A review of the application of deep learning in intelligent fault diagnosis of rotating machinery

Z Zhu, Y Lei, G Qi, Y Chai, N Mazur, Y An, X Huang - Measurement, 2023 - Elsevier
With the rapid development of industry, fault diagnosis plays a more and more important role
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …

A comprehensive review on convolutional neural network in machine fault diagnosis

J Jiao, M Zhao, J Lin, K Liang - Neurocomputing, 2020 - Elsevier
With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …

A deep learning method for bearing fault diagnosis based on cyclic spectral coherence and convolutional neural networks

Z Chen, A Mauricio, W Li, K Gryllias - Mechanical Systems and Signal …, 2020 - Elsevier
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 …

Semi-supervised meta-learning networks with squeeze-and-excitation attention for few-shot fault diagnosis

Y Feng, J Chen, T Zhang, S He, E Xu, Z Zhou - ISA transactions, 2022 - Elsevier
In the engineering practice, lacking of data especially labeled data typically hinders the wide
application of deep learning in mechanical fault diagnosis. However, collecting and labeling …

An adaptive deep transfer learning method for bearing fault diagnosis

Z Wu, H Jiang, K Zhao, X Li - Measurement, 2020 - Elsevier
Bearing fault diagnosis has made some achievements based on massive labeled fault data.
In practical engineering, machines are mostly in healthy and faults seldom happen, it's …

Challenges and opportunities of AI-enabled monitoring, diagnosis & prognosis: A review

Z Zhao, J Wu, T Li, C Sun, R Yan, X Chen - Chinese Journal of Mechanical …, 2021 - Springer
Abstract Prognostics and Health Management (PHM), including monitoring, diagnosis,
prognosis, and health management, occupies an increasingly important position in reducing …

A new dynamic model and transfer learning based intelligent fault diagnosis framework for rolling element bearings race faults: Solving the small sample problem

Y Dong, Y Li, H Zheng, R Wang, M Xu - ISA transactions, 2022 - Elsevier
Intelligent fault diagnosis of rolling element bearings gains increasing attention in recent
years due to the promising development of artificial intelligent technology. Many intelligent …

Deep learning-based intelligent fault diagnosis methods toward rotating machinery

S Tang, S Yuan, Y Zhu - Ieee Access, 2019 - ieeexplore.ieee.org
Fault diagnosis of rotating machinery plays a significant role in the industrial production and
engineering field. Owing to the drawbacks of traditional fault diagnosis methods, such as …

Machine learning approach using MLP and SVM algorithms for the fault prediction of a centrifugal pump in the oil and gas industry

PF Orrù, A Zoccheddu, L Sassu, C Mattia, R Cozza… - Sustainability, 2020 - mdpi.com
The demand for cost-effective, reliable and safe machinery operation requires accurate fault
detection and classification to achieve an efficient maintenance strategy and increase …

Data preprocessing techniques in convolutional neural network based on fault diagnosis towards rotating machinery

S Tang, S Yuan, Y Zhu - IEEE Access, 2020 - ieeexplore.ieee.org
Rotating machinery plays a critical role in many significant fields. However, the
unpredictable machinery faults may lead to the severe damage and losses. Hence, it is of …