Applications of machine learning to machine fault diagnosis: A review and roadmap
Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …
machine fault diagnosis. This is a promising way to release the contribution from human …
Vibration based condition monitoring and fault diagnosis of wind turbine planetary gearbox: A review
As one of the most immensely growing renewable energies, the wind power industry also
experiences a high failure rate and operation & maintenance cost. Therefore, the condition …
experiences a high failure rate and operation & maintenance cost. Therefore, the condition …
An explainable artificial intelligence approach for unsupervised fault detection and diagnosis in rotating machinery
The monitoring of rotating machinery is an essential task in today's production processes.
Currently, several machine learning and deep learning-based modules have achieved …
Currently, several machine learning and deep learning-based modules have achieved …
Practical framework of Gini index in the application of machinery fault feature extraction
Gini index (GI) is an outstanding sparsity index that has high robustness for the interference
of the random impulse noise. Yet, as a new index, the definition of GI in different domains is …
of the random impulse noise. Yet, as a new index, the definition of GI in different domains is …
A new deep auto-encoder method with fusing discriminant information for bearing fault diagnosis
In recent years, deep learning techniques have been proved a promising tool for bearing
fault diagnosis. However, to extract deep features with better representative ability, how to …
fault diagnosis. However, to extract deep features with better representative ability, how to …
Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization
Deep learning has attracted attentions in intelligent fault diagnosis of machinery because it
allows a deep network to accomplish the tasks of feature learning and fault classification …
allows a deep network to accomplish the tasks of feature learning and fault classification …
Deep learning-based intelligent fault diagnosis methods toward rotating machinery
S Tang, S Yuan, Y Zhu - Ieee Access, 2019 - ieeexplore.ieee.org
Fault diagnosis of rotating machinery plays a significant role in the industrial production and
engineering field. Owing to the drawbacks of traditional fault diagnosis methods, such as …
engineering field. Owing to the drawbacks of traditional fault diagnosis methods, such as …
Predicting remaining useful life of rolling bearings based on deep feature representation and transfer learning
For the data-driven remaining useful life (RUL) prediction for rolling bearings, the traditional
machine learning-based methods generally provide insufficient feature representation and …
machine learning-based methods generally provide insufficient feature representation and …
An intelligent diagnosis scheme based on generative adversarial learning deep neural networks and its application to planetary gearbox fault pattern recognition
Z Wang, J Wang, Y Wang - Neurocomputing, 2018 - Elsevier
Planetary gearbox has complex structures and works under various non-stationary
operating conditions. The vibration signals of planetary gearbox are complicated and …
operating conditions. The vibration signals of planetary gearbox are complicated and …
The entropy algorithm and its variants in the fault diagnosis of rotating machinery: A review
Rotating machines have been widely used in industrial engineering. The fault diagnosis of
rotating machines plays a vital important role to reduce the catastrophic failures and heavy …
rotating machines plays a vital important role to reduce the catastrophic failures and heavy …