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 …
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
Imbalanced data problems are prevalent in the real rotating machinery applications.
Traditional data-driven diagnosis methods fail to identify the fault condition effectively for …
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 …
used in fault diagnosis. Unfortunately, traditional vibration signal-based fault diagnosis …
Intelligent rotating machinery fault diagnosis based on deep learning using data augmentation
Intelligent machinery fault diagnosis system has been receiving increasing attention recently
due to the potential large benefits of maintenance cost reduction, enhanced operation safety …
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 …
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 …
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
For the fault diagnosis problems of rotating machinery in the real industrial practice,
measurement data with imbalanced class distributions negatively affect the diagnostic …
measurement data with imbalanced class distributions negatively affect the diagnostic …
Unsupervised cross-domain fault diagnosis using feature representation alignment networks for rotating machinery
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 …
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
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 …
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
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 …
common methods to monitor health condition of rotating machinery. However, due to the …
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