TY - GEN
T1 - General diagnosis of transformer winding axial displacement faults based on FEM simulation and on-site experiments
AU - Lu, Fei
AU - Jin, Lei
AU - Liu, Siwei
AU - Liu, Yi
AU - Li, Hua
AU - Lin, Fuchang
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/22
Y1 - 2016/8/22
N2 - Structural faults detection of power transformers are quite significant, and general diagnosis based on different test and simulation methods is commonly used to detect mechanical and/or electrical faults in power transformers. In this paper, the diagnosis of the transformer winding axial displacement faults based on FEM simulation and on-site experiment is carried out and presented. Based on the FEM simulation, it is necessary to analyze the effect of the axial displacement faults on the change of the electrical parameters. The whole winding's or the single disk's axial displacement are under consideration, and different fault levels are taken into consideration in the simulation analysis to investigate the influence of axial displacement on the electrical parameters. Using the calculated parameters, a distributed model of the power transformer based on ATP/EMTP is present to study the performance of frequency response curve on the axial displacement with different fault levels. The operating states of several 110 kV power transformers are tracked, and a typical transformer after the short-circuit impact is tested. The FRA test results are obtained before and after the short-circuit impact. The simulation results and the on-site test results are compared, and they show a better consistency. It can be concluded that under the typical impact of the axial displacement, the frequency response curve starts an obvious variation from 150 kHz, and the resonances and anti-resonances are shifted to the high frequency direction. The overall fault detection results show that the proposed method can discriminate the winding axial displacement fault with the high hit ratio.
AB - Structural faults detection of power transformers are quite significant, and general diagnosis based on different test and simulation methods is commonly used to detect mechanical and/or electrical faults in power transformers. In this paper, the diagnosis of the transformer winding axial displacement faults based on FEM simulation and on-site experiment is carried out and presented. Based on the FEM simulation, it is necessary to analyze the effect of the axial displacement faults on the change of the electrical parameters. The whole winding's or the single disk's axial displacement are under consideration, and different fault levels are taken into consideration in the simulation analysis to investigate the influence of axial displacement on the electrical parameters. Using the calculated parameters, a distributed model of the power transformer based on ATP/EMTP is present to study the performance of frequency response curve on the axial displacement with different fault levels. The operating states of several 110 kV power transformers are tracked, and a typical transformer after the short-circuit impact is tested. The FRA test results are obtained before and after the short-circuit impact. The simulation results and the on-site test results are compared, and they show a better consistency. It can be concluded that under the typical impact of the axial displacement, the frequency response curve starts an obvious variation from 150 kHz, and the resonances and anti-resonances are shifted to the high frequency direction. The overall fault detection results show that the proposed method can discriminate the winding axial displacement fault with the high hit ratio.
KW - axial displacement
KW - finite element method
KW - frequency response analysis
KW - Power transformer
KW - winding deformation
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U2 - 10.1109/EIC.2016.7548700
DO - 10.1109/EIC.2016.7548700
M3 - Conference contribution
AN - SCOPUS:84988358577
T3 - 34th Electrical Insulation Conference, EIC 2016
SP - 223
EP - 228
BT - 34th Electrical Insulation Conference, EIC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 34th Electrical Insulation Conference, EIC 2016
Y2 - 19 June 2016 through 22 June 2016
ER -