Araştırma Makalesi

ARTIFICIAL NEURAL NETWORK MODELS OF CROSS-LINKED POLYETHYLENE

Cilt: 25 Sayı: 2 30 Aralık 2024
PDF İndir
TR EN

ARTIFICIAL NEURAL NETWORK MODELS OF CROSS-LINKED POLYETHYLENE

Öz

Cross-linked polyethylene (XLPE) is the most widely used insulator material in high-power cables. The complex electrical permittivity of the XLPE layer mostly determines the leakage admittance of the cable and the propagation speed of the signal. The complex electrical permittivity of XLPE depends on not only operating frequency but also temperature. In this study, Artificial neural networks (ANNs) are used to model the complex electrical permittivity parts of the XLPE. The structure of the ANNs is optimized. It has been found that the optimized ANN can predict the behavior of the XLPE with an R2 value of 0.99.

Anahtar Kelimeler

Power cables, Insulation models, Cross-linked polyethylene, ANN model, Parameter prediction

Destekleyen Kurum

Ünika Üniversal Kablo Sanayi ve Tic. A.Ş.

Proje Numarası

UPN-2003

Etik Beyan

This study has been supported by the research and development center of Ünika Üniversal Kablo Sanayi ve Tic. A.Ş.; Project number: UPN-2003.

Teşekkür

This study has been supported by the research and development center of Ünika Üniversal Kablo Sanayi ve Tic. A.Ş.; Project number: UPN-2003.

Kaynakça

  1. Arikan, O., Uydur, C. C., & Kumru, C. F. (2022). Prediction of dielectric parameters of an aged MV cable: A comparison of curve fitting, decision tree and artificial neural network methods. Electric Power Systems Research, 208, 107892. https://doi.org/10.1016/j.epsr.2022.107892
  2. Ashok, N., Soman, K. P., Samanta, M., Sruthi, M. S., Poornachandran, P., Devi V. G, S., & Sukumar, N. (2024). Polymer and Nanocomposite Informatics: Recent Applications of Artificial Intelligence and Data Repositories. Advanced Machine Learning with Evolutionary and Metaheuristic Techniques, 297-322. https://doi.org/10.1007/978-981-99-9718-3_12
  3. Boukezzi, L., & Boubakeur, A. (2013). Prediction of mechanical properties of XLPE cable insulation under thermal aging: neural network approach. IEEE Transactions on Dielectrics and Electrical Insulation, 20(6), 2125-2134. https://doi.org/10.1109/TDEI.2013.6678861
  4. Cole, K. S., & Cole, R. H. (1941). Dispersion and absorption in dielectrics I. Alternating current characteristics. The Journal of chemical physics, 9(4), 341-351. https://doi.org/10.1063/1.1750906
  5. Çanta, H., Mutlu, R., & Korkmaz Tan, R. (2024). Yeni Üretilen XLPE İzolasyonlu Tek Damarlı Bir Güç Kablosunun Kaçak Empedansının Hesabı. EMO Bilimsel Dergi, 14(1), 19-26.

Kaynak Göster

APA
Korkmaz Tan, R., Çanta, H., & Mutlu, R. (2024). ARTIFICIAL NEURAL NETWORK MODELS OF CROSS-LINKED POLYETHYLENE. Trakya Üniversitesi Mühendislik Bilimleri Dergisi, 25(2), 129-141. https://doi.org/10.59314/tujes.1598718
AMA
1.Korkmaz Tan R, Çanta H, Mutlu R. ARTIFICIAL NEURAL NETWORK MODELS OF CROSS-LINKED POLYETHYLENE. TUJES. 2024;25(2):129-141. doi:10.59314/tujes.1598718
Chicago
Korkmaz Tan, Rabia, Hakan Çanta, ve Reşat Mutlu. 2024. “ARTIFICIAL NEURAL NETWORK MODELS OF CROSS-LINKED POLYETHYLENE”. Trakya Üniversitesi Mühendislik Bilimleri Dergisi 25 (2): 129-41. https://doi.org/10.59314/tujes.1598718.
EndNote
Korkmaz Tan R, Çanta H, Mutlu R (01 Aralık 2024) ARTIFICIAL NEURAL NETWORK MODELS OF CROSS-LINKED POLYETHYLENE. Trakya Üniversitesi Mühendislik Bilimleri Dergisi 25 2 129–141.
IEEE
[1]R. Korkmaz Tan, H. Çanta, ve R. Mutlu, “ARTIFICIAL NEURAL NETWORK MODELS OF CROSS-LINKED POLYETHYLENE”, TUJES, c. 25, sy 2, ss. 129–141, Ara. 2024, doi: 10.59314/tujes.1598718.
ISNAD
Korkmaz Tan, Rabia - Çanta, Hakan - Mutlu, Reşat. “ARTIFICIAL NEURAL NETWORK MODELS OF CROSS-LINKED POLYETHYLENE”. Trakya Üniversitesi Mühendislik Bilimleri Dergisi 25/2 (01 Aralık 2024): 129-141. https://doi.org/10.59314/tujes.1598718.
JAMA
1.Korkmaz Tan R, Çanta H, Mutlu R. ARTIFICIAL NEURAL NETWORK MODELS OF CROSS-LINKED POLYETHYLENE. TUJES. 2024;25:129–141.
MLA
Korkmaz Tan, Rabia, vd. “ARTIFICIAL NEURAL NETWORK MODELS OF CROSS-LINKED POLYETHYLENE”. Trakya Üniversitesi Mühendislik Bilimleri Dergisi, c. 25, sy 2, Aralık 2024, ss. 129-41, doi:10.59314/tujes.1598718.
Vancouver
1.Rabia Korkmaz Tan, Hakan Çanta, Reşat Mutlu. ARTIFICIAL NEURAL NETWORK MODELS OF CROSS-LINKED POLYETHYLENE. TUJES. 01 Aralık 2024;25(2):129-41. doi:10.59314/tujes.1598718