TY - GEN
T1 - Generation of synthetic datasets for transformer's dissolved gas analysis using Conte-Carlo simulation
AU - Babu, Eaby Kollonoor
AU - Bashir, Imran
AU - Pillai, Gobind
AU - Jyothi, Kiran Chandrakumar
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/31
Y1 - 2021/8/31
N2 - The fault diagnosis in power transformers is carried out using Dissolved Gas Analysis (DGA). Although DGA does provide key information for fault detection, the method is inherently complex. Several methods have been developed for DGA, but still possess challenges in accurately detecting the fault. A method has been developed to generate synthetic data using Monte-Carlo simulation. The generated synthetic data is feed into DGA excel tool to investigate the accuracy of fault detection. The synthetic data can be used to further enhance the DGA tool, improve its accuracy and investigate the inclusive faults. A model has been proposed for the integration of synthetic data generator with DGA tool for machine learning and to obtain an automated and improved DGA tool for fault diagnoses in power transformers.
AB - The fault diagnosis in power transformers is carried out using Dissolved Gas Analysis (DGA). Although DGA does provide key information for fault detection, the method is inherently complex. Several methods have been developed for DGA, but still possess challenges in accurately detecting the fault. A method has been developed to generate synthetic data using Monte-Carlo simulation. The generated synthetic data is feed into DGA excel tool to investigate the accuracy of fault detection. The synthetic data can be used to further enhance the DGA tool, improve its accuracy and investigate the inclusive faults. A model has been proposed for the integration of synthetic data generator with DGA tool for machine learning and to obtain an automated and improved DGA tool for fault diagnoses in power transformers.
KW - Dissolved gas analysis
KW - Fault diagnosis
KW - Monte-Carlo simulation
KW - Power transformers
UR - http://www.scopus.com/inward/record.url?scp=85116700000&partnerID=8YFLogxK
U2 - 10.1109/UPEC50034.2021.9548242
DO - 10.1109/UPEC50034.2021.9548242
M3 - Conference contribution
AN - SCOPUS:85116700000
T3 - 2021 56th International Universities Power Engineering Conference: Powering Net Zero Emissions, UPEC 2021 - Proceedings
BT - 2021 56th International Universities Power Engineering Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 56th International Universities Power Engineering Conference, UPEC 2021
Y2 - 31 August 2021 through 3 September 2021
ER -
