A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges
Abstract Deep Transfer Learning (DTL) is a new paradigm of machine learning, which can
not only leverage the advantages of Deep Learning (DL) in feature representation, but also …
not only leverage the advantages of Deep Learning (DL) in feature representation, but also …
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 …
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …
Towards trustworthy machine fault diagnosis: A probabilistic Bayesian deep learning framework
Fault diagnosis is efficient to improve the safety, reliability, and cost-effectiveness of
industrial machinery. Deep learning has been extensively investigated in fault diagnosis …
industrial machinery. Deep learning has been extensively investigated in fault diagnosis …
Meta-learning for few-shot bearing fault diagnosis under complex working conditions
Deep learning-based bearing fault diagnosis has been systematically studied in recent
years. However, the success of most of these methods relies heavily on massive labeled …
years. However, the success of most of these methods relies heavily on massive labeled …
Machinery fault diagnosis based on domain adaptation to bridge the gap between simulation and measured signals
In intelligent fault diagnosis, the success of artificial intelligence (AI) models is highly
dependent on labeled training samples, which may not be obtained in real-world …
dependent on labeled training samples, which may not be obtained in real-world …
Perspectives on nonstationary process monitoring in the era of industrial artificial intelligence
C Zhao - Journal of Process Control, 2022 - Elsevier
The development of the Internet of Things, cloud computing, and artificial intelligence has
given birth to industrial artificial intelligence (IAI) technology, which enables us to obtain fine …
given birth to industrial artificial intelligence (IAI) technology, which enables us to obtain fine …
Multisource domain feature adaptation network for bearing fault diagnosis under time-varying working conditions
Intelligent fault diagnosis methods based on domain adaptation (DA) have been extensively
employed for tackling domain shift problems, and the basic diagnosis tasks under time …
employed for tackling domain shift problems, and the basic diagnosis tasks under time …
A new multiple source domain adaptation fault diagnosis method between different rotating machines
Fault diagnosis based on data-driven methods are widely investigated when enough
supervised samples of the target machine are available to build a reliable model. However …
supervised samples of the target machine are available to build a reliable model. However …
Motion trajectory prediction based on a CNN-LSTM sequential model
G Xie, A Shangguan, R Fei, W Ji, W Ma… - Science China Information …, 2020 - Springer
Accurate monitoring the surrounding environment is an important research direction in the
field of unmanned systems such as bio-robotics, and has attracted much research attention …
field of unmanned systems such as bio-robotics, and has attracted much research attention …
A deep probabilistic transfer learning framework for soft sensor modeling with missing data
Soft sensors have been extensively developed and applied in the process industry. One of
the main challenges of the data-driven soft sensors is the lack of labeled data and the need …
the main challenges of the data-driven soft sensors is the lack of labeled data and the need …