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Prof. Sayed Abo-Elsood Sayed Ward :: Publications: |
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| Title: | Estimation of Carbon Nanotube Sensors Performance using Linear, Fuzzy and Neural Regression Models |
| Authors: | S. Hassan1, A. Emam2, S. A. Ward1, Z. Abdel Hamid3 and M. Badawi1 |
| Year: | 2018 |
| Keywords: | Partial Discharge, Carbon Nanotubes Sensors, Fuzzy Regression, Linear Regression. |
| Journal: | INTERNATIONAL JOURNAL OF INNOVATIVE TRENDS IN ENGINEERING (IJITE) |
| Volume: | ISSUE: 70, VOLUME 46, NUMBER 01, OCTOBER 2018 |
| Issue: | ISSUE: 70, VOLUME 46, NUMBER 01, OCTOBER 2018 |
| Pages: | ISSUE: 70, VOLUME 46, NUMBER 01, OCTOBER 2018 |
| Publisher: | INTERNATIONAL JOURNAL OF INNOVATIVE TRENDS IN ENGINEERING (IJITE) |
| Local/International: | International |
| Paper Link: | Not Available |
| Full paper | Sayed Abo-Elsood Sayed Ward_paper samhe shawky - 1.pdf |
| Supplementary materials | Sayed Abo-Elsood Sayed Ward_paper samhe shawky - 1.pdf |
| Abstract: |
Electrical transformers are considered one of the very important elements on the operation of power systems. The operation of electrical transformers is dependent on the performance of transformer oils. Hence, it is very necessary for continuous and online checking the transformer oil insulation level. Transformer oil wet process generates oil discharge space charge in the long run and bubbles are formed. When the electric field reaches a certain limit, partial discharge (PD) appears and lead to deterioration of oil insulation level. In this paper, Multi-wall carbon nanotube (MWNT) sensor is used for detecting PD of oils). The performance of (MWNTs) films sensor for continuous and on line monitoring the oil insulation level is studied. A linear, fuzzy and neural regression models are used to explain and predict the performance of the sensor. |
