed to the successful completion of the whole work. Discrete Cosine Transform feature has become an effective feature extraction method in modern power system. In this paper, we used algorithm of a unique feature for power quality (PQ) disturbance signal classification. Here, we proposed the extraction of spectral features from Discrete Cosine Transform (DCT) domain. This feature extraction offers the ability to detect and localize harmonic events and it also classifies different power quality disturbance signals. A useful technique of selecting significant DCT coefficients is proposed for optimal feature selection. This process offers dimensional feature reduction. In this paper we consider seven types of power quality disturbance signals and simulate for each of the given categories. Using this extracted feature we can get not only very high classification accuracy but also a low computational burden. This feature extraction using Discrete Cosine Transform is one of the best feature extraction formula, we have ever seen DEPARTMENT OF ELECTRICAL, ELECTRONIC AND COMMUNICATION ENGINEERING (EECE), MILITARY INSTITUTE OF SCIENCE AND TECHNOLOGY, DHAKA, BANGLADESH 2015-06-29T08:07:35Z 2015-06-29T08:07:35Z 2013-12 Thesis http://hdl.handle.net/123456789/122 en application/pdf Department of Electrical Electronic and Communication Engineering Military Institute of Science and Technology
spellingShingle Power, Quality, Disturbance Classification, Frequency, Domain Features .
Yousuf, Md. Adib Ibne
Shamim, S.M.
Akanda, Md. Touhidur Rahman
Power Quality Disturbance Classification Using Frequency Domain Features A
title Power Quality Disturbance Classification Using Frequency Domain Features A
title_full Power Quality Disturbance Classification Using Frequency Domain Features A
title_fullStr Power Quality Disturbance Classification Using Frequency Domain Features A
title_full_unstemmed Power Quality Disturbance Classification Using Frequency Domain Features A
title_short Power Quality Disturbance Classification Using Frequency Domain Features A
title_sort power quality disturbance classification using frequency domain features a
topic Power, Quality, Disturbance Classification, Frequency, Domain Features .
url http://hdl.handle.net/123456789/122
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AT shamimsm powerqualitydisturbanceclassificationusingfrequencydomainfeaturesa
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