IJSTE

CALL FOR PAPERS : December-2022

Submission Last Date
25-December-22
Submit Manuscript Online

FOR AUTHORS

FOR REVIEWERS

ARCHIEVES

DOWNLOADS

Open Access



CopyScape
Creative Commons License

Condition Assessment of Power Transformer Winding by FRA using Different AI Techniques


Author(s):

Bhatt Palak R. , L. D. COLLEGE OF ENGINEERING; Nilesh D. Rabara, L. D. COLLEGE OF ENGINEERING

Keywords:

Transformer; FRA; ANN; Winding Parameters; PNN; GRNN

Abstract:

There are many methods of fault diagnosis of Power transformer but among all these FRA is the most suitable method for electrical and /or mechanical faults of a transformer. The concept of FRA has been successfully used as a diagnostic technique to detect the winding deformation of power transformer. In FRA measurement, the nine statistical indicators are used to detect the deviation in FRA signature. The effects of different winding parameters on FRA signature is described. The artificial neural network approach has been proposed to complement these nine indicators. ANN can be used to increase the efficiency and accuracy of diagnosis system. Neural network toolbox is used to train the multilayer feed-forward neural network. The Probabilistic neural network (PNN) approach and General Regression Neural network (GRNN) has been introduced due to its higher sensitivity and accuracy over the neural network. Neural pattern recognition toolbox is used to train the multilayer probabilistic neural network. Different practical case studies and their data are used to train and test the multilayer feed-forward neural network, probabilistic neural network and general regression neural network.Among all these AI techniques PNN gives the best accuracy result. In this work Matlab-2014 is to be used.


Other Details:

Manuscript Id :IJSTEV1I12077
Published in :Volume : 1, Issue : 12
Publication Date: 01/07/2015
Page(s): 220-227
Download Article

IMPACT FACTOR

4.753

NEWS & UPDATES

Submit Article

Dear Authors, You can submit your article to our journal at the following link: http://www.ijste.org/Submit

Impact Factor

The Impact Factor of our Journal is 4.753 (Year - 2016)
3.905 (Year - 2015) 2.895(Year -2014)

Click Here

Submit Payment Online

Dear Authors, Now you can submit the payment receipt to our journal online at the following link: index.php?p=Payment

1

1

GLOBAL INDEXING



















Computer Science Directory. We are listed under Computer Research Institutes category

Share on Social media

Home | Privacy Policy | Terms & Conditions | Refund Policy | Feedback | Contact Us
Copyright © 2014 ijste.org All rights reserved