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 | |
| Publication status | Published - Nov 14 2018 |
| Event | 7th International Conference on Condition Monitoring and Diagnosis, CMD 2018 - Perth, Australia Duration: Sep 23 2018 → Sep 26 2018 |
Other
| Other | 7th International Conference on Condition Monitoring and Diagnosis, CMD 2018 |
|---|---|
| Country | Australia |
| City | Perth |
| Period | 9/23/18 → 9/26/18 |
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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
Cite this
Real-time Transformer Diagnosis using Voltage-Current Signal over Cloud Environment. / Smagulova, Altynay; Borasheva, Aigerim; Moldiyar, Nurtas; Bazarbek, Nurbolat; Bagheri, Mehdi; Phung, B. T.
2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings. ed. / Ahmed Abu-Siada. Institute of Electrical and Electronics Engineers Inc., 2018. 8535876.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Real-time Transformer Diagnosis using Voltage-Current Signal over Cloud Environment
AU - Smagulova, Altynay
AU - Borasheva, Aigerim
AU - Moldiyar, Nurtas
AU - Bazarbek, Nurbolat
AU - Bagheri, Mehdi
AU - Phung, B. T.
PY - 2018/11/14
Y1 - 2018/11/14
N2 - 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.
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.
KW - Cloud computing
KW - Internet of Things (IoT) application
KW - Real-time transformer deformation evaluation
KW - Transformer diagnosis
UR - http://www.scopus.com/inward/record.url?scp=85059085624&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059085624&partnerID=8YFLogxK
U2 - 10.1109/CMD.2018.8535876
DO - 10.1109/CMD.2018.8535876
M3 - Conference contribution
AN - SCOPUS:85059085624
BT - 2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings
A2 - Abu-Siada, Ahmed
PB - Institute of Electrical and Electronics Engineers Inc.
ER -