الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
The occurrence of the Partial Discharge (PD) inside the high voltage apparatus especially in power transformer due to some defect in its insulation system results in a catastrophic failure. In this work, the internal PD of the power transformer was predicted based on dissolved gas analysis techniques (DGA) as well as the severity of PD due to the thermodynamic theory was determined. The magnitude of PD was determined using electrical detection according to IEC 60270. Finally, the location of the PD source was identified based on the acoustic detection. All of the above processes can protect the transformer from undesirable outage or failure and help in the maintenance strategy procedures to isolate the reason for occurring PD.
In the first part of this work, the dissolved gas analysis techniques (DGA) were used to determine fault types of power transformers based on the concentration of dissolved combustion gases such as Hydrogen (H2), Methane (CH4), Ethan (C2H6), Ethylene (C2H4), Acetylene (C2H2), and Carbon mono-oxide (CO). On the other hand, these DGA techniques cannot identify the severity of the fault types. Therefore, a thermodynamic theory, which was based on the starting decomposing materials (n-Octane (C8H18) and Eicosane (C20H42)), was used to estimate the severity of the transformer faults especially, partial discharge. Determination of partial discharge severity inside the transformer was performed relying on the constructed fuzzy logic system (FLS) that was constructed based on the rules of the Duval triangle technique. The work focused on the influence of starting decomposing material on the severity of partial discharge. The results demonstrated that varying starting decomposition material resulted in a change in the partial discharge fault severity. In the second part, the electrical detection which based on IEC 60270 was represented to determine the magnitude of the PD inside the transformer to avoid the undesired outage. Measuring the magnitude of the PD by the electrical detection device (MPD 600) that has many kits. MPD600 is an acquisition and analysis for detecting, recording and analyzing the PD. PD Measuring circuit of MPD600 connected with a scale model which has two different gap configuration such point to plane model and plane to plane model as well as connected with on-site case study such power transformer 220/66/11 kV according to IEC60270 with an optical interface (computer) that has Metronix software in case of partial prediction. Finally in the third part, the acoustic detection was presented in order to detect the PD source location. The determination of the PD source location is very necessary to start the maintenance procedures and isolate the reason for occurring PD. PD location can be determined by capturing the acoustic signals that emitted from the PD source. Then, the proposed algorithm is based on the computation of the time difference of arrival (TDOA) between the signals. The location of PD can be accurately determined depends on the precision degree of the TDOA. An experimental work is built in the first case study to develop a PD using point to plane gap configuration in the insulation oil that fills the Acrylic tank, and four piezoelectric (PZT) sensors which are mounted on the Acrylic tank to receive the acoustic signals. Therefore, the sensors are coupled with acoustic PD detector and the PD detector outputs are applied to the four-channel digital oscilloscope to measure the acoustic signals. The signal is converted to digit numbers to express the characteristic of the signal and then the time difference between the reference signal and the other signal is estimated using the cross correlation function. In addition the partial location is determined for on-site case study of power transformer.