Power grid classification through Electrical Network Frequency
This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2017.
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| Формат: | Диссертация |
| Язык: | English |
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BRAC University
2018
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| Online-ссылка: | http://hdl.handle.net/10361/9560 |
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10361-95602023-01-23T08:59:53Z Power grid classification through Electrical Network Frequency Zaman, MD.Arif Uz Mortoza, Tasnim Abid, Zawad Hasan Musa, MD. Abu Chakma, Shoili Sagor, Dr. Hasanuzzaman Department of Electrical and Electronic Engineering, BRAC University Electrical Network Frequency Power grid This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2017. Cataloged from PDF version of thesis. Includes bibliographical references (page 42). A general review of certain techniques for power grid analysis and power signatures detection is presented in this paper. After some motivation and research on the existing trends on solving this issue of supply network system problems, particular techniques are described with proper analysis. Identifying such issues through a series of methodological steps, a solution can be predicted for designing better grids for a futuristic system. Such identi cations can be done through software analysis of the power grid data. The main objective of this paper is the chronological overview and analysis of audio signals received from certain grid machines that can be utilized to detect errors or irregularities through pattern recognition technique and exploring feature detection algorithm. Performing a software analysis of electrical network frequency extraction, pattern recognition and accuracy measurement, certain information can be obtained. These information can be compared and matched in di erent ratios and percentages to get better accuracy of results. Finally, a solution for the existing issue can be predicted based on the analyzed results. The techniques for power grid analysis and detection followed in this research can be very useful for a number of other software based research works of similar interests. MD.Arif Uz Zaman Tasnim Mortoza Zawad Hasan Abid MD. Abu Musa B. Electrical and Electronic Engineering 2018-02-26T09:09:35Z 2018-02-26T09:09:35Z 2017 2017-12-24 Thesis ID 12210011 ID 12221042 ID 13321036 ID 13321038 http://hdl.handle.net/10361/9560 en BRAC University thesis is protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 43 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Electrical Network Frequency Power grid |
| spellingShingle |
Electrical Network Frequency Power grid Zaman, MD.Arif Uz Mortoza, Tasnim Abid, Zawad Hasan Musa, MD. Abu Power grid classification through Electrical Network Frequency |
| description |
This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2017. |
| author2 |
Chakma, Shoili |
| author_facet |
Chakma, Shoili Zaman, MD.Arif Uz Mortoza, Tasnim Abid, Zawad Hasan Musa, MD. Abu |
| format |
Thesis |
| author |
Zaman, MD.Arif Uz Mortoza, Tasnim Abid, Zawad Hasan Musa, MD. Abu |
| author_sort |
Zaman, MD.Arif Uz |
| title |
Power grid classification through Electrical Network Frequency |
| title_short |
Power grid classification through Electrical Network Frequency |
| title_full |
Power grid classification through Electrical Network Frequency |
| title_fullStr |
Power grid classification through Electrical Network Frequency |
| title_full_unstemmed |
Power grid classification through Electrical Network Frequency |
| title_sort |
power grid classification through electrical network frequency |
| publisher |
BRAC University |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10361/9560 |
| work_keys_str_mv |
AT zamanmdarifuz powergridclassificationthroughelectricalnetworkfrequency AT mortozatasnim powergridclassificationthroughelectricalnetworkfrequency AT abidzawadhasan powergridclassificationthroughelectricalnetworkfrequency AT musamdabu powergridclassificationthroughelectricalnetworkfrequency |
| _version_ |
1814307623246233600 |