A comprehensive review of artificial intelligence and wind energy

FP Garcia Marquez, A Peinado Gonzalo - Archives of Computational …, 2022 - Springer
Support of artificial intelligence, renewable energy and sustainability is currently increasing
through the main policies of developed countries, eg, the White Paper of the European …

Feature extraction using Discrete Wavelet Transform for fault classification of planetary gearbox–A comparative study

SH Syed, V Muralidharan - Applied Acoustics, 2022 - Elsevier
Monitoring the condition of unreachable gears of epicyclic gearbox in real-time increases
the asset reliability by anticipating the failures through preventive maintenance. Machine …

Fault classification in three-phase motors based on vibration signal analysis and artificial neural networks

RF Ribeiro Junior, FA de Almeida… - Neural Computing and …, 2020 - Springer
Competition in the industrial environment is increasingly intense, so it is of utmost
importance that organizations keep their assets in operation as much as possible (in order to …

Comparative analysis of fuzzy classifier and ANN with histogram features for defect detection and classification in planetary gearbox

SS Hameed, V Muralidharan, BK Ane - Applied Soft Computing, 2021 - Elsevier
The planetary gearbox plays a vital role in many heavy-duty power transmission systems. It
is essential to monitor such systems for smooth and continuous operations to anticipate …

Intelligent framework for automated failure prediction, detection, and classification of mission critical autonomous flights

MW Ahmad, MU Akram, R Ahmad, K Hameed… - ISA transactions, 2022 - Elsevier
Autonomous flights are the major industry contributors towards next-generation
developments in pervasive and ubiquitous computing. Modern aerial vehicles are designed …

Experimental investigation of efficiency of worm gears and modeling of power loss through artificial neural networks

YE Karabacak, H Baş - Measurement, 2022 - Elsevier
In this study, an experimental system that can operate at different speeds and loading rates
was developed for the efficiency calculations of worm gears (WGs), and measurements were …

Fault diagnosis of bolt loosening based on LightGBM recognition of sound signal features

M Guo, Y Guo, Y Peng, W Zhang… - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
Aiming at the strong vibration condition of the inner curve radial plunger hydraulic motor, the
bolt connection of the motor base is easy to loosen, and it is difficult to distinguish the early …

[HTML][HTML] Fuel economy improvement of urban buses with development of an eco-drive scoring algorithm using machine learning

K Kim, J Park, J Lee - Energies, 2021 - mdpi.com
Eco-drive is a widely used concept. It can improve fuel economy for different driving
behaviors such as vehicle acceleration or accelerator pedal operation, deceleration or …

A comparison of machine learning techniques for LNG pumps fault prediction in regasification plants

MA Crespo, E Candón, JF Gómez, J Serra - IFAC-PapersOnLine, 2020 - Elsevier
We present a comparative study on the most popular machine learning methods applied to
the challenging problem of Liquefied Natural Gas pumps fault prediction in regasification …

Fault detection in single-stage helical planetary gearbox using support vector machine (svm) and artificial neural network (ann) with statistical features

SS Hameed, V Muralidharan - Advances in Design and Thermal Systems …, 2021 - Springer
Drive train failures are most common in wind turbines. Lots of effort have been made to
improve the reliability of the gearbox but the truth is that these efforts do not provide a …