Transformer Mechanical Integrity Evaluation Via Unsupervised Neural Network (UNN) In Smart Grid Network

• Main Authors: Zul Hasrizal, Bohari, Mohd Hafiz, Jali, Mohamad Faizal, Baharom, Mohamad Na'im, Mohd Nasir, Nik Mohd Fariz, Mohd Nawi, Yasmin Hanum, Md Thayoob
• Format: Article
• Language: English
• Published: Institute Of Electrical And Electronics Engineers Inc. (IEEE) 2016
• Subjects: T Technology (General); TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utem.edu.my/id/eprint/17703/1/Transformer%20Mechanical%20Integrity%20Evaluation%20Via%20Unsupervised%20Neural%20Network%20%28UNN%29%20In%20Smart%20Grid%20Network.pdf; http://eprints.utem.edu.my/id/eprint/17703/; http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7482178
• Institution: Universiti Teknikal Malaysia Melaka

This paper describes the classification of mechanical integrity of transformers using unsupervised neural networks (UNN). Transformers are the integral part of electrical system or smart grid networks since the last century. Self-Organizing Maps (SOM) is one type of UNN the widely used to do asses...