Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques.
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...
Main Authors: | Hazlee Azil Illias, Xin Rui Chai, Ab Halim Abu Bakar, Hazlie Mokhlis |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2015-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0129363 |
Similar Items
-
Optimisation of PID controller for load frequency control in two-area power system using evolutionary particle swarm optimisation
by: Hazlee Illias, et al.
Published: (2016-06-01) -
Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation.
by: Hazlee Azil Illias, et al.
Published: (2018-01-01) -
Fault Identification in an Unbalanced Distribution System Using Support Vector Machine
by: Sophi Shilpa Gururajapathy, et al.
Published: (2016-12-01) -
Classification of abnormal location in medium voltage switchgears using hybrid gravitational search algorithm-artificial intelligence.
by: Hazlee Azil Illias, et al.
Published: (2021-01-01) -
Intermittent Smoothing Approaches for Wind Power Output: A Review
by: Muhammad Jabir, et al.
Published: (2017-10-01)