Transformer incipient fault prediction using combined artificial neural network and various particle swarm optimisation techniques

• Main Authors: Illias, Hazlee Azil, Chai, X.R., Abu Bakar, A.H., Mokhlis, Hazlie
• Format: Article
• Language: English
• Published: Public Library of Science 2015
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General); TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.um.edu.my/15704/1/Transformer_Incipient_Fault_Prediction_Using_Combined_Artificial_Neural_Network.pdf; http://eprints.um.edu.my/15704/; http://www.ncbi.nlm.nih.gov/pubmed/26103634
• Institution: Universiti Malaya

It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power trans...