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...
| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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IEEE
2018
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| Online Access: | http://psasir.upm.edu.my/id/eprint/68361/ http://psasir.upm.edu.my/id/eprint/68361/1/Estimation%20of%20transformers%20health%20index%20based%20on%20condition%20parameter%20factor%20and%20hidden%20Markov%20model.pdf |
| _version_ | 1848856105118072832 |
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| author | Mohd Selva, Amran Yahaya, Muhammad Sharil Azis, Norhafiz Ab Kadir, Mohd Zainal Abidin Jasni, Jasronita Yang Ghazali, Young Zaidey |
| 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 |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T11:36:22Z |
| format | Conference or Workshop Item |
| id | upm-68361 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:36:22Z |
| publishDate | 2018 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-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 |
| 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 |
| title | 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_short | 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 |
| url | http://psasir.upm.edu.my/id/eprint/68361/ http://psasir.upm.edu.my/id/eprint/68361/ http://psasir.upm.edu.my/id/eprint/68361/1/Estimation%20of%20transformers%20health%20index%20based%20on%20condition%20parameter%20factor%20and%20hidden%20Markov%20model.pdf |