Intelligent fault diagnosis of machines with small & imbalanced data: A state-of-the-art review and possible extensions
The research on intelligent fault diagnosis has yielded remarkable achievements based on
artificial intelligence-related technologies. In engineering scenarios, machines usually work …
artificial intelligence-related technologies. In engineering scenarios, machines usually work …
Bearing fault detection and diagnosis using case western reserve university dataset with deep learning approaches: A review
A smart factory is a highly digitized and connected production facility that relies on smart
manufacturing. Additionally, artificial intelligence is the core technology of smart factories …
manufacturing. Additionally, artificial intelligence is the core technology of smart factories …
Deep learning algorithms for rotating machinery intelligent diagnosis: An open source benchmark study
Rotating machinery intelligent diagnosis based on deep learning (DL) has gone through
tremendous progress, which can help reduce costly breakdowns. However, different …
tremendous progress, which can help reduce costly breakdowns. However, different …
Federated learning for machinery fault diagnosis with dynamic validation and self-supervision
Intelligent data-driven machinery fault diagnosis methods have been successfully and
popularly developed in the past years. While promising diagnostic performance has been …
popularly developed in the past years. While promising diagnostic performance has been …
Review of tool condition monitoring in machining and opportunities for deep learning
Tool condition monitoring and machine tool diagnostics are performed using advanced
sensors and computational intelligence to predict and avoid adverse conditions for cutting …
sensors and computational intelligence to predict and avoid adverse conditions for cutting …
A comprehensive review on convolutional neural network in machine fault diagnosis
With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …
increasingly significant to ensure safe equipment operation and production. Consequently …
Deep learning for prognostics and health management: State of the art, challenges, and opportunities
B Rezaeianjouybari, Y Shang - Measurement, 2020 - Elsevier
Improving the reliability of engineered systems is a crucial problem in many applications in
various engineering fields, such as aerospace, nuclear energy, and water declination …
various engineering fields, such as aerospace, nuclear energy, and water declination …
Intelligent fault diagnosis of rolling bearings under imbalanced data conditions using attention-based deep learning method
J Li, Y Liu, Q Li - Measurement, 2022 - Elsevier
Data-driven intelligent method has been widely used in fault diagnostics. However, it is
observed that previous research studies focusing on imbalanced datasets for fault diagnosis …
observed that previous research studies focusing on imbalanced datasets for fault diagnosis …
A multi-stage semi-supervised learning approach for intelligent fault diagnosis of rolling bearing using data augmentation and metric learning
Limited condition monitoring data are recorded with label information in practice, which
make the fault identification task more challenging. A semi-supervised learning (SSL) …
make the fault identification task more challenging. A semi-supervised learning (SSL) …
Machinery fault diagnosis with imbalanced data using deep generative adversarial networks
Despite the recent advances of intelligent data-driven fault diagnosis methods on rotating
machines, balanced training data for different machine health conditions are assumed in …
machines, balanced training data for different machine health conditions are assumed in …