Artificial intelligence application in fault diagnostics of rotating industrial machines: A state-of-the-art review
The fault monitoring and diagnosis of industrial machineries are very significant in Industry
4.0 revolution but are often complicated and labour intensive. The application of artificial …
4.0 revolution but are often complicated and labour intensive. The application of artificial …
Condition monitoring and fault diagnosis of planetary gearboxes: A review
Planetary gearboxes significantly differ from fixed-axis gearboxes and exhibit unique
behaviors, which invalidate fault diagnosis methods working well for fixed-axis gearboxes …
behaviors, which invalidate fault diagnosis methods working well for fixed-axis gearboxes …
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 …
is essential to monitor such systems for smooth and continuous operations to anticipate …
Predictive monitoring of incipient faults in rotating machinery: a systematic review from data acquisition to artificial intelligence
Predictive maintenance is one of the major tasks in today's modern industries. All rotating
machines consisting of rotating elements such as gears, bearings etc are considered as the …
machines consisting of rotating elements such as gears, bearings etc are considered as the …
ANFIS system for prognosis of dynamometer high-speed ball bearing based on frequency domain acoustic emission signals
M Motahari-Nezhad, SM Jafari - Measurement, 2020 - Elsevier
Bearing faults account for approximately half of all electric machine failures. Bearing
condition monitoring is of practical importance. Until now, there is not any complete research …
condition monitoring is of practical importance. Until now, there is not any complete research …
Robust and explainable fault diagnosis with power-perturbation-based decision boundary analysis of deep learning models
Robustness of neural network models is important in fault diagnosis (FD) because
uncertainty in operating conditions varies the power spectral densities of vibration data; …
uncertainty in operating conditions varies the power spectral densities of vibration data; …
Planetary gear train microcrack detection using vibration data and convolutional neural networks
S Emmanuel, Y Yihun, Z Nili Ahmedabadi… - Neural Computing and …, 2021 - Springer
Planetary gear trains (PGTs) are widely used in many industrial applications from wind
turbines to automobile transmissions due to their high power-to-weight ratio. Since PGT can …
turbines to automobile transmissions due to their high power-to-weight ratio. Since PGT can …
Vibration-based diagnostics of epicyclic gearboxes–From classical to soft-computing methods
The paper presents up-to-date multidisciplinary review of scientific knowledge and industrial
guidelines concerning the issue of technical assessment of epicyclic gearboxes on the basis …
guidelines concerning the issue of technical assessment of epicyclic gearboxes on the basis …
Fault diagnosis of planetary gearbox with incomplete information using assignment reduction and flexible naive Bayesian classifier
J Yu, M Bai, G Wang, X Shi - Journal of Mechanical Science and …, 2018 - Springer
In planetary gearbox operation, there are many uncertain factors that may result in
incomplete diagnostic information, such as measurement instrument faults, limitation of …
incomplete diagnostic information, such as measurement instrument faults, limitation of …
Feature extraction based on PSO-FC optimizing KPCA and wear fault identification of planetary gear
Y He, L Ye, X Zhu, Z Wang - Journal of Mechanical Science and …, 2021 - Springer
The feature extraction problem of coupled vibration signals with multiple fault modes of
planetary gear has not been solved effectively. At present, kernel principal component …
planetary gear has not been solved effectively. At present, kernel principal component …