Application of statistical distribution models to predict health index for condition-based management of transformers
In this study, statistical distribution model (SDM) is used to predict the health index (HI) of transformers by utilizing the condition parameters data from dissolved gas analysis (DGA), oil quality analysis (OQA), and furanic compound analysis (FCA), respectively. First, the individual condition pa...
Saved in:
Main Authors: | , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021
|
Online Access: | http://eprints.utem.edu.my/id/eprint/25944/2/APPLICATION%20OF%20STATISTICAL%20DISTRIBUTION%20MODELS%20TO%20PREDICT%20HEALTH%20INDEX%20FOR%20CONDITION-BASED%20MANAGEMENT%20OF%20TRANSFORMERS.PDF http://eprints.utem.edu.my/id/eprint/25944/ https://www.mdpi.com/2076-3417/11/6/2728 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utem.eprints.25944 |
---|---|
record_format |
eprints |
spelling |
my.utem.eprints.259442022-05-30T10:21:16Z http://eprints.utem.edu.my/id/eprint/25944/ Application of statistical distribution models to predict health index for condition-based management of transformers Azis, Norhafiz Mohd Selva, Amran Shariffudin, Nor Shafiqin Yahaya, Muhammad Sharil Ab Kadir, Mohd Zainal Abidin Jasni, Jasronita Talib, Mohd Aizam In this study, statistical distribution model (SDM) is used to predict the health index (HI) of transformers by utilizing the condition parameters data from dissolved gas analysis (DGA), oil quality analysis (OQA), and furanic compound analysis (FCA), respectively. First, the individual condition parameters data were categorized based on transformer age from year 1 to 15. Next, the individual condition parameters data for every age were fitted while using a probability plot to find the representative distribution models. The distribution parameters were calculated based on 95% confidence level and extrapolated from year 16 to 25 through representative fitting models. The individual condition parameters data within the period were later calculated based on the estimated distribution parameters through the inverse cumulative distribution function (ICDF) of the selected distribution models. The predicted HI was then determined based on the conventional scoring method. The Chi-square test for statistical hypothesis reveals that the predicted HI for the transformer data is quite close to the calculated HI. The average percentage of absolute error is 2.7%. The HI that is predicted based on SDM yields 97.83% accuracy for the transformer data. MDPI AG 2021-03-18 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/25944/2/APPLICATION%20OF%20STATISTICAL%20DISTRIBUTION%20MODELS%20TO%20PREDICT%20HEALTH%20INDEX%20FOR%20CONDITION-BASED%20MANAGEMENT%20OF%20TRANSFORMERS.PDF Azis, Norhafiz and Mohd Selva, Amran and Shariffudin, Nor Shafiqin and Yahaya, Muhammad Sharil and Ab Kadir, Mohd Zainal Abidin and Jasni, Jasronita and Talib, Mohd Aizam (2021) Application of statistical distribution models to predict health index for condition-based management of transformers. Applied Sciences (Switzerland), 11 (6). pp. 1-20. ISSN 2076-3417 https://www.mdpi.com/2076-3417/11/6/2728 10.3390/app11062728 |
institution |
Universiti Teknikal Malaysia Melaka |
building |
UTEM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknikal Malaysia Melaka |
content_source |
UTEM Institutional Repository |
url_provider |
http://eprints.utem.edu.my/ |
language |
English |
description |
In this study, statistical distribution model (SDM) is used to predict the health index (HI) of transformers by utilizing the condition parameters data from dissolved gas analysis (DGA), oil quality analysis (OQA), and furanic compound analysis (FCA), respectively. First, the individual condition parameters data were categorized based on transformer age from year 1 to 15. Next, the individual condition parameters data for every age were fitted while using a probability plot to find the representative distribution models. The distribution parameters were calculated based on 95% confidence level and extrapolated from year 16 to 25 through representative fitting models. The individual condition parameters data within the period were later calculated based on the estimated distribution parameters through the inverse cumulative distribution function (ICDF) of the selected distribution models. The predicted HI was then determined based on the conventional scoring method. The Chi-square test for statistical hypothesis reveals that the predicted HI for the transformer data is quite close to the calculated HI. The average percentage of absolute error is 2.7%. The HI that is predicted based on SDM yields 97.83% accuracy for the transformer data. |
format |
Article |
author |
Azis, Norhafiz Mohd Selva, Amran Shariffudin, Nor Shafiqin Yahaya, Muhammad Sharil Ab Kadir, Mohd Zainal Abidin Jasni, Jasronita Talib, Mohd Aizam |
spellingShingle |
Azis, Norhafiz Mohd Selva, Amran Shariffudin, Nor Shafiqin Yahaya, Muhammad Sharil Ab Kadir, Mohd Zainal Abidin Jasni, Jasronita Talib, Mohd Aizam Application of statistical distribution models to predict health index for condition-based management of transformers |
author_facet |
Azis, Norhafiz Mohd Selva, Amran Shariffudin, Nor Shafiqin Yahaya, Muhammad Sharil Ab Kadir, Mohd Zainal Abidin Jasni, Jasronita Talib, Mohd Aizam |
author_sort |
Azis, Norhafiz |
title |
Application of statistical distribution models to predict health index for condition-based management of transformers |
title_short |
Application of statistical distribution models to predict health index for condition-based management of transformers |
title_full |
Application of statistical distribution models to predict health index for condition-based management of transformers |
title_fullStr |
Application of statistical distribution models to predict health index for condition-based management of transformers |
title_full_unstemmed |
Application of statistical distribution models to predict health index for condition-based management of transformers |
title_sort |
application of statistical distribution models to predict health index for condition-based management of transformers |
publisher |
MDPI AG |
publishDate |
2021 |
url |
http://eprints.utem.edu.my/id/eprint/25944/2/APPLICATION%20OF%20STATISTICAL%20DISTRIBUTION%20MODELS%20TO%20PREDICT%20HEALTH%20INDEX%20FOR%20CONDITION-BASED%20MANAGEMENT%20OF%20TRANSFORMERS.PDF http://eprints.utem.edu.my/id/eprint/25944/ https://www.mdpi.com/2076-3417/11/6/2728 |
_version_ |
1734303572774879232 |
score |
13.160551 |