@article { author = {Nasirpour, F. and Samimi, M.H. and Mohseni, H.}, title = {Evaluation of online techniques utilized for extracting the transformer transfer function}, journal = {Scientia Iranica}, volume = {26}, number = {Special Issue on machine learning, data analytics, and advanced optimization techniques...}, pages = {3582-3591}, year = {2019}, publisher = {Sharif University of Technology}, issn = {1026-3098}, eissn = {2345-3605}, doi = {10.24200/sci.2019.53890.3473}, abstract = {Power transformers have vital importance in the power delivery and, therefore, different diagnostic techniques are proposed for them. The frequency response analysis (FRA) is an effective method which detects the mechanical changes in transformer windings by extracting the transfer function. There are various approaches for obtaining the transfer function online, which is known as the online FRA technique. This paper compares these different mathematical approaches for obtaining the transfer function of a transformer. The comparison is carried out by defining an appropriate model for the transformer and applying these mathematical methods to it. The effect of other power network equipment on the transformer transfer function is also studied in this paper. The results of this contribution determine the proper methods for the online FRA technique, which can be used in the transformer monitoring applications.}, keywords = {Fault diagnosis,Fourier transform,Frequency response analysis,Online diagnosis,Power transformer monitoring,Transfer function,wavelet transform}, url = {https://scientiairanica.sharif.edu/article_21549.html}, eprint = {https://scientiairanica.sharif.edu/article_21549_db1d9dc7d514c796964ad793b20b32cb.pdf} }