Dual-threshold attention-guided GAN and limited infrared thermal images for rotating machinery fault diagnosis under speed fluctuation
End-to-end intelligent diagnosis of rotating machinery under speed fluctuation and limited
samples is challenging in industrial practice. The existing limited samples methods usually …
samples is challenging in industrial practice. The existing limited samples methods usually …
A generative adversarial network-based intelligent fault diagnosis method for rotating machinery under small sample size conditions
Rotating machinery plays a key role in mechanical equipment, and the fault diagnosis of
rotating machinery is a popular research topic. To overcome the dependency on expert …
rotating machinery is a popular research topic. To overcome the dependency on expert …
Generative adversarial network and transfer-learning-based fault detection for rotating machinery with imbalanced data condition
J Li, Y Liu, Q Li - Measurement Science and Technology, 2022 - iopscience.iop.org
Intelligent fault diagnosis achieves tremendous success in machine fault diagnosis because
of its outstanding data-driven capability. However, the severely imbalanced dataset in …
of its outstanding data-driven capability. However, the severely imbalanced dataset in …
Multi-mode data augmentation and fault diagnosis of rotating machinery using modified ACGAN designed with new framework
As one of the representative unsupervised data augmentation methods, generative
adversarial networks (GANs) have the potential to solve the problem of insufficient samples …
adversarial networks (GANs) have the potential to solve the problem of insufficient samples …
Imbalanced fault diagnosis of rolling bearing using enhanced generative adversarial networks
H Zhang, R Wang, R Pan, H Pan - IEEE Access, 2020 - ieeexplore.ieee.org
Machinery fault diagnosis tasks have been well addressed when sufficient and abundant
data are available. However, the data imbalance problem widely exists in real-world …
data are available. However, the data imbalance problem widely exists in real-world …
Fault diagnosis of rotating machinery based on combination of Wasserstein generative adversarial networks and long short term memory fully convolutional network
Y Li, W Zou, L Jiang - Measurement, 2022 - Elsevier
The traditional fault diagnosis methods of rotating machinery based on deep learning have
made some achievements. However, the fault samples are generally difficult to collect …
made some achievements. However, the fault samples are generally difficult to collect …
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 …
Machine fault diagnosis with small sample based on variational information constrained generative adversarial network
S Liu, H Jiang, Z Wu, Y Liu, K Zhu - Advanced Engineering Informatics, 2022 - Elsevier
In actual engineering scenarios, limited fault data leads to insufficient model training and
over-fitting, which negatively affects the diagnostic performance of intelligent diagnostic …
over-fitting, which negatively affects the diagnostic performance of intelligent diagnostic …
Data synthesis using deep feature enhanced generative adversarial networks for rolling bearing imbalanced fault diagnosis
S Liu, H Jiang, Z Wu, X Li - Mechanical Systems and Signal Processing, 2022 - Elsevier
Rolling bearing fault diagnosis is of great significance to the stable operation of rotating
machinery systems. However, the fault data collected in practical engineering is seriously …
machinery systems. However, the fault data collected in practical engineering is seriously …
Improved generative adversarial network for rotating component fault diagnosis in scenarios with extremely limited data
Traditional data-driven intelligent fault diagnosis methods for rotating component commonly
assume that sufficient labeled data is available. However, the rotary machine works in a …
assume that sufficient labeled data is available. However, the rotary machine works in a …