TY  - SER
AU  - Thitaporn Tubpong  
AU  - Weerakorn Ongsakul,
AU  - Singh,Jai Govind
AU  - Ekbordin Winijkul,
ED  - PEA-AIT Education Cooperation Project,
ED  - Asian Institute of Technology Fellowship,
TI  - Machine learning-based asset management for power transformer maintenance
T2  - Thesis
PY  - 2020///
CY  - Pathum Thani, Thailand
PB  - Asian Institute of Technology
KW  - Electric power systems
KW  - Maintenance and repair
KW  - Machine learning
KW  - Technique
N1  - A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Energy, School of Environment, Resources and Development; Thesis (M. Eng.) - Asian Institute of Technology, 2020
N2  - The power transformer is a crucial asset in the electrical power system since high cost  and failure can lead to system failure. Power transformer maintenance management is  asset management that can prevent unexpected failure and extend the power  transformer's useful life, saving the replacement cost.  This study presents reliability-centered maintenance that uses machine learning to  predict future conditions and make the maintenance plan. LSTM (Long Short Term  Memory) predicted 2020 power transformer component index from 2019 maintenance  test record then use SVM, Decision tree, Random forest, and k-NN algorithm to  classify to 2020 maintenance condition. Compared with the traditional technique such  as time-based maintenance plan and reliability-center maintenance plan using the  calculation in weighing and score technique. The cost of maintenance determined by  combining routine maintenance cost 35,371 Baht and replacement cost 791,800 Baht,  which calculates the depreciation expense of installing a new power transformer based  on 20 years of useful life.  In this study, the 2020 maintenance plan presents that Reliability-Centered maintenance  with Long Short Term Memory prediction and random forest classification technique  can predict the future power transformer conditions and classify them into suitable  maintenance activities. These techniques make an effective maintenance plan that plans  the suitable maintenance for power transformer, reduce maintenance costs, and extend  the power transformer useful life.
UR  - http://203.159.5.9/ait-thesis/detail.php?q=B16698
ER  -