Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Ayman El-Hag"'
Publikováno v:
Energies, Vol 16, Iss 22, p 7656 (2023)
Furan tests provide a non-intrusive and cost-effective method of estimating the degradation of paper insulation, which is critical for ensuring the reliability of power grids. However, conducting routine furan tests can be expensive and challenging,
Externí odkaz:
https://doaj.org/article/376f5a988e824b5eac5244db8d54a253
Publikováno v:
Energies, Vol 15, Iss 14, p 5005 (2022)
Condition monitoring of high voltage apparatus is of much importance for the maintenance of electric power systems. Whether it is detecting faults or partial discharges that take place in high voltage equipment, or detecting contamination and degrada
Externí odkaz:
https://doaj.org/article/bb7b1225ca5d477082e52897f4cc91fc
Self-Healing Silicones for Outdoor High Voltage Insulation: Mechanism, Applications and Measurements
Autor:
Fadi Z. Kamand, Basharat Mehmood, Refat Ghunem, Mohammad K. Hassan, Ayman El-Hag, Leena Al-Sulaiti, Ahmed Abdala
Publikováno v:
Energies, Vol 15, Iss 5, p 1677 (2022)
This paper discusses the state of the art in the application of self-healing silicone-based materials for outdoor high-voltage insulation. Both the dynamic behavior of the dimethyl side groups of silicone rubber and the diffusion of a bulk siloxane t
Externí odkaz:
https://doaj.org/article/ab9d2af4096f4fb5bb449df059fcdd26
Publikováno v:
High Voltage (2019)
Condition monitoring of outdoor insulation systems is crucial to the integrity of distribution and transmission overhead lines and substations. The objective of this study is to use a commercial acoustic sensor along with artificial neural network (A
Externí odkaz:
https://doaj.org/article/2ecc9a22b2b14adeade60a9bc9f4fd2e
Autor:
Suganya Govindarajan, Venkateshwar Ragavan, Ayman El-Hag, Kannan Krithivasan, Jayalalitha Subbaiah
Publikováno v:
Energies, Vol 14, Iss 6, p 1564 (2021)
Different types of classifiers for acoustic partial discharge (PD) pattern classification have been widely discussed in the literature. The classifier performance mainly depends on the measurement conditions (location and type of the PD, acoustic sen
Externí odkaz:
https://doaj.org/article/d1a073dee7d24c75a47e35ef475d99c8
Autor:
Ahmad Nayyar Hassan, Ayman El-Hag
Publikováno v:
Energies, Vol 13, Iss 7, p 1735 (2020)
This paper uses a two-layered soft voting-based ensemble model to predict the interfacial tension (IFT), as one of the transformer oil test parameters. The input feature vector is composed of acidity, water content, dissipation factor, color and brea
Externí odkaz:
https://doaj.org/article/27cc559141a647c98a2a00492f0310b6
Autor:
Amir Abbas Soltani, Ayman El-Hag
Publikováno v:
Energies, Vol 12, Iss 18, p 3485 (2019)
One of the most promising techniques for condition monitoring of high voltage equipment insulation is partial discharge (PD) measurement using radio frequency (RF) antenna. Nevertheless, the accuracy of monitoring, classification, localization, or li
Externí odkaz:
https://doaj.org/article/29d96b093d7546eca8c39e9a017b8064
Autor:
Alhaytham Alqudsi, Ayman El-Hag
Publikováno v:
Energies, Vol 12, Iss 14, p 2694 (2019)
The presented paper aims to establish a strong basis for utilizing machine learning (ML) towards the prediction of the overall insulation health condition of medium voltage distribution transformers based on their oil test results. To validate the pr
Externí odkaz:
https://doaj.org/article/6e4e86ebf8284f338247981e13104cb0
Autor:
Abdulla Lutfi, Ayman El-Hag
Publikováno v:
2022 5th International Conference on Communications, Signal Processing, and their Applications (ICCSPA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27bbc7d91a9e7a87af1bca5cfa7e9056
https://doi.org/10.1109/iccspa55860.2022.10019102
https://doi.org/10.1109/iccspa55860.2022.10019102
Publikováno v:
2022 IEEE Conference on Electrical Insulation and Dielectric Phenomena (CEIDP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::533d0545eeeb05a4e21840123a6a4ea4
https://doi.org/10.1109/ceidp55452.2022.9985259
https://doi.org/10.1109/ceidp55452.2022.9985259