Abstract
Transformers are utilized in generation, transmission, and distribution power system network, and face an enormous number of hazards during their course of operation. Frequency response analysis (FRA) is an inexpensive, accurate, and non-destructive technique to explore the transformer mechanical integrity very fast. However, FRA results interpretation is not being automated yet. This study introduces a new setup for FRA measurement that can assist to leave the conventional FRA data interpretation techniques and obtain smart interpretation. Hence, FRA setups and interpretation techniques are studied and formulated in this paper. A new measurement technique is introduced and discussed in detail. Practical studies are performed over distribution and power transformers and FRA data are recorded for inter-disk fault. The analysis of fault severity, which is obatined in this paper, is an advantage of the proposed measurement technique. In this regard, the techniques from machine learning and numerical analysis are employed to train a predictive engine for smart interpretation of FRA data. It is revealed that the proposed intelligent technique is capable of interpreting, detecting, and classifying the transformer winding inter-disk fault and its severity. The new introduced FRA measurement setup is also able to support the online FRA data assessment.
| Original language | English |
|---|---|
| Article number | 8682123 |
| Pages (from-to) | 1508-1519 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Power Delivery |
| Volume | 34 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Aug 1 2019 |
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Keywords
- FRA interpretation
- Frequency response analysis (FRA)
- online monitoring
- short-circuit detection
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering
Cite this
A New Transformer FRA Measurement Technique to Reach Smart Interpretation for Inter-Disk Faults. / Nurmanova, Venera; Bagheri, Mehdi; Zollanvari, Amin; Aliakhmet, Kamilla; Akhmetov, Yerbol; Gharehpetian, Gevork B.
In: IEEE Transactions on Power Delivery, Vol. 34, No. 4, 8682123, 01.08.2019, p. 1508-1519.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A New Transformer FRA Measurement Technique to Reach Smart Interpretation for Inter-Disk Faults
AU - Nurmanova, Venera
AU - Bagheri, Mehdi
AU - Zollanvari, Amin
AU - Aliakhmet, Kamilla
AU - Akhmetov, Yerbol
AU - Gharehpetian, Gevork B.
PY - 2019/8/1
Y1 - 2019/8/1
N2 - Transformers are utilized in generation, transmission, and distribution power system network, and face an enormous number of hazards during their course of operation. Frequency response analysis (FRA) is an inexpensive, accurate, and non-destructive technique to explore the transformer mechanical integrity very fast. However, FRA results interpretation is not being automated yet. This study introduces a new setup for FRA measurement that can assist to leave the conventional FRA data interpretation techniques and obtain smart interpretation. Hence, FRA setups and interpretation techniques are studied and formulated in this paper. A new measurement technique is introduced and discussed in detail. Practical studies are performed over distribution and power transformers and FRA data are recorded for inter-disk fault. The analysis of fault severity, which is obatined in this paper, is an advantage of the proposed measurement technique. In this regard, the techniques from machine learning and numerical analysis are employed to train a predictive engine for smart interpretation of FRA data. It is revealed that the proposed intelligent technique is capable of interpreting, detecting, and classifying the transformer winding inter-disk fault and its severity. The new introduced FRA measurement setup is also able to support the online FRA data assessment.
AB - Transformers are utilized in generation, transmission, and distribution power system network, and face an enormous number of hazards during their course of operation. Frequency response analysis (FRA) is an inexpensive, accurate, and non-destructive technique to explore the transformer mechanical integrity very fast. However, FRA results interpretation is not being automated yet. This study introduces a new setup for FRA measurement that can assist to leave the conventional FRA data interpretation techniques and obtain smart interpretation. Hence, FRA setups and interpretation techniques are studied and formulated in this paper. A new measurement technique is introduced and discussed in detail. Practical studies are performed over distribution and power transformers and FRA data are recorded for inter-disk fault. The analysis of fault severity, which is obatined in this paper, is an advantage of the proposed measurement technique. In this regard, the techniques from machine learning and numerical analysis are employed to train a predictive engine for smart interpretation of FRA data. It is revealed that the proposed intelligent technique is capable of interpreting, detecting, and classifying the transformer winding inter-disk fault and its severity. The new introduced FRA measurement setup is also able to support the online FRA data assessment.
KW - FRA interpretation
KW - Frequency response analysis (FRA)
KW - online monitoring
KW - short-circuit detection
UR - http://www.scopus.com/inward/record.url?scp=85069971546&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85069971546&partnerID=8YFLogxK
U2 - 10.1109/TPWRD.2019.2909144
DO - 10.1109/TPWRD.2019.2909144
M3 - Article
AN - SCOPUS:85069971546
VL - 34
SP - 1508
EP - 1519
JO - IEEE Transactions on Power Delivery
JF - IEEE Transactions on Power Delivery
SN - 0885-8977
IS - 4
M1 - 8682123
ER -