Deep transfer learning for bearing fault diagnosis: A systematic review since 2016
The traditional deep learning-based bearing fault diagnosis approaches assume that the
training and test data follow the same distribution. This assumption, however, is not always …
training and test data follow the same distribution. This assumption, however, is not always …
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 novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings
Remaining useful life (RUL) prediction has been a hotspot in the engineering field, which is
useful to avoid unexpected breakdowns and reduce maintenance costs of the system. Due …
useful to avoid unexpected breakdowns and reduce maintenance costs of the system. Due …
Meta-learning as a promising approach for few-shot cross-domain fault diagnosis: Algorithms, applications, and prospects
Y Feng, J Chen, J **e, T Zhang, H Lv, T Pan - Knowledge-Based Systems, 2022 - Elsevier
The advances of intelligent fault diagnosis in recent years show that deep learning has
strong capability of automatic feature extraction and accurate identification for fault signals …
strong capability of automatic feature extraction and accurate identification for fault signals …
A hybrid prognostics approach for estimating remaining useful life of rolling element bearings
Remaining useful life (RUL) prediction of rolling element bearings plays a pivotal role in
reducing costly unplanned maintenance and increasing the reliability, availability, and safety …
reducing costly unplanned maintenance and increasing the reliability, availability, and safety …
Deep learning algorithms for rotating machinery intelligent diagnosis: An open source benchmark study
Rotating machinery intelligent diagnosis based on deep learning (DL) has gone through
tremendous progress, which can help reduce costly breakdowns. However, different …
tremendous progress, which can help reduce costly breakdowns. However, different …
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 …
Deep learning algorithms for bearing fault diagnostics—A comprehensive review
In this survey paper, we systematically summarize existing literature on bearing fault
diagnostics with deep learning (DL) algorithms. While conventional machine learning (ML) …
diagnostics with deep learning (DL) algorithms. While conventional machine learning (ML) …
Bearing fault detection and diagnosis using case western reserve university dataset with deep learning approaches: A review
A smart factory is a highly digitized and connected production facility that relies on smart
manufacturing. Additionally, artificial intelligence is the core technology of smart factories …
manufacturing. Additionally, artificial intelligence is the core technology of smart factories …
Remaining useful life prediction with partial sensor malfunctions using deep adversarial networks
In recent years, intelligent data-driven prognostic methods have been successfully
developed, and good machinery health assessment performance has been achieved …
developed, and good machinery health assessment performance has been achieved …