SPEAKER: Dr. Ayman El-Hag, Electrical Engineering Department, American University of Sharjah, Sharjah, U.A.E.
Partial Discharge (PD) is a localized electrical discharge in the insulation or on the surface of the insulation that partially bridges the two conductors. PD is one of the main reasons of aging of different power system assets that may eventually lead to their complete failure. When PD activities are initiated, the resulting energy is transformed into different forms as mechanical, electrical, thermal and chemical energy. As a result, a wide range of sensors and techniques can be used to detect PD activities.
In this presentation the use of both RF antenna and acoustic emission sensors in PD detection for both transformers and outdoor insulators will be discussed. Artificial intelligent system along with different developed PCB based RF antennas and acoustic emission sensors have been utilized to detect and identify different types of PD in transformer insulation system. Three different Hilbert fractal antennas have been designed and tested. The three proposed designs show different characteristics each covering a different range of frequencies. Design 1 has resonant frequencies from 0.5 – 4.0 GHz, whereas design 2 operates at a smaller band between 0.6 to 2.3 GHz. On the other hand, design 3 has two main resonating bands at 1.3 – 2.3 GHz and 3.8 – 4.15 GHz.
Moreover, a commercial RF antenna with a pass band between 1-2 GHz with a corresponding gain in the range 14.5 - 18 dB have been used to detect different damages in ceramic insulators. A unique signature of the measured RF signals has been found for each defect which facilitates the use of artificial intelligent to automate the classification process. Also, electric field enhancement can cause PD initiation on non-ceramic insulators surface due to water droplet and/or defects in the metallic hardware. RF antenna acoustic sensors have been used to detect the measured PD signals. The presentation will also address briefly the overall classification systems from the feature selection till the use of the different classifiers.
Dr. Ayman El-Hag received his B.S. and M.S. degree from King Fahd University of Petroleum and Minerals and his PhD from the University of Waterloo in 1993, 1998 and 2003 respectively. He joined the Saudi Transformer Co. as a Quality Control Engineer from 1993 till 1999. From January till June 2004, Dr. El Hag worked as a Postdoctoral fellow at the University of Waterloo then he joined the University of Toronto as a Postdoctoral fellow from July 2004 till July 2006. Currently Dr. El-Hag is a professor in the electrical engineering department at the American University of Sharjah. Also, Dr. El-Hag is an adjunct professor at the University of Waterloo. He is the Middle-East Regional Editor of the IEEE DEIS Electrical Insulation Magazine and a member of the IEEE DEIS Outdoor Insulation Technical Committee. Dr. El-Hag main areas of interest are condition monitoring and diagnostics of electrical insulation and pulse power applications in biological systems.
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