Data augmentation and intelligent fault diagnosis of planetary gearbox using ILoFGAN under extremely limited samples
M Chen, H Shao, H Dou, W Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Although the existing generative adversarial networks (GAN) have the potential for data
augmentation and intelligent fault diagnosis of planetary gearbox, it remains difficult to deal …
augmentation and intelligent fault diagnosis of planetary gearbox, it remains difficult to deal …
Improvement of generative adversarial network and its application in bearing fault diagnosis: A review
A small sample size and unbalanced sample distribution are two main problems when data-
driven methods are applied for fault diagnosis in practical engineering. Technically, sample …
driven methods are applied for fault diagnosis in practical engineering. Technically, sample …
Prior knowledge-embedded meta-transfer learning for few-shot fault diagnosis under variable operating conditions
In recent years, intelligent fault diagnosis based on deep learning has achieved vigorous
development thanks to its powerful feature representation ability. However, scarcity of high …
development thanks to its powerful feature representation ability. However, scarcity of high …
Dynamic joint distribution alignment network for bearing fault diagnosis under variable working conditions
An inconsistent distribution between training and testing data caused by complicated and
changeable machine working conditions hinders wide applications of traditional deep …
changeable machine working conditions hinders wide applications of traditional deep …
Statistical methods with applications in data mining: A review of the most recent works
JF Pinto da Costa, M Cabral - Mathematics, 2022 - mdpi.com
The importance of statistical methods in finding patterns and trends in otherwise
unstructured and complex large sets of data has grown over the past decade, as the amount …
unstructured and complex large sets of data has grown over the past decade, as the amount …
Fault severity classification of ball bearing using SinGAN and deep convolutional neural network
Condition monitoring and diagnosis of a bearing are very important for any rotating machine
as it governs the safety while the machine is in operating condition. To construct a feature …
as it governs the safety while the machine is in operating condition. To construct a feature …
A two-step data augmentation method based on generative adversarial network for hardness prediction of high entropy alloy
Z Yang, S Li, S Li, J Yang, D Liu - Computational Materials Science, 2023 - Elsevier
The machine learning (ML) has been widely applied in materials science research and has
made a lot of contributions. However, the performance of ML model is limited by the amount …
made a lot of contributions. However, the performance of ML model is limited by the amount …
Detection of foreign objects intrusion into transmission lines using diverse generation model
Y Wu, S Zhao, Z Xing, Z Wei, Y Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Foreign objects intrusion into transmission lines can lead to serious troubles, using deep
learning technology for foreign object detection has good performance and can reduce …
learning technology for foreign object detection has good performance and can reduce …
A multi-module generative adversarial network augmented with adaptive decoupling strategy for intelligent fault diagnosis of machines with small sample
In actual industrial environment, intelligent diagnosis method requires a sufficient number of
samples to ensure application effect. However, once industrial system fails, it usually stops …
samples to ensure application effect. However, once industrial system fails, it usually stops …
Effective time-series Data Augmentation with Analytic Wavelets for bearing fault diagnosis
DKB Kulevome, H Wang, BM Cobbinah… - Expert Systems with …, 2024 - Elsevier
In the realm of rotary machine maintenance, rolling bearings emerge as crucial yet
frequently vulnerable components. Ensuring their operational integrity is pivotal for the …
frequently vulnerable components. Ensuring their operational integrity is pivotal for the …