Advanced signal processing methods for condition monitoring
Condition monitoring of induction motors (IM) among with the predictive maintenance
concept are currently among the most promising research topics of manufacturing industry …
concept are currently among the most promising research topics of manufacturing industry …
Meta-learning as a promising approach for few-shot cross-domain fault diagnosis: Algorithms, applications, and prospects
Y Feng, J Chen, J Xie, T Zhang, H Lv, T Pan - Knowledge-Based Systems, 2022 - Elsevier
The advances of intelligent fault diagnosis in recent years show that deep learning has
strong capability of automatic feature extraction and accurate identification for fault signals …
strong capability of automatic feature extraction and accurate identification for fault signals …
Multi-input CNN based vibro-acoustic fusion for accurate fault diagnosis of induction motor
Induction motor (IM) is a highly efficient prime mover in industrial applications. To maintain
an uninterrupted operation, accurate fault diagnosis system of IM is required. It can help to …
an uninterrupted operation, accurate fault diagnosis system of IM is required. It can help to …
A case study of conditional deep convolutional generative adversarial networks in machine fault diagnosis
J Luo, J Huang, H Li - Journal of Intelligent Manufacturing, 2021 - Springer
Due to the real working conditions, the collected mechanical fault datasets are actually
limited and always highly imbalanced, which restricts the diagnosis accuracy and stability …
limited and always highly imbalanced, which restricts the diagnosis accuracy and stability …
Imbalance fault diagnosis under long-tailed distribution: Challenges, solutions and prospects
Intelligent fault diagnosis based on deep learning has yielded remarkable progress for its
strong feature representation capability in recent years. Nevertheless, in engineering …
strong feature representation capability in recent years. Nevertheless, in engineering …
A recursive sparse representation strategy for bearing fault diagnosis
C Han, W Lu, P Wang, L Song, H Wang - Measurement, 2022 - Elsevier
Partial faults of bearings trigger periodic vibration features, but the interference makes fault
diagnosis more difficult. A recursive sparse representation (RSR) algorithm is proposed to …
diagnosis more difficult. A recursive sparse representation (RSR) algorithm is proposed to …
Multi-channel Calibrated Transformer with Shifted Windows for few-shot fault diagnosis under sharp speed variation
In engineering practice, mechanical equipment is mainly operated under the working
conditions of sharp speed variations, which results the data distribution domain shift …
conditions of sharp speed variations, which results the data distribution domain shift …
A novel damage identification method based on short time Fourier transform and a new efficient index
Structural failure can be corrected and restored with the preliminary review of the status of
the structures, and thus prevent the spread of corruption and collapse of structures. Among …
the structures, and thus prevent the spread of corruption and collapse of structures. Among …
Industrial edge intelligence: Federated-meta learning framework for few-shot fault diagnosis
The scarcity of fault samples has been the bottleneck for the large-scale application of
mechanical fault diagnosis (FD) methods in the industrial Internet of Things (IIoT). Traditional …
mechanical fault diagnosis (FD) methods in the industrial Internet of Things (IIoT). Traditional …
Enhanced generative adversarial networks for fault diagnosis of rotating machinery with imbalanced data
Deep learning-based methods have attracted the attention of researchers due to their
outstanding performance in automatic feature learning, a crucial step for satisfactory fault …
outstanding performance in automatic feature learning, a crucial step for satisfactory fault …