Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model

Electric transformers; Health; Hidden Markov models; Nonlinear programming; Probability distributions; Quality control; Viterbi algorithm; Condition parameters; Dissolved gas analysis; Distribution transformer; Emission probabilities; Health indices; Non-linear optimization; Remaining useful lives;...

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Main Authors: Selva A.M., Yahaya M.S., Azis N., Ab Kadir M.Z.A., Jasni J., Yang Ghazali Y.Z.
Other Authors: 57203742582
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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spelling my.uniten.dspace-237752023-05-29T14:51:45Z Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model Selva A.M. Yahaya M.S. Azis N. Ab Kadir M.Z.A. Jasni J. Yang Ghazali Y.Z. 57203742582 36083783000 56120698200 25947297000 25632671500 55336569600 Electric transformers; Health; Hidden Markov models; Nonlinear programming; Probability distributions; Quality control; Viterbi algorithm; Condition parameters; Dissolved gas analysis; Distribution transformer; Emission probabilities; Health indices; Non-linear optimization; Remaining useful lives; Transition probabilities; Parameter estimation 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. � 2018 IEEE. Final 2023-05-29T06:51:45Z 2023-05-29T06:51:45Z 2018 Conference Paper 10.1109/PECON.2018.8684158 2-s2.0-85064749197 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064749197&doi=10.1109%2fPECON.2018.8684158&partnerID=40&md5=a26d32507d3602449f8d918060d51bc0 https://irepository.uniten.edu.my/handle/123456789/23775 8684158 288 292 All Open Access, Green Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Electric transformers; Health; Hidden Markov models; Nonlinear programming; Probability distributions; Quality control; Viterbi algorithm; Condition parameters; Dissolved gas analysis; Distribution transformer; Emission probabilities; Health indices; Non-linear optimization; Remaining useful lives; Transition probabilities; Parameter estimation
author2 57203742582
author_facet 57203742582
Selva A.M.
Yahaya M.S.
Azis N.
Ab Kadir M.Z.A.
Jasni J.
Yang Ghazali Y.Z.
format Conference Paper
author Selva A.M.
Yahaya M.S.
Azis N.
Ab Kadir M.Z.A.
Jasni J.
Yang Ghazali Y.Z.
spellingShingle Selva A.M.
Yahaya M.S.
Azis N.
Ab Kadir M.Z.A.
Jasni J.
Yang Ghazali Y.Z.
Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
author_sort Selva A.M.
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 Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806423248498327552
score 13.223943