Abstract
Identifying types of Partial Discharge (PD) is very crucial in order to prepare and provide solutions before complete breakdown occurs. Before PD can be identified, detection of the PD is initially required and it can be made by ultrasonic and electrical methods. By using ultrasonic methods, the obtained PD data is conventionally identified using Neural Network (NN) models where it has several disadvantages. It can be said that NN suffer from several drawbacks such as black-box behaviour, inconsistencies in producing results, initialization issues and complex parameter setup. Similarly, electrical method, where PD is identified using PD circuit detectors, sensors and amplification circuits also presents drawbacks such as inconvenient system configuration as well as complex set up. Two novel algorithms are presented in this wok namely ‘Simple Partial Discharge Identifier (SPDI) and Fundamental Partial Discharge Identifier (FPDI) were developed to overcome the PD identification shortcoming…
Metadata
Item Type: | Book Section |
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Creators: | Creators Email / ID Num. Hapeez, Mohammad Shukri UNSPECIFIED |
Subjects: | L Education > LB Theory and practice of education > Higher Education > Dissertations, Academic. Preparation of theses > Malaysia Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Algorithms |
Divisions: | Universiti Teknologi MARA, Shah Alam > Institut Pengajian Siswazah (IPSis) : Institute of Graduate Studies (IGS) |
Series Name: | IPSis Biannual Publication |
Volume: | 7 |
Number: | 7 |
Keywords: | Abstract; Abstract of thesis; Newsletter; Research information; Doctoral graduates; IPSis; IGS; UiTM; Novel algorithms |
Date: | 2015 |
URI: | https://ir.uitm.edu.my/id/eprint/19233 |
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