Real-time Transformer Diagnosis using Voltage-Current Signal over Cloud Environment

Altynay Smagulova; Aigerim Borasheva; Nurtas Moldiyar; Nurbolat Bazarbek; Mehdi Bagheri; B. T. Phung

doi:10.1109/CMD.2018.8535876

Real-time Transformer Diagnosis using Voltage-Current Signal over Cloud Environment

Altynay Smagulova
, Aigerim Borasheva
, Nurtas Moldiyar
, Nurbolat Bazarbek
, Mehdi Bagheri
, B. T. Phung

Department of Electrical and Computer Engineering

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

Abstract

Most transformer diagnosis methods can only be performed off-line when the transformer is taken out of service. This study is specifically focused on the V-I locus method for real-time transformer active part evaluation over the cloud environment and assessment of captured data through cloud computing. Experiments are carried out on a test setup to study turn-to-turn short circuit fault created on small transformers. Transformer mechanical fault recognition is discussed and the voltage/current technique is evaluated. Data obtained from practical measurements is analysed over cloud environment and assessment of the transformer condition is performed via application on mobile device. Also, protection relay connected to the transformer can be activated via cloud-based data assessment.

Original language	English
Title of host publication	2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings
Editors	Ahmed Abu-Siada
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538641262
DOIs	https://doi.org/10.1109/CMD.2018.8535876
Publication status	Published - Nov 14 2018
Event	7th International Conference on Condition Monitoring and Diagnosis, CMD 2018 - Perth, Australia Duration: Sept 23 2018 → Sept 26 2018

Publication series

Name	2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings

Other

Other	7th International Conference on Condition Monitoring and Diagnosis, CMD 2018
Country/Territory	Australia
City	Perth
Period	9/23/18 → 9/26/18

Funding

This research work was supported by Faculty Development Competitive Research Grant of Nazarbayev University (Grant Award No. 090118FD5318).

Keywords

Cloud computing
Internet of Things (IoT) application
Real-time transformer deformation evaluation
Transformer diagnosis

ASJC Scopus subject areas

Computer Networks and Communications
Signal Processing
Energy Engineering and Power Technology
Safety, Risk, Reliability and Quality

Access to Document

10.1109/CMD.2018.8535876

Cite this

Smagulova, A., Borasheva, A., Moldiyar, N., Bazarbek, N., Bagheri, M., & Phung, B. T. (2018). Real-time Transformer Diagnosis using Voltage-Current Signal over Cloud Environment. In A. Abu-Siada (Ed.), 2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings Article 8535876 (2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CMD.2018.8535876

Real-time Transformer Diagnosis using Voltage-Current Signal over Cloud Environment. / Smagulova, Altynay; Borasheva, Aigerim; Moldiyar, Nurtas et al.
2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings. ed. / Ahmed Abu-Siada. Institute of Electrical and Electronics Engineers Inc., 2018. 8535876 (2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings).

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

Smagulova, A, Borasheva, A, Moldiyar, N, Bazarbek, N, Bagheri, M & Phung, BT 2018, Real-time Transformer Diagnosis using Voltage-Current Signal over Cloud Environment. in A Abu-Siada (ed.), 2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings., 8535876, 2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 7th International Conference on Condition Monitoring and Diagnosis, CMD 2018, Perth, Australia, 9/23/18. https://doi.org/10.1109/CMD.2018.8535876

Smagulova A, Borasheva A, Moldiyar N, Bazarbek N, Bagheri M, Phung BT. Real-time Transformer Diagnosis using Voltage-Current Signal over Cloud Environment. In Abu-Siada A, editor, 2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. 8535876. (2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings). doi: 10.1109/CMD.2018.8535876

Smagulova, Altynay ; Borasheva, Aigerim ; Moldiyar, Nurtas et al. / Real-time Transformer Diagnosis using Voltage-Current Signal over Cloud Environment. 2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings. editor / Ahmed Abu-Siada. Institute of Electrical and Electronics Engineers Inc., 2018. (2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings).

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title = "Real-time Transformer Diagnosis using Voltage-Current Signal over Cloud Environment",

abstract = "Most transformer diagnosis methods can only be performed off-line when the transformer is taken out of service. This study is specifically focused on the V-I locus method for real-time transformer active part evaluation over the cloud environment and assessment of captured data through cloud computing. Experiments are carried out on a test setup to study turn-to-turn short circuit fault created on small transformers. Transformer mechanical fault recognition is discussed and the voltage/current technique is evaluated. Data obtained from practical measurements is analysed over cloud environment and assessment of the transformer condition is performed via application on mobile device. Also, protection relay connected to the transformer can be activated via cloud-based data assessment.",

keywords = "Cloud computing, Internet of Things (IoT) application, Real-time transformer deformation evaluation, Transformer diagnosis",

author = "Altynay Smagulova and Aigerim Borasheva and Nurtas Moldiyar and Nurbolat Bazarbek and Mehdi Bagheri and Phung, \{B. T.\}",

note = "Funding Information: This research work was supported by Faculty Development Competitive Research Grant of Nazarbayev University (Grant Award No. 090118FD5318). Publisher Copyright: {\textcopyright} 2018 IEEE.; 7th International Conference on Condition Monitoring and Diagnosis, CMD 2018 ; Conference date: 23-09-2018 Through 26-09-2018",

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AB - Most transformer diagnosis methods can only be performed off-line when the transformer is taken out of service. This study is specifically focused on the V-I locus method for real-time transformer active part evaluation over the cloud environment and assessment of captured data through cloud computing. Experiments are carried out on a test setup to study turn-to-turn short circuit fault created on small transformers. Transformer mechanical fault recognition is discussed and the voltage/current technique is evaluated. Data obtained from practical measurements is analysed over cloud environment and assessment of the transformer condition is performed via application on mobile device. Also, protection relay connected to the transformer can be activated via cloud-based data assessment.

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Real-time Transformer Diagnosis using Voltage-Current Signal over Cloud Environment

Abstract

Publication series

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Funding

Keywords

ASJC Scopus subject areas

Access to Document

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