Latest innovations in the field of condition-based maintenance of rotatory machinery: A review
A Kumar, CP Gandhi, H Tang, W Sun… - Measurement Science …, 2023 - iopscience.iop.org
Health monitoring in rotatory machinery is a process of developing a mechanism to
determine its state of deterioration. It involves analysing the presence of damage, locating …
determine its state of deterioration. It involves analysing the presence of damage, locating …
Integrated intelligent fault diagnosis approach of offshore wind turbine bearing based on information stream fusion and semi-supervised learning
Offshore wind turbines play a vital role in transferring wind energy to electricity, which could
help relieve the energy crisis and improve the global climate. In general, offshore wind …
help relieve the energy crisis and improve the global climate. In general, offshore wind …
Digital Twins in safety analysis, risk assessment and emergency management
E Zio, L Miqueles - Reliability Engineering & System Safety, 2024 - Elsevier
Digital twins (DTs) represent an emerging technology that is currently leveraging the
monitoring of complex systems, the implementation of autonomous control systems, and …
monitoring of complex systems, the implementation of autonomous control systems, and …
Data-driven bearing health management using a novel multi-scale fused feature and gated recurrent unit
Remaining useful life (RUL) prediction plays a crucial role in bearing health management
which can guarantee the rotating machinery systems' safety and reliability. This paper …
which can guarantee the rotating machinery systems' safety and reliability. This paper …
A novel digital twin-driven approach based on physical-virtual data fusion for gearbox fault diagnosis
The acknowledged challenge of intelligent fault diagnosis methods is that constructing a
reliable diagnosis model requires numerous labeled datasets as training data, which is …
reliable diagnosis model requires numerous labeled datasets as training data, which is …
Digital twin-assisted imbalanced fault diagnosis framework using subdomain adaptive mechanism and margin-aware regularization
The current data-level and algorithm-level based imbalanced fault diagnosis methods have
respective limitations such as uneven data generation quality and excessive reliance on …
respective limitations such as uneven data generation quality and excessive reliance on …
C-ECAFormer: A new lightweight fault diagnosis framework towards heavy noise and small samples
In engineering practice, small-sample fault diagnosis of mechanical equipment towards
heavy noise interference poses great challenges for the existing Transformer based …
heavy noise interference poses great challenges for the existing Transformer based …
Digital twin enabled domain adversarial graph networks for bearing fault diagnosis
K Feng, Y Xu, Y Wang, S Li, Q Jiang… - … on Industrial Cyber …, 2023 - ieeexplore.ieee.org
The fault diagnosis of rolling bearings is of utmost importance in industrial applications to
ensure mechanical systems' reliability, safety, and economic viability. However …
ensure mechanical systems' reliability, safety, and economic viability. However …
Heterogeneous federated domain generalization network with common representation learning for cross-load machinery fault diagnosis
Various federated transfer learning (FTL) methods have been proposed to address domain
shift and safeguard data privacy in the field of fault diagnosis. However, the effectiveness of …
shift and safeguard data privacy in the field of fault diagnosis. However, the effectiveness of …
Digital twin-driven focal modulation-based convolutional network for intelligent fault diagnosis
S Li, Q Jiang, Y Xu, K Feng, Y Wang, B Sun… - Reliability Engineering & …, 2023 - Elsevier
Rolling bearings are essential components of various rotating machinery and are critical in
ensuring safe and reliable industrial production. Deep learning techniques have …
ensuring safe and reliable industrial production. Deep learning techniques have …