Failure rate estimation for transformer population based on health index through Markov model approach
This work examines the failure rate of the transformer population through the application of the Markov Model (MM) and Health Index (HI). Overall, the condition parameters data extracted from 3,192 oil samples were analysed in this study. The samples were from 370 transformers with the age range bet...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Universiti Putra Malaysia Press
2021
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| Online Access: | http://psasir.upm.edu.my/id/eprint/98151/ http://psasir.upm.edu.my/id/eprint/98151/1/42%20JST-2691-2021.pdf |
| _version_ | 1848862791872544768 |
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| author | Shariffuddin, Nor Shafiqin Azis, Norhafiz Mohd Selva, Amran Yahaya, Muhammad Sharil Jasni, Jasronita Ab Kadir, Mohd Zainal Abidin Talib, Mohd Aizam |
| author_facet | Shariffuddin, Nor Shafiqin Azis, Norhafiz Mohd Selva, Amran Yahaya, Muhammad Sharil Jasni, Jasronita Ab Kadir, Mohd Zainal Abidin Talib, Mohd Aizam |
| author_sort | Shariffuddin, Nor Shafiqin |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | This work examines the failure rate of the transformer population through the application of the Markov Model (MM) and Health Index (HI). Overall, the condition parameters data extracted from 3,192 oil samples were analysed in this study. The samples were from 370 transformers with the age range between 1 and 25 years. First, both HIs and failure rates of transformers were determined based on the condition parameters data of the oil samples known as Oil Quality Analysis (OQA), Dissolved Gas Analysis (DGA), Furanic Compounds Analysis (FCA) and age. A two-parameter exponential function model was applied to represent the relationship between the HI and failure rate. Once the failure rate state was obtained, the non-linear optimisation was used to determine the transition probability for each age band. Next, the future failure rate of the transformer population was computed through the MM prediction model. The goodness-of-fit test and Mean Absolute Percentage Error (MAPE) were utilised to determine the performance of the predicted failure rate. The current study reveals that the future state of the transformer population and failure rate could be predicted through MM based on updated transition probabilities. It is observed that the MAPE between predicted and computed failure rates is 7.3%. |
| first_indexed | 2025-11-15T13:22:39Z |
| format | Article |
| id | upm-98151 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T13:22:39Z |
| publishDate | 2021 |
| publisher | Universiti Putra Malaysia Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-981512022-08-13T00:33:10Z http://psasir.upm.edu.my/id/eprint/98151/ Failure rate estimation for transformer population based on health index through Markov model approach Shariffuddin, Nor Shafiqin Azis, Norhafiz Mohd Selva, Amran Yahaya, Muhammad Sharil Jasni, Jasronita Ab Kadir, Mohd Zainal Abidin Talib, Mohd Aizam This work examines the failure rate of the transformer population through the application of the Markov Model (MM) and Health Index (HI). Overall, the condition parameters data extracted from 3,192 oil samples were analysed in this study. The samples were from 370 transformers with the age range between 1 and 25 years. First, both HIs and failure rates of transformers were determined based on the condition parameters data of the oil samples known as Oil Quality Analysis (OQA), Dissolved Gas Analysis (DGA), Furanic Compounds Analysis (FCA) and age. A two-parameter exponential function model was applied to represent the relationship between the HI and failure rate. Once the failure rate state was obtained, the non-linear optimisation was used to determine the transition probability for each age band. Next, the future failure rate of the transformer population was computed through the MM prediction model. The goodness-of-fit test and Mean Absolute Percentage Error (MAPE) were utilised to determine the performance of the predicted failure rate. The current study reveals that the future state of the transformer population and failure rate could be predicted through MM based on updated transition probabilities. It is observed that the MAPE between predicted and computed failure rates is 7.3%. Universiti Putra Malaysia Press 2021-10-28 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/98151/1/42%20JST-2691-2021.pdf Shariffuddin, Nor Shafiqin and Azis, Norhafiz and Mohd Selva, Amran and Yahaya, Muhammad Sharil and Jasni, Jasronita and Ab Kadir, Mohd Zainal Abidin and Talib, Mohd Aizam (2021) Failure rate estimation for transformer population based on health index through Markov model approach. Pertanika Journal of Science & Technology, 29 (4). pp. 3029-3042. ISSN 0128-7680; EISSN: 2231-8526 http://www.pertanika.upm.edu.my/pjst/browse/regular-issue?article=JST-2691-2021 10.47836/pjst.29.4.42 |
| spellingShingle | Shariffuddin, Nor Shafiqin Azis, Norhafiz Mohd Selva, Amran Yahaya, Muhammad Sharil Jasni, Jasronita Ab Kadir, Mohd Zainal Abidin Talib, Mohd Aizam Failure rate estimation for transformer population based on health index through Markov model approach |
| title | Failure rate estimation for transformer population based on health index through Markov model approach |
| title_full | Failure rate estimation for transformer population based on health index through Markov model approach |
| title_fullStr | Failure rate estimation for transformer population based on health index through Markov model approach |
| title_full_unstemmed | Failure rate estimation for transformer population based on health index through Markov model approach |
| title_short | Failure rate estimation for transformer population based on health index through Markov model approach |
| title_sort | failure rate estimation for transformer population based on health index through markov model approach |
| url | http://psasir.upm.edu.my/id/eprint/98151/ http://psasir.upm.edu.my/id/eprint/98151/ http://psasir.upm.edu.my/id/eprint/98151/ http://psasir.upm.edu.my/id/eprint/98151/1/42%20JST-2691-2021.pdf |