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dc.contributor.advisorChakma, Shoili
dc.contributor.advisorSagor, Dr. Hasanuzzaman
dc.contributor.authorZaman, MD.Arif Uz
dc.contributor.authorMortoza, Tasnim
dc.contributor.authorAbid, Zawad Hasan
dc.contributor.authorMusa, MD. Abu
dc.date.accessioned2018-02-26T09:09:35Z
dc.date.available2018-02-26T09:09:35Z
dc.date.copyright2017
dc.date.issued2017-12-24
dc.identifier.otherID 12210011
dc.identifier.otherID 12221042
dc.identifier.otherID 13321036
dc.identifier.otherID 13321038
dc.identifier.urihttp://hdl.handle.net/10361/9560
dc.descriptionThis thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2017.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (page 42).
dc.description.abstractA 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.en_US
dc.description.statementofresponsibilityMD.Arif Uz Zaman
dc.description.statementofresponsibilityTasnim Mortoza
dc.description.statementofresponsibilityZawad Hasan Abid
dc.description.statementofresponsibilityMD. Abu Musa
dc.format.extent43 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC 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.
dc.subjectElectrical Network Frequencyen_US
dc.subjectPower griden_US
dc.titlePower grid classification through Electrical Network Frequencyen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Electrical and Electronic Engineering, BRAC University
dc.description.degreeB. Electrical and Electronic Engineering


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