Prediction of breakdown strength of cellulosic insulating materials using artificial neural networks

被引:6
|
作者
Singh, Sakshi [1 ]
Mohsin, M. M. [1 ]
Masood, Aejaz [1 ]
机构
[1] Aligarh Muslim Univ, Dept Elect Engn, ZH Coll Engn & Technol, Aligarh 202002, Uttar Pradesh, India
关键词
Cellulosic materials; relative permittivity; loss tangent; breakdown strength; ANN;
D O I
10.1142/S2010135X18500030
中图分类号
O59 [应用物理学];
学科分类号
摘要
In this research work, a few sets of experiments have been performed in high voltage laboratory on various cellulosic insulating materials like diamond-dotted paper, paper phenolic sheets, cotton phenolic sheets, leatheroid, and presspaper, to measure different electrical parameters like breakdown strength, relative permittivity, loss tangent, etc. Considering the dependency of breakdown strength on other physical parameters, different Artificial Neural Network (ANN) models are proposed for the prediction of breakdown strength. The ANN model results are compared with those obtained experimentally and also with the values already predicted from an empirical relation suggested by Swanson and Dall. The reported results indicated that the breakdown strength predicted from the ANN model is in good agreement with the experimental values.
引用
收藏
页数:4
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