Fault detection and diagnosis in power transformers: a comprehensive review and classification of publications and methods

AR Abbasi - Electric Power Systems Research, 2022 - Elsevier
A challenging problem in the protection of power transformers is the fault detection and
diagnosis (FDD). FDD has an essential role in the reliability and safety of modern power …

Advances in DGA based condition monitoring of transformers: A review

SA Wani, AS Rana, S Sohail, O Rahman… - … and Sustainable Energy …, 2021 - Elsevier
Abstract Dissolved Gas Analysis (DGA) is a standout diagnostic strategy to recognise
incipient faults and monitor the condition of oil-immersed transformers. It correlates the …

Adaptive dynamic meta-heuristics for feature selection and classification in diagnostic accuracy of transformer faults

SSM Ghoneim, TA Farrag, AA Rashed… - Ieee …, 2021 - ieeexplore.ieee.org
Detection of transformer faults avoids the transformer's undesirable loss from service and
ensures utility service continuity. Diagnosis of transformer faults is determined using …

Human activity recognition in IoHT applications using arithmetic optimization algorithm and deep learning

A Dahou, MAA Al-qaness, M Abd Elaziz, A Helmi - Measurement, 2022 - Elsevier
Nowadays, people use smart devices everywhere and for different applications such as
healthcare. The Internet of Healthcare Things (IoHT) generates enormous amounts of data …

A new method for prediction of air pollution based on intelligent computation

S Al-Janabi, M Mohammad, A Al-Sultan - Soft Computing, 2020 - Springer
The detection and treatment of increasing air pollution due to technological developments
represent some of the most important challenges facing the world today. Indeed, there has …

Intelligent forecaster of concentrations (PM2. 5, PM10, NO2, CO, O3, SO2) caused air pollution (IFCsAP)

S Al-Janabi, A Alkaim, E Al-Janabi, A Aljeboree… - Neural Computing and …, 2021 - Springer
Upgrading health reality is the responsibility of all, it is necessary to think about the design of
a smart system based on modern technologies to reduce the time and effort exerted on the …

An Innovative synthesis of deep learning techniques (DCapsNet & DCOM) for generation electrical renewable energy from wind energy

S Al-Janabi, AF Alkaim, Z Adel - Soft Computing, 2020 - Springer
Renewable energy becomes one of the main resources that help the world to safety the
environment from pollution and provide the people of new type of energy; therefore, this …

Optimal dissolved gas ratios selected by genetic algorithm for power transformer fault diagnosis based on support vector machine

J Li, Q Zhang, K Wang, J Wang… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Dissolved gas analysis (DGA) of oil is used to detect the incipient fault of power
transformers. This paper presents a new approach for transformer fault diagnosis based on …

[HTML][HTML] Codon-mRNA prediction using deep optimal neurocomputing technique (DLSTM-DSN-WOA) and multivariate analysis

ZA Kadhuim, S Al-Janabi - Results in Engineering, 2023 - Elsevier
Based on the principle that the upgrading of any nation begins by raising the level of
performance of its institutions that serve the community, including the Ministry of Healthcare …

Dynamic fault prediction of power transformers based on hidden Markov model of dissolved gases analysis

J Jiang, R Chen, M Chen, W Wang… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Dissolved gases analysis (DGA) provides widely recognized practice for oil-immersed
power transformers, and it is mainly interpreted for fault diagnosis. In order to accurately …