[PDF][PDF] 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 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 …
Bearing fault diagnosis based on vibro-acoustic data fusion and 1D-CNN network
X Wang, D Mao, X Li - Measurement, 2021 - Elsevier
Bearing fault diagnosis is an important part of rotating machinery maintenance. Existing
diagnosis methods based on single-modal signals not only have unsatisfactory accuracy …
diagnosis methods based on single-modal signals not only have unsatisfactory accuracy …
Intelligent fault diagnosis of rotating machinery based on continuous wavelet transform-local binary convolutional neural network
This paper presents a data-driven intelligent fault diagnosis approach for rotating machinery
(RM) based on a novel continuous wavelet transform-local binary convolutional neural …
(RM) based on a novel continuous wavelet transform-local binary convolutional neural …
Intelligent fault diagnosis of hydraulic piston pump based on deep learning and Bayesian optimization
S Tang, Y Zhu, S Yuan - ISA transactions, 2022 - Elsevier
Hydraulic axial piston pump is broadly-used in aerospace, ocean engineering and
construction machinery since it is the vital component of fluid power systems. In the light of …
construction machinery since it is the vital component of fluid power systems. In the light of …
Deep learning for smart manufacturing: Methods and applications
Smart manufacturing refers to using advanced data analytics to complement physical
science for improving system performance and decision making. With the widespread …
science for improving system performance and decision making. With the widespread …
A review on the application of deep learning in system health management
Given the advancements in modern technological capabilities, having an integrated health
management and diagnostic strategy becomes an important part of a system's operational …
management and diagnostic strategy becomes an important part of a system's operational …
Multiscale convolutional neural networks for fault diagnosis of wind turbine gearbox
This paper proposes a novel intelligent fault diagnosis method to automatically identify
different health conditions of wind turbine (WT) gearbox. Unlike traditional approaches …
different health conditions of wind turbine (WT) gearbox. Unlike traditional approaches …
Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks
Gearbox fault diagnosis is expected to significantly improve the reliability, safety and
efficiency of power transmission systems. However, planetary gearbox fault diagnosis …
efficiency of power transmission systems. However, planetary gearbox fault diagnosis …
Understanding and learning discriminant features based on multiattention 1DCNN for wheelset bearing fault diagnosis
Recently, deep-learning-based fault diagnosis methods have been widely studied for rolling
bearings. However, these neural networks are lack of interpretability for fault diagnosis …
bearings. However, these neural networks are lack of interpretability for fault diagnosis …