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Reference: ISH2015_82

Type:
ISH Collection
Title:

On Line Detection of Partial Discharge in High Voltage Equipment Using Acoustic Emission Technique

 

Abstracts

Throughout the decade, generation of the high voltage (HV) electrical power gradually increases due to increase of demand in industrial growth as well as to meet the demand for modern civilization. Extensive electrical power networks installations have been built in industrialized countries and are being constructed in developing countries at a rapid increasing rate. The major function of such power systems is to generate, transport and distribute electrical energy over large geographical areas in an economical manner while ensuring a high degree of reliability and quality of supply. Apart from these, high voltages are also widely used in many industrial as well as engineering applications. In all such applications, the high cost and comparatively long life span of HV power equipments are need to be take care of continuously from its degradation. The degradation of insulation is responsible mainly for internal discharge i.e., Partial discharge (PD). High voltage insulation condition monitoring is one of the major important diagnostic tools for servicing the better quality of power. Therefore, on-line detection of PD in high voltage power equipment is getting more importance in the field of insulation diagnosis for early detection of incipient fault. In this work, detection of PD in the oil-paper insulation model has been carried out in high voltage laboratory using Acoustic Emission Technique. The observed PD signal is also analysis with the Fast Fourier Transform (FFT) and the Short Time Fourier Transform (SFFT) algorithm which is having the potential to find out the frequency component of PD signal with respect to time. This study intends to process the UHF signals obtained from indigenous developed experimental setup. The technique is having great potential to detect the PD activity inside the high voltage power equipment at any time without any power failure .
 

File Size: 690,8 KB

Year: 2015

 
 
 
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