Dielectric Resonator Antenna-Based Sensing Technology for Enhanced Insulation Oil Diagnostics
dc.authorid | Duman, Mehmet/0000-0002-0831-0172; | |
dc.contributor.author | Duman, Mehmet | |
dc.contributor.author | Bicen, Yunus | |
dc.date.accessioned | 2025-10-11T20:48:50Z | |
dc.date.available | 2025-10-11T20:48:50Z | |
dc.date.issued | 2025 | |
dc.department | Düzce Üniversitesi | en_US |
dc.description.abstract | The insulating oil in transformers plays a critical role both as a coolant supporting the paper insulation and as an element protecting the dielectric properties of the system. Serious failures may result from changes in the oil's dielectric characteristics brought on by the presence of water and other contaminants. This study assesses the insulation condition of transformer oils by designing and simulating three different dielectric resonator antennas (DRA) in the CST Design Environment. An attempt is made to find the best design by analyzing the effect of variations in dielectric constant on various resonator antenna designs. The resonant frequency range of 1.5-3GHz$1.5 {-}3\;GHz$ and the RT5880 dielectric substrate are chosen. Simulations are carried out to illustrate situations where the epsilon r${\varepsilon _r}$ value of the oil varies between 1$\hskip.001pt 1$ and 5$\hskip.001pt 5$. In general, it is found that as the dielectric constant of the oil (epsilon r${\varepsilon _r}$) increases, the resonant frequency (fr${f_r}$) and the S11${S_{11}}$ parameter decrease. Single DRA-A single SMA port is advised for low-cost and straightforward applications, but Dual DRA can be chosen for investigations needing high sensitivity and double-check. The analysis allows the best approach to be selected based on the requirements of the application by highlighting the advantages and disadvantages of different designs. | en_US |
dc.description.sponsorship | Dzce University [2025.06.03.1572] | en_US |
dc.description.sponsorship | M.D. and Y.B. contributed equally to this work. The authors would like to thank Duezce University for financial support, Grant No. 2025.06.03.1572. The authors acknowledge the use of AI-based tools for enhancing the linguistic clarity of the manuscript and assisting in the refinement of figures. | en_US |
dc.identifier.doi | 10.1002/adts.202500114 | |
dc.identifier.issn | 2513-0390 | |
dc.identifier.scopus | 2-s2.0-105008660924 | en_US |
dc.identifier.scopusquality | Q1 | en_US |
dc.identifier.uri | https://doi.org/10.1002/adts.202500114 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12684/22135 | |
dc.identifier.wos | WOS:001512035500001 | en_US |
dc.identifier.wosquality | Q2 | en_US |
dc.indekslendigikaynak | Web of Science | en_US |
dc.indekslendigikaynak | Scopus | en_US |
dc.language.iso | en | en_US |
dc.publisher | Wiley-V C H Verlag Gmbh | en_US |
dc.relation.ispartof | Advanced Theoryand Simulations | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.snmz | KA_WOS_20250911 | |
dc.subject | dielectric | en_US |
dc.subject | permittivity | en_US |
dc.subject | quality testing | en_US |
dc.subject | resonator antenna | en_US |
dc.subject | transformer oil | en_US |
dc.title | Dielectric Resonator Antenna-Based Sensing Technology for Enhanced Insulation Oil Diagnostics | en_US |
dc.type | Article | en_US |