Integration of novel sensors and machine learning for predictive maintenance in medium voltage switchgear to enable the energy and mobility revolutions

MW Hoffmann, S Wildermuth, R Gitzel, A Boyaci… - Sensors, 2020 - mdpi.com
The development of renewable energies and smart mobility has profoundly impacted the
future of the distribution grid. An increasing bidirectional energy flow stresses the assets of …

Infrared image target detection of substation electrical equipment using an improved faster R-CNN

J Ou, J Wang, J Xue, J Wang, X Zhou… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Infrared camera can be used to monitor the condition of substation electrical equipment. Fast
and accurate target detection algorithm is the key for infrared intelligent on-line routing …

Electrical fault detection in three-phase induction motor using deep network-based features of thermograms

M Khanjani, M Ezoji - Measurement, 2021 - Elsevier
In this paper, an automatic method is proposed for detecting the operating faults in three-
phase induction motors based on thermal images. If these faults are not detected or fixed on …

Human emotions detection based on a smart-thermal system of thermographic images

IA Cruz-Albarran, JP Benitez-Rangel… - Infrared Physics & …, 2017 - Elsevier
This work presents a noninvasive methodology to obtain biomedical thermal imaging which
provide relevant information that may assist in the diagnosis of emotions. Biomedical …

Multi-layered Ordovician paleokarst reservoir detection and spatial delineation: A case study in the Tahe Oilfield, Tarim Basin, Western China

F Tian, Q **, X Lu, Y Lei, L Zhang, S Zheng… - Marine and Petroleum …, 2016 - Elsevier
Paleokarst systems are major carbonate reservoirs that can form significant and very large
oilfields. The Ordovician carbonate reservoirs of the Tahe Oilfield represent a special type of …

Fault diagnosis of electrical equipment through thermal imaging and interpretable machine learning applied on a newly-introduced dataset

M Najafi, Y Baleghi, SA Gholamian… - 2020 6th Iranian …, 2020 - ieeexplore.ieee.org
In this study, an interpretable, fully automated pipeline for condition monitoring of electrical
equipment using thermal imaging is proposed. A wider array of defects in comparison with …

An intelligent system for quality measurement of Golden Bleached raisins using two comparative machine learning algorithms

N Karimi, RR Kondrood, T Alizadeh - Measurement, 2017 - Elsevier
In this research, an expert system is provided for measuring and recognizing the quality and
purity of mixed (pure-impure) raisins using bulk raisins' images. For this purpose, by utilizing …

Image-based incipient fault classification of electrical substation equipment by transfer learning of deep convolutional neural network

X Guan, W Gao, H Peng, N Shu… - IEEE Canadian Journal …, 2021 - ieeexplore.ieee.org
A transfer learning-based deep convolutional neural network (DCNN) is employed in this
article to identify several typical electrical substation equipment incipient faults. Image …

Localization of thermal anomalies in electrical equipment using Infrared Thermography and support vector machine

YL dit Leksir, M Mansour, A Moussaoui - Infrared Physics & Technology, 2018 - Elsevier
Abstract Analysis and processing of databases obtained from infrared thermal inspections
made on electrical installations require the development of new tools to obtain more …

Online monitoring of electrical equipment condition based on infrared image temperature data visualization

J Wang, J Ou, Y Fan, L Cai… - IEEJ Transactions on …, 2022 - Wiley Online Library
Temperature is one of the most common indicators for the health of electrical equipment in
the substation. By now, infrared thermography has been an important monitoring tool due to …