An alternative approaches to predict flashover voltage on polluted outdoor insulators using artificial intelligence techniques
| Autor: | Nordiana Azlin Othman, Mohd Taufiq Ishak, Nor Akmal Mohd Jamail, M. S. Kamarudin, Rahisham Abd Rahman, Ali. A. Salem, Haziah Abdul Hamid |
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| Rok vydání: | 2020 |
| Předmět: |
Adaptive neuro fuzzy inference system
Control and Optimization Coefficient of determination Form factor (electronics) Artificial neural network Computer Networks and Communications business.industry 020209 energy 020208 electrical & electronic engineering 02 engineering and technology Flashover voltage Hardware and Architecture Control and Systems Engineering Pollution flashover 0202 electrical engineering electronic engineering information engineering Computer Science (miscellaneous) Arc flash Artificial intelligence Electrical and Electronic Engineering business Instrumentation Information Systems Test data Mathematics |
| Zdroj: | Bulletin of Electrical Engineering and Informatics. 9 |
| ISSN: | 2302-9285 2089-3191 |
| DOI: | 10.11591/eei.v9i2.1864 |
| Popis: | This paper presents an alternative approach for predicting critical voltage of pollution flashover by using Artificial Intelligence (AI) technique. Data from experimental works combined with the theoretical results from well-known theoretical modelling are used to derive algorithm for Artificial Neural Network (ANN) and Adaptive Neuro-fuzzy Inference System (ANFIS) for determining critical voltage of flashover. Series of laboratory testing and measurement are carried for 1:1, 1:5 and 1:10 ratios of top to bottom surface salt deposit density on cup and pin insulators. Insulators variables such as height H, diameter D, form factor F, creepage distance L, equivalent salt deposit density (ESDD) and flashover voltage correction are identified and used to train the AI network. Comparative studies have evidently shown that the proposed (AI) technique gives the satisfactory results compared to the analytical model and test data with the Coefficient of determination R-Square value of more than 97%. |
| Databáze: | OpenAIRE |
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