Imbalanced fault diagnosis of rotating machinery via multi-domain feature extraction and cost-sensitive learning

Q Xu, S Lu, W Jia, C Jiang - Journal of Intelligent Manufacturing, 2020 - Springer
Fault diagnosis plays an essential role in rotating machinery manufacturing systems to
reduce their maintenance costs. How to improve diagnosis accuracy remains an open issue …

Imbalanced data fault diagnosis of rotating machinery using synthetic oversampling and feature learning

Y Zhang, X Li, L Gao, L Wang, L Wen - Journal of manufacturing systems, 2018 - Elsevier
Imbalanced data problems are prevalent in the real rotating machinery applications.
Traditional data-driven diagnosis methods fail to identify the fault condition effectively for …

A novel transfer learning method for robust fault diagnosis of rotating machines under variable working conditions

W Qian, S Li, P Yi, K Zhang - Measurement, 2019 - Elsevier
Vibration signals are closely linked with health conditions of rotating machines and widely
used in fault diagnosis. Unfortunately, traditional vibration signal-based fault diagnosis …

Intelligent rotating machinery fault diagnosis based on deep learning using data augmentation

X Li, W Zhang, Q Ding, JQ Sun - Journal of Intelligent Manufacturing, 2020 - Springer
Intelligent machinery fault diagnosis system has been receiving increasing attention recently
due to the potential large benefits of maintenance cost reduction, enhanced operation safety …

Multi-view rotating machinery fault diagnosis with adaptive co-attention fusion network

X Liu, J Wang, S Meng, X Qiu, G Zhao - Engineering Applications of …, 2023 - Elsevier
Intelligent fault diagnosis is an intriguing topic, attracting increasing interest in safe and
reliable industrial production. Tremendous progress has been made in recent years in …

Multi-fault diagnosis of rotating machinery based on deep convolution neural network and support vector machine

Y Xue, D Dou, J Yang - Measurement, 2020 - Elsevier
Because multi-fault vibration signals in rotating machinery are often more complicated than
single faults, human-designed fault feature sets are not yet able to respond adequately to …

Data fusion generative adversarial network for multi-class imbalanced fault diagnosis of rotating machinery

Q Liu, G Ma, C Cheng - IEEE Access, 2020 - ieeexplore.ieee.org
For the fault diagnosis problems of rotating machinery in the real industrial practice,
measurement data with imbalanced class distributions negatively affect the diagnostic …

Unsupervised cross-domain fault diagnosis using feature representation alignment networks for rotating machinery

J Chen, J Wang, J Zhu, TH Lee… - … /ASME Transactions on …, 2020 - ieeexplore.ieee.org
In this article, the problem of the cross-domain fault diagnosis of rotating machinery is
considered. In a practical setting of this approach, the operating platform of the machine may …

[HTML][HTML] Fault diagnosis for rotating machinery using vibration measurement deep statistical feature learning

C Li, RV Sánchez, G Zurita, M Cerrada, D Cabrera - Sensors, 2016 - mdpi.com
Fault diagnosis is important for the maintenance of rotating machinery. The detection of
faults and fault patterns is a challenging part of machinery fault diagnosis. To tackle this …

Fault diagnosis of rotating machinery based on deep reinforcement learning and reciprocal of smoothness index

W Dai, Z Mo, C Luo, J Jiang, H Zhang… - IEEE Sensors …, 2020 - ieeexplore.ieee.org
Rotating machinery are widely used in industry, and vibration analysis is one of the most
common methods to monitor health condition of rotating machinery. However, due to the …