Estimation of transformers health index based on condition parameter factor and hidden Markov model

This paper presents a study to estimate future Health Index (HI) of transformer population based on Hidden Markov Model (HMM). In this paper, HI was represented as hidden state and the condition parameter factors in the HI algorithm namely Dissolved Gas Analysis Factor (DGAF), Oil Quality Analysis F...

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Main Authors: Mohd Selva, Amran, Yahaya, Muhammad Sharil, Azis, Norhafiz, Ab Kadir, Mohd Zainal Abidin, Jasni, Jasronita, Yang Ghazali, Young Zaidey
Format: Conference or Workshop Item
Language:English
Published: IEEE 2018
Online Access:http://psasir.upm.edu.my/id/eprint/68361/1/Estimation%20of%20transformers%20health%20index%20based%20on%20condition%20parameter%20factor%20and%20hidden%20Markov%20model.pdf
http://psasir.upm.edu.my/id/eprint/68361/
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Institution: Universiti Putra Malaysia
Language: English
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spelling my.upm.eprints.683612019-05-10T08:32:28Z http://psasir.upm.edu.my/id/eprint/68361/ Estimation of transformers health index based on condition parameter factor and hidden Markov model Mohd Selva, Amran Yahaya, Muhammad Sharil Azis, Norhafiz Ab Kadir, Mohd Zainal Abidin Jasni, Jasronita Yang Ghazali, Young Zaidey This paper presents a study to estimate future Health Index (HI) of transformer population based on Hidden Markov Model (HMM). In this paper, HI was represented as hidden state and the condition parameter factors in the HI algorithm namely Dissolved Gas Analysis Factor (DGAF), Oil Quality Analysis Factor (OQAF) and Furfural Analysis Factor (FAF) were represented as the observable states. A case study of 1130 oil samples from 373 oil-typed distribution transformers (33/11 kV and 30 MVA) were examined. First, the mean for HI in each year was computed and the transition probabilities for the condition data were obtained based on non-linear optimization technique. Next, the emission probabilities for each of the condition parameter factors were derived based on frequency of occurrence method. Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. Finally, the predicted and computed HI were compared to the hypothesized distribution. Majority of the predicted HI agrees with computed HI. Predicted HI based on OQAF records the most accurate estimation throughout the sampling years. Inconsistencies are observed in year 2 and between year 7 and 10 for the predicted HI based on FAF. The predicted HI based on DGAF is in line with the computed HI during the first 2 years and deviates at the later stage of the sampling period. IEEE 2018 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/68361/1/Estimation%20of%20transformers%20health%20index%20based%20on%20condition%20parameter%20factor%20and%20hidden%20Markov%20model.pdf Mohd Selva, Amran and Yahaya, Muhammad Sharil and Azis, Norhafiz and Ab Kadir, Mohd Zainal Abidin and Jasni, Jasronita and Yang Ghazali, Young Zaidey (2018) Estimation of transformers health index based on condition parameter factor and hidden Markov model. In: 2018 IEEE 7th International Conference on Power and Energy (PECon), 3-4 Dec. 2018, Berjaya Times Square Hotel, Kuala Lumpur, Malaysia. (pp. 288-292). 10.1109/PECON.2018.8684158
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description This paper presents a study to estimate future Health Index (HI) of transformer population based on Hidden Markov Model (HMM). In this paper, HI was represented as hidden state and the condition parameter factors in the HI algorithm namely Dissolved Gas Analysis Factor (DGAF), Oil Quality Analysis Factor (OQAF) and Furfural Analysis Factor (FAF) were represented as the observable states. A case study of 1130 oil samples from 373 oil-typed distribution transformers (33/11 kV and 30 MVA) were examined. First, the mean for HI in each year was computed and the transition probabilities for the condition data were obtained based on non-linear optimization technique. Next, the emission probabilities for each of the condition parameter factors were derived based on frequency of occurrence method. Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. Finally, the predicted and computed HI were compared to the hypothesized distribution. Majority of the predicted HI agrees with computed HI. Predicted HI based on OQAF records the most accurate estimation throughout the sampling years. Inconsistencies are observed in year 2 and between year 7 and 10 for the predicted HI based on FAF. The predicted HI based on DGAF is in line with the computed HI during the first 2 years and deviates at the later stage of the sampling period.
format Conference or Workshop Item
author Mohd Selva, Amran
Yahaya, Muhammad Sharil
Azis, Norhafiz
Ab Kadir, Mohd Zainal Abidin
Jasni, Jasronita
Yang Ghazali, Young Zaidey
spellingShingle Mohd Selva, Amran
Yahaya, Muhammad Sharil
Azis, Norhafiz
Ab Kadir, Mohd Zainal Abidin
Jasni, Jasronita
Yang Ghazali, Young Zaidey
Estimation of transformers health index based on condition parameter factor and hidden Markov model
author_facet Mohd Selva, Amran
Yahaya, Muhammad Sharil
Azis, Norhafiz
Ab Kadir, Mohd Zainal Abidin
Jasni, Jasronita
Yang Ghazali, Young Zaidey
author_sort Mohd Selva, Amran
title Estimation of transformers health index based on condition parameter factor and hidden Markov model
title_short Estimation of transformers health index based on condition parameter factor and hidden Markov model
title_full Estimation of transformers health index based on condition parameter factor and hidden Markov model
title_fullStr Estimation of transformers health index based on condition parameter factor and hidden Markov model
title_full_unstemmed Estimation of transformers health index based on condition parameter factor and hidden Markov model
title_sort estimation of transformers health index based on condition parameter factor and hidden markov model
publisher IEEE
publishDate 2018
url http://psasir.upm.edu.my/id/eprint/68361/1/Estimation%20of%20transformers%20health%20index%20based%20on%20condition%20parameter%20factor%20and%20hidden%20Markov%20model.pdf
http://psasir.upm.edu.my/id/eprint/68361/
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