Document Details

Document Type : Article In Journal 
Document Title :
Fault Diagnosis System for Power Transformers
بناء نظام لتشخيص الأعطال لمحولات القوى الكهربائية
 
Subject : Electrical and Computer Engineering 
Document Language : English 
Abstract : This paper introduces an artificial neural network (ANN) based fault diagnosis system (FDS) for power transformers. The system is designed to detect, localize and finally classify faults. The proposed FDS consists of three hierarchical levels. In the first level, a preprocessing procedure for input data is performed. In the second level, an ANN is designed to detect the fault and localize its side. In the third level, there are two sub-diagnosis systems. Each system is dedicated to one side and consists of one ANN designed to classify the fault. This ANN is also cascaded with four parallel ANN's utilized to identify the faulted phase. The performance of FDS is evaluated using samples from local measurements (three-phase primary voltage and primary & secondary currents). These samples were generated using the EMTP simulation of the High-Dam 15.75/500 kV transformer substation in the 500 kV Upper Egypt network. Different fault types were simulated. Fault location and incipience time were also considered. Evaluation results proved that the performance of the proposed FDS is promising. 
ISSN : 1319-1047 
Journal Name : Engineering Sciences Journal 
Volume : 18 
Issue Number : 2 
Publishing Year : 1428 AH
2007 AD 
Number Of Pages : 24 
Article Type : Article 
Added Date : Sunday, October 11, 2009 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
السيد عبدالعليم محمدE. A. MohamedResearcher  
المعتز يوسف عبدالعزيزA. Y. AbdelazizResearcher  
أمل سيد مصطفى A. S. MostafaResearcher  

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