Generation of synthetic datasets for transformer’s dissolved gas analysis using Monte-Carlo Simulation

Eaby Kollonoor Babu; IMRAN Bashir; Gobind Pillai; Kiran Chandrakumar Jyothi

doi:10.1109/upec50034.2021.9548242

Generation of synthetic datasets for transformer’s dissolved gas analysis using Monte-Carlo Simulation

Eaby Kollonoor Babu, IMRAN Bashir, Gobind Pillai, Kiran Chandrakumar Jyothi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

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.

Original language	English
Title of host publication	2021 56th International Universities Power Engineering Conference
Subtitle of host publication	Powering Net Zero Emissions, UPEC 2021 - Proceedings
Publisher	IEEE
ISBN (Electronic)	9781665443890
DOIs	https://doi.org/10.1109/upec50034.2021.9548242
Publication status	Published - 30 Sept 2021
Event	56th International Universities Power Engineering Conference - Middlesbrough, United Kingdom Duration: 31 Aug 2021 → 3 Sept 2021 https://www.ieee-pes.org/meetings-and-conferences/conference-calendar/monthly-view/166-technically-cosponsored-by-pes/883-upec-2021

Publication series

Name	2021 56th International Universities Power Engineering Conference (UPEC)

Conference

Conference	56th International Universities Power Engineering Conference
Abbreviated title	UPEC
Country/Territory	United Kingdom
City	Middlesbrough
Period	31/08/21 → 3/09/21
Internet address	https://www.ieee-pes.org/meetings-and-conferences/conference-calendar/monthly-view/166-technically-cosponsored-by-pes/883-upec-2021

Access to Document

10.1109/upec50034.2021.9548242

Full textAccepted author manuscript, 361 KBLicence: CC BY-NC-ND

Cite this

Kollonoor Babu, E., Bashir, IMRAN., Pillai, G., & Jyothi, K. C. (2021). Generation of synthetic datasets for transformer’s dissolved gas analysis using Monte-Carlo Simulation. In 2021 56th International Universities Power Engineering Conference: Powering Net Zero Emissions, UPEC 2021 - Proceedings (2021 56th International Universities Power Engineering Conference (UPEC)). IEEE. https://doi.org/10.1109/upec50034.2021.9548242

Kollonoor Babu, Eaby ; Bashir, IMRAN ; Pillai, Gobind et al. / Generation of synthetic datasets for transformer’s dissolved gas analysis using Monte-Carlo Simulation. 2021 56th International Universities Power Engineering Conference: Powering Net Zero Emissions, UPEC 2021 - Proceedings. IEEE, 2021. (2021 56th International Universities Power Engineering Conference (UPEC)).

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title = "Generation of synthetic datasets for transformer{\textquoteright}s dissolved gas analysis using Monte-Carlo Simulation",

abstract = "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.",

author = "{Kollonoor Babu}, Eaby and IMRAN Bashir and Gobind Pillai and Jyothi, {Kiran Chandrakumar}",

year = "2021",

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day = "30",

doi = "10.1109/upec50034.2021.9548242",

language = "English",

series = "2021 56th International Universities Power Engineering Conference (UPEC)",

publisher = "IEEE",

booktitle = "2021 56th International Universities Power Engineering Conference",

note = "56th International Universities Power Engineering Conference, UPEC ; Conference date: 31-08-2021 Through 03-09-2021",

url = "https://www.ieee-pes.org/meetings-and-conferences/conference-calendar/monthly-view/166-technically-cosponsored-by-pes/883-upec-2021",

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Kollonoor Babu, E, Bashir, IMRAN , Pillai, G & Jyothi, KC 2021, Generation of synthetic datasets for transformer’s dissolved gas analysis using Monte-Carlo Simulation. in 2021 56th International Universities Power Engineering Conference: Powering Net Zero Emissions, UPEC 2021 - Proceedings. 2021 56th International Universities Power Engineering Conference (UPEC), IEEE, 56th International Universities Power Engineering Conference, Middlesbrough, United Kingdom, 31/08/21. https://doi.org/10.1109/upec50034.2021.9548242

Generation of synthetic datasets for transformer’s dissolved gas analysis using Monte-Carlo Simulation. / Kollonoor Babu, Eaby; Bashir, IMRAN ; Pillai, Gobind et al.
2021 56th International Universities Power Engineering Conference: Powering Net Zero Emissions, UPEC 2021 - Proceedings. IEEE, 2021. (2021 56th International Universities Power Engineering Conference (UPEC)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Generation of synthetic datasets for transformer’s dissolved gas analysis using Monte-Carlo Simulation

AU - Kollonoor Babu, Eaby

AU - Bashir, IMRAN

AU - Pillai, Gobind

AU - Jyothi, Kiran Chandrakumar

PY - 2021/9/30

Y1 - 2021/9/30

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.

U2 - 10.1109/upec50034.2021.9548242

DO - 10.1109/upec50034.2021.9548242

M3 - Conference contribution

T3 - 2021 56th International Universities Power Engineering Conference (UPEC)

BT - 2021 56th International Universities Power Engineering Conference

PB - IEEE

T2 - 56th International Universities Power Engineering Conference

Y2 - 31 August 2021 through 3 September 2021

ER -

Kollonoor Babu E, Bashir IMRAN , Pillai G, Jyothi KC. Generation of synthetic datasets for transformer’s dissolved gas analysis using Monte-Carlo Simulation. In 2021 56th International Universities Power Engineering Conference: Powering Net Zero Emissions, UPEC 2021 - Proceedings. IEEE. 2021. (2021 56th International Universities Power Engineering Conference (UPEC)). doi: 10.1109/upec50034.2021.9548242

Generation of synthetic datasets for transformer’s dissolved gas analysis using Monte-Carlo Simulation

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