Prediction of salt contamination on high voltage insulators in rainy season using regression technique

The severity of contamination on the high voltage insulator surfaces is the significant factor in determining the level of outdoor insulation and in choosing the types of insulators. In the equatorial region, the most dangerous kind of contamination is salt contamination. A regression technique has...

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Main Authors: S. Ahmad, Ahmad, Ahmad, Hussein, Salam, Md. Abdus, Tamsir, T, Buntat, Z, Mustafa, M. W.
Format: Article
Language:English
Published: 2000
Subjects:
Online Access:http://eprints.utm.my/2178/
http://eprints.utm.my/2178/1/Ahmad2000__PredictionofSaltContaminationon.pdf
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author S. Ahmad, Ahmad
Ahmad, Hussein
Salam, Md. Abdus
Tamsir, T
Buntat, Z
Mustafa, M. W.
author_facet S. Ahmad, Ahmad
Ahmad, Hussein
Salam, Md. Abdus
Tamsir, T
Buntat, Z
Mustafa, M. W.
author_sort S. Ahmad, Ahmad
building UTeM Institutional Repository
collection Online Access
description The severity of contamination on the high voltage insulator surfaces is the significant factor in determining the level of outdoor insulation and in choosing the types of insulators. In the equatorial region, the most dangerous kind of contamination is salt contamination. A regression technique has been used to develop a modified equivalent salt deposit density (ESDD) mathematical model with respect to meteorological conditions. This model provides a useful way for predicting contamination level and for determining frequency of washing the insulators in a given contaminated area
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institution Universiti Teknologi Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T20:39:58Z
publishDate 2000
recordtype eprints
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spelling utm-21782010-06-01T03:01:32Z http://eprints.utm.my/2178/ Prediction of salt contamination on high voltage insulators in rainy season using regression technique S. Ahmad, Ahmad Ahmad, Hussein Salam, Md. Abdus Tamsir, T Buntat, Z Mustafa, M. W. TK Electrical engineering. Electronics Nuclear engineering The severity of contamination on the high voltage insulator surfaces is the significant factor in determining the level of outdoor insulation and in choosing the types of insulators. In the equatorial region, the most dangerous kind of contamination is salt contamination. A regression technique has been used to develop a modified equivalent salt deposit density (ESDD) mathematical model with respect to meteorological conditions. This model provides a useful way for predicting contamination level and for determining frequency of washing the insulators in a given contaminated area 2000-09-24 Article PeerReviewed application/pdf en http://eprints.utm.my/2178/1/Ahmad2000__PredictionofSaltContaminationon.pdf S. Ahmad, Ahmad and Ahmad, Hussein and Salam, Md. Abdus and Tamsir, T and Buntat, Z and Mustafa, M. W. (2000) Prediction of salt contamination on high voltage insulators in rainy season using regression technique. TENCON 2000. Proceedings , 3 . pp. 184-189.
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
S. Ahmad, Ahmad
Ahmad, Hussein
Salam, Md. Abdus
Tamsir, T
Buntat, Z
Mustafa, M. W.
Prediction of salt contamination on high voltage insulators in rainy season using regression technique
title Prediction of salt contamination on high voltage insulators in rainy season using regression technique
title_full Prediction of salt contamination on high voltage insulators in rainy season using regression technique
title_fullStr Prediction of salt contamination on high voltage insulators in rainy season using regression technique
title_full_unstemmed Prediction of salt contamination on high voltage insulators in rainy season using regression technique
title_short Prediction of salt contamination on high voltage insulators in rainy season using regression technique
title_sort prediction of salt contamination on high voltage insulators in rainy season using regression technique
topic TK Electrical engineering. Electronics Nuclear engineering
url http://eprints.utm.my/2178/
http://eprints.utm.my/2178/1/Ahmad2000__PredictionofSaltContaminationon.pdf