An analysis of process fault diagnosis methods from safety perspectives
Industry 4.0 provides substantial opportunities to ensure a safer environment through online
monitoring, early detection of faults, and preventing the faults to failures transitions. Decision …
monitoring, early detection of faults, and preventing the faults to failures transitions. Decision …
Deep learning-based fault diagnosis of photovoltaic systems: A comprehensive review and enhancement prospects
Photovoltaic (PV) systems are subject to failures during their operation due to the aging
effects and external/environmental conditions. These faults may affect the different system …
effects and external/environmental conditions. These faults may affect the different system …
Reduced kernel random forest technique for fault detection and classification in grid-tied PV systems
K Dhibi, R Fezai, M Mansouri, M Trabelsi… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
The random forest (RF) classifier, which is a combination of tree predictors, is one of the
most powerful classification algorithms that has been recently applied for fault detection and …
most powerful classification algorithms that has been recently applied for fault detection and …
Deep learning method for fault detection of wind turbine converter
C Xiao, Z Liu, T Zhang, X Zhang - Applied Sciences, 2021 - mdpi.com
The converter is an important component in wind turbine power drive-train systems, and
usually, it has a higher failure rate. Therefore, detecting the potential faults for prediction of …
usually, it has a higher failure rate. Therefore, detecting the potential faults for prediction of …
Multivariate feature extraction based supervised machine learning for fault detection and diagnosis in photovoltaic systems
Fault detection and diagnosis (FDD) in the photovoltaic (PV) array has become a challenge
due to the magnitudes of the faults, the presence of maximum power point trackers, non …
due to the magnitudes of the faults, the presence of maximum power point trackers, non …
Fault diagnosis of rotating machinery based on graph weighted reinforcement networks under small samples and strong noise
X Yu, B Tang, L Deng - Mechanical Systems and Signal Processing, 2023 - Elsevier
Available fault vibration signals of large rotating machines are usually limited and consist of
strong noise. Existing deep learning methods do not sufficiently extract the correlation …
strong noise. Existing deep learning methods do not sufficiently extract the correlation …
Predicting the parameters of vortex bladeless wind turbine using deep learning method of long short-term memory
M Dehghan Manshadi, M Ghassemi, SM Mousavi… - Energies, 2021 - mdpi.com
From conventional turbines to cutting-edge bladeless turbines, energy harvesting from wind
has been well explored by researchers for more than a century. The vortex bladeless wind …
has been well explored by researchers for more than a century. The vortex bladeless wind …
Genetic-algorithm-based neural network for fault detection and diagnosis: Application to grid-connected photovoltaic systems
Modern photovoltaic (PV) systems have received significant attention regarding fault
detection and diagnosis (FDD) for enhancing their operation by boosting their dependability …
detection and diagnosis (FDD) for enhancing their operation by boosting their dependability …
An adaptive fault detection and root-cause analysis scheme for complex industrial processes using moving window KPCA and information geometric causal inference
In recent years, fault detection and diagnosis for industrial processes have been rapidly
developed to minimize costs and maximize efficiency by taking advantages of cheap …
developed to minimize costs and maximize efficiency by taking advantages of cheap …
A generalized cauchy method for remaining useful life prediction of wind turbine gearboxes
H Liu, W Song, Y Niu, E Zio - Mechanical Systems and Signal Processing, 2021 - Elsevier
The accurate estimate of the Remaining Useful Life (RUL) of mechanical tools is a
fundamental problem in Engineering. This prediction often implies the knowledge and …
fundamental problem in Engineering. This prediction often implies the knowledge and …