Transfer learning algorithms for bearing remaining useful life prediction: A comprehensive review from an industrial application perspective
Accurate remaining useful life (RUL) prediction for rolling bearings encounters many
challenges such as complex degradation processes, varying working conditions, and …
challenges such as complex degradation processes, varying working conditions, and …
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 …
Data-driven prognostic scheme for bearings based on a novel health indicator and gated recurrent unit network
The prognosis of bearings is vital for condition-based maintenance of rotating machinery.
This article proposes a systematic prognostic scheme for rolling element bearings. The …
This article proposes a systematic prognostic scheme for rolling element bearings. The …
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 …
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 …
A multi-stage semi-supervised learning approach for intelligent fault diagnosis of rolling bearing using data augmentation and metric learning
Limited condition monitoring data are recorded with label information in practice, which
make the fault identification task more challenging. A semi-supervised learning (SSL) …
make the fault identification task more challenging. A semi-supervised learning (SSL) …
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 …
Bearing remaining useful life prediction based on regression shapalet and graph neural network
Remaining useful life (RUL) prediction of bearing is essential to guarantee its safe
operation. In recent years, deep learning (DL)-based methods attract a lot of research …
operation. In recent years, deep learning (DL)-based methods attract a lot of research …
Gated dual attention unit neural networks for remaining useful life prediction of rolling bearings
In the mechatronic system, rolling bearing is a frequently used mechanical part, and its
failure may result in serious accident and major economic loss. Therefore, the remaining …
failure may result in serious accident and major economic loss. Therefore, the remaining …
Multitask learning based on lightweight 1DCNN for fault diagnosis of wheelset bearings
In recent years, deep learning has been proved to be a promising bearing fault diagnosis
technology. However, most of the existing methods are based on single-task learning. Fault …
technology. However, most of the existing methods are based on single-task learning. Fault …