Proposed diagnostic methodology using the cross‐correlation coefficient factor technique for power transformer fault identification-Reference-Cited by-同舟云学术

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Proposed diagnostic methodology using the cross‐correlation coefficient factor technique for power transformer fault identification

Published:2017-03 Issue:3 Volume:11 Page:412-422
ISSN:1751-8660
Container-title:IET Electric Power Applications
language:en
Short-container-title:IET Electric Power Applications

Author:

Saleh Saber M.¹,EL‐Hoshy Salah Hamdy²,Gouda Osama E.³

Affiliation:

1. Department of Electrical Power and MachinesFaculty of EngineeringFayoum UniversityAl FayoumEgypt

2. Middle Egypt Electricity ZoneEgyptian Electricity Transmission CompanyEl‐FayoumEgypt

3. Department of Electrical Power and MachinesFaculty of EngineeringCairo UniversityCairoEgypt

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-epa.2016.0545

Reference24 articles.

1. Examining the ageing of transformer insulation using FRA and FDS techniques

2. FRA vs. short circuit impedance measurement in detection of mechanical defects within large power transformer

3. Sweep frequency response analysis (SFRA) for the assessment of winding displacements and deformation in power transformers

4. A new technique for a better sweep frequency response analysis interpretation

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1. A new approach towards more accurate modeling of mechanical defects in power transformer windings;Measurement;2025-01

2. Deformations in Power Transformers by Sweep Frequency Response Analysis and a Sample Field Study;European Journal of Technic;2023-12-22

3. A New Procedure for High Frequency Decentralized Modeling Parameters Identification of a Transformer Winding Construction Using Frequency Response Analysis Based on Logistic Chaotic JAYA Algorithm;Russian Journal of Nondestructive Testing;2023-04

4. Pearson Correlation in Determination of Quality of Current Transformers;Sensors;2023-03-01

5. Fault detection and diagnosis in power transformers: a comprehensive review and classification of publications and methods;Electric Power Systems Research;2022-08

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