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Ibrahim Saeh
Universiti Teknologi Malaysia
Computer Science & IT Electrical & Electronics Engineering

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New Classifier Design for Static Security Evaluation Using Artificial In-telligence Techniques Ibrahim Saeh; Wazir Mustafa; Nasir Al-geelani
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 2: April 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (15.022 KB) | DOI: 10.11591/ijece.v6i2.pp870-876

Abstract

This paper proposes evaluation and classification classifier for static security evaluation (SSE) and classifica-tion. Data are generated on (30, 57, 118 and 300) bus IEEE test systems used to design the classifiers. The implementation decision tree methods on several IEEE test systems involved appropriateness SSE and classi-fication by using four algorithms of DT’s. Empirically, with the present of FSA, the implementation results indicate that these classifiers have the capability for system security evaluation and classification. Lastly, FSA is efficient and effective approach for real-time evaluation and classification classifier design.
Identification of Acoustic Signals of Internal Electric Discharges on Glass Insulator under Variable Applied Voltage Nasir A. Al-geelani; M. Afendi M. Piah; Ibrahim Saeh; Nordiana Azlin Othman; Fatin Liyana Muhamedin; N. F. Kasri
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 2: April 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (696.931 KB) | DOI: 10.11591/ijece.v6i2.pp827-834

Abstract

A Partial Discharge (PD) is an unwanted phenomenon in electrical equipment. Therefore it is of great importance to identify different types of PD and assess their severity. This paper investigates the acoustic emissions associated with Internal Discharge (ID) from different types of sources in the time-domain. An experimental setup was arranged in the high voltage laboratory, a chamber with an electrode configuration attached to it was connected to a high voltage transformer for generating various types of PD. A laboratory experiment was done by making the models of these discharges. The test equipment including antennas as a means of detection and digital processing techniques for signal analysis were used. Wavelet signal processing was used to recover the internal discharge acoustic signal by eliminating the noises of many natures.
Co-Authors Fatin Liyana Muhamedin M. Afendi M. Piah N. F. Kasri Nasir A. Al-geelani Nasir Al-geelani Nordiana Azlin Othman Wazir Mustafa