A comprehensive review on convolutional neural network in machine fault diagnosis
With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …
increasingly significant to ensure safe equipment operation and production. Consequently …
A review of failure modes, condition monitoring and fault diagnosis methods for large-scale wind turbine bearings
Large-scale wind turbine bearings including main bearings, gearbox bearings, generator
bearings, blade bearings and yaw bearings, are critical components for wind turbines to …
bearings, blade bearings and yaw bearings, are critical components for wind turbines to …
Recent advances and trends of predictive maintenance from data-driven machine prognostics perspective
In the Engineering discipline, prognostics play an essential role in improving system safety,
reliability and enabling predictive maintenance decision-making. Due to the adoption of …
reliability and enabling predictive maintenance decision-making. Due to the adoption of …
A survey of predictive maintenance: Systems, purposes and approaches
This paper provides a comprehensive literature review on Predictive Maintenance (PdM)
with emphasis on system architectures, purposes and approaches. In industry, any outages …
with emphasis on system architectures, purposes and approaches. In industry, any outages …
Multicellular LSTM-based deep learning model for aero-engine remaining useful life prediction
The prediction of aero-engine remaining useful life (RUL) is helpful for its operation and
maintenance. Aiming at the challenge that most neural networks (NNs), including long short …
maintenance. Aiming at the challenge that most neural networks (NNs), including long short …
Modified deep autoencoder driven by multisource parameters for fault transfer prognosis of aeroengine
The existing fault prognosis techniques of aeroengine mostly focus on a single monitoring
parameter under stable condition, and have low adaptability to new prognosis scenes. To …
parameter under stable condition, and have low adaptability to new prognosis scenes. To …
[HTML][HTML] Challenges and opportunities of AI-enabled monitoring, diagnosis & prognosis: A review
Abstract Prognostics and Health Management (PHM), including monitoring, diagnosis,
prognosis, and health management, occupies an increasingly important position in reducing …
prognosis, and health management, occupies an increasingly important position in reducing …
Model migration neural network for predicting battery aging trajectories
An accurate prediction of batteries' future degradation is a key solution to relief the users'
anxiety on battery lifespan and electric vehicles' driving range. Technical challenges arise …
anxiety on battery lifespan and electric vehicles' driving range. Technical challenges arise …
Transferable convolutional neural network based remaining useful life prediction of bearing under multiple failure behaviors
H Cheng, X Kong, G Chen, Q Wang, R Wang - Measurement, 2021 - Elsevier
Remaining useful life (RUL) prediction has been a hotspot topic, which is useful to avoid
unexpected breakdowns and improve reliability. Different bearing failure behaviors caused …
unexpected breakdowns and improve reliability. Different bearing failure behaviors caused …
Bayesian deep-learning for RUL prediction: An active learning perspective
Deep learning (DL) has been intensively exploited for remaining useful life (RUL) prediction
in the recent decade. Although with high precision and flexibility, DL methods need sufficient …
in the recent decade. Although with high precision and flexibility, DL methods need sufficient …