Hydrogenerator early fault detection: Sparse dictionary learning jointly with the variational autoencoder
Monitoring the continuous health status of a Hydraulic Turbine Generator Unit (HTGU) is a
strategic task to prevent any unexpected downtime. In addition to the loss of energy …
strategic task to prevent any unexpected downtime. In addition to the loss of energy …
Cracking performance evaluation and modelling of RAP mixtures containing different recycled materials using deep neural network model
This study evaluates the cracking resistance of recycled asphalt pavement (RAP) mixtures
including waste engine oil (WEO), crumb rubber (CR), and steel slag aggregates using the …
including waste engine oil (WEO), crumb rubber (CR), and steel slag aggregates using the …
[HTML][HTML] Prognostics and health management in nuclear power plants: An updated method-centric review with special focus on data-driven methods
In a carbon-constrained world, future uses of nuclear power technologies can contribute to
climate change mitigation as the installed electricity generating capacity and range of …
climate change mitigation as the installed electricity generating capacity and range of …
Probabilistic deep learning methodology for uncertainty quantification of remaining useful lifetime of multi-component systems
KTP Nguyen, K Medjaher, C Gogu - Reliability Engineering & System Safety, 2022 - Elsevier
For dealing with uncertainty in Remaining Useful Life (RUL) predictions, numerous studies
in literature use stochastic models to characterize the degradation process and predict the …
in literature use stochastic models to characterize the degradation process and predict the …
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 deep multi-source domain adaptation framework for bearing fault diagnosis based on feature-level and task-specific distribution alignment
B Rezaeianjouybari, Y Shang - Measurement, 2021 - Elsevier
In recent years, deep learning has been extensively applied for intelligent fault diagnosis
systems. Most of the developed algorithms ignore the domain shift problem and assume …
systems. Most of the developed algorithms ignore the domain shift problem and assume …
A review of fault diagnosis, prognosis and health management for aircraft electromechanical actuators
Z Yin, N Hu, J Chen, Y Yang… - IET Electric Power …, 2022 - Wiley Online Library
Abstract As More/All Electric Aircraft gradually become a research hotspot,
electromechanical actuators (EMAs), which can directly convert electrical energy into …
electromechanical actuators (EMAs), which can directly convert electrical energy into …
[HTML][HTML] Towards interpretable deep learning: a feature selection framework for prognostics and health management using deep neural networks
In the last five years, the inclusion of Deep Learning algorithms in prognostics and health
management (PHM) has led to a performance increase in diagnostics, prognostics, and …
management (PHM) has led to a performance increase in diagnostics, prognostics, and …
A tool wear condition monitoring method for non-specific sensing signals
Real-time and accurate monitoring of tool wear conditions is crucial to achieving double
optimization of production cost and product quality. However, the differences in the …
optimization of production cost and product quality. However, the differences in the …
FS-SCF network: Neural network interpretability based on counterfactual generation and feature selection for fault diagnosis
Interpretability of neural networks aims at the development of models that can give
information to the end-user about its inner workings and/or predictions, while keeping the …
information to the end-user about its inner workings and/or predictions, while keeping the …