A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges
Abstract Deep Transfer Learning (DTL) is a new paradigm of machine learning, which can
not only leverage the advantages of Deep Learning (DL) in feature representation, but also …
not only leverage the advantages of Deep Learning (DL) in feature representation, but also …
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 …
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 fault diagnosis method based on global optimization GAN for unbalanced data
Deep learning can be applied to the field of fault diagnosis for its powerful feature
representation capabilities. When a certain class fault samples available are very limited, it …
representation capabilities. When a certain class fault samples available are very limited, it …
A deep learning method for bearing fault diagnosis based on cyclic spectral coherence and convolutional neural networks
Accurate fault diagnosis is critical to ensure the safe and reliable operation of rotating
machinery. Data-driven fault diagnosis techniques based on Deep Learning (DL) have …
machinery. Data-driven fault diagnosis techniques based on Deep Learning (DL) have …
Deep-convolution-based LSTM network for remaining useful life prediction
Accurate prediction of remaining useful life (RUL) has been a critical and challenging
problem in the field of prognostics and health management (PHM), which aims to make …
problem in the field of prognostics and health management (PHM), which aims to make …
Intelligent fault diagnosis of rolling bearings based on normalized CNN considering data imbalance and variable working conditions
Intelligent fault detection and diagnosis, as an important approach, play a crucial role in
ensuring the stable, reliable and safe operation of rolling bearings, which is one of the most …
ensuring the stable, reliable and safe operation of rolling bearings, which is one of the most …
A hybrid classification autoencoder for semi-supervised fault diagnosis in rotating machinery
X Wu, Y Zhang, C Cheng, Z Peng - Mechanical Systems and Signal …, 2021 - Elsevier
Accurate fault diagnosis is critical to the safe and reliable operation of rotating machinery.
Intelligent fault diagnosis techniques based on deep learning have recently gained …
Intelligent fault diagnosis techniques based on deep learning have recently gained …
Mechanical fault diagnosis using convolutional neural networks and extreme learning machine
In the era of the so called 4th industrial revolution, the Factory of the Future and the Industrial
Internet of Things, the industrial mechanical systems become continuously more intelligent …
Internet of Things, the industrial mechanical systems become continuously more intelligent …
Deep learning techniques in intelligent fault diagnosis and prognosis for industrial systems: a review
S Qiu, X Cui, Z **, N Shan, Z Li, X Bao, X Xu - Sensors, 2023 - mdpi.com
Fault diagnosis and prognosis (FDP) tries to recognize and locate the faults from the
captured sensory data, and also predict their failures in advance, which can greatly help to …
captured sensory data, and also predict their failures in advance, which can greatly help to …