Attention mechanism in intelligent fault diagnosis of machinery: A review of technique and application
Attention Mechanism has become very popular in the field of mechanical fault diagnosis in
recent years and has become an important technique for scholars to study and apply. The …
recent years and has become an important technique for scholars to study and apply. The …
Construction of health indicators for condition monitoring of rotating machinery: A review of the research
The condition monitoring (CM) of rotating machinery (RM) is an essential operation for
improving the reliability of mechanical systems. For this purpose, an efficient CM method that …
improving the reliability of mechanical systems. For this purpose, an efficient CM method that …
A two-stage method based on extreme learning machine for predicting the remaining useful life of rolling-element bearings
Z Pan, Z Meng, Z Chen, W Gao, Y Shi - Mechanical Systems and Signal …, 2020 - Elsevier
Rolling-element bearing is one of the main parts of rotating equipment. In order to avoid the
mechanical equipment damage caused by the sudden failure of rolling-element bearings, it …
mechanical equipment damage caused by the sudden failure of rolling-element bearings, it …
Multicellular LSTM-based deep learning model for aero-engine remaining useful life prediction
The prediction of aero-engine remaining useful life (RUL) is helpful for its operation and
maintenance. Aiming at the challenge that most neural networks (NNs), including long short …
maintenance. Aiming at the challenge that most neural networks (NNs), including long short …
Bearing fault diagnosis using transfer learning and self-attention ensemble lightweight convolutional neural network
The rapid development of big data leads to many researchers focusing on improving
bearing fault classification accuracy using deep learning models. However, implementing a …
bearing fault classification accuracy using deep learning models. However, implementing a …
A new deep transfer learning network based on convolutional auto-encoder for mechanical fault diagnosis
Deep learning has gained a great achievement in the intelligent fault diagnosis of rotating
machineries. However, the labeled data is scarce in actual engineering and the marginal …
machineries. However, the labeled data is scarce in actual engineering and the marginal …
Remaining useful life prediction of bearings by a new reinforced memory GRU network
The remaining useful life (RUL) prediction of bearings has great significance in the
predictive maintenance of mechanical equipment. Owing to the difficulty of collecting …
predictive maintenance of mechanical equipment. Owing to the difficulty of collecting …
Gated dual attention unit neural networks for remaining useful life prediction of rolling bearings
In the mechatronic system, rolling bearing is a frequently used mechanical part, and its
failure may result in serious accident and major economic loss. Therefore, the remaining …
failure may result in serious accident and major economic loss. Therefore, the remaining …
Health indicator construction by quadratic function-based deep convolutional auto-encoder and its application into bearing RUL prediction
As one of the most important components of machinery, once the bearing has a failure,
serious catastrophe may happen. Hence, for avoiding the catastrophe, it is valuable to …
serious catastrophe may happen. Hence, for avoiding the catastrophe, it is valuable to …
Convolutional neural network based on attention mechanism and Bi-LSTM for bearing remaining life prediction
J Luo, X Zhang - Applied Intelligence, 2022 - Springer
Good prognostic health management (PHM) plays a crucial role in industrial production and
other fields. The accurate prediction of remaining useful life (RUL) can ensure good working …
other fields. The accurate prediction of remaining useful life (RUL) can ensure good working …