Novel joint transfer network for unsupervised bearing fault diagnosis from simulation domain to experimental domain
Unsupervised cross-domain fault diagnosis of bearings has practical significance; however,
the existing studies still face some problems. For example, transfer diagnosis scenarios are …
the existing studies still face some problems. For example, transfer diagnosis scenarios are …
Development of deep reinforcement learning-based fault diagnosis method for rotating machinery in nuclear power plants
G Qian, J Liu - Progress in Nuclear Energy, 2022 - Elsevier
Rotating machinery fault can cause accidents like loss of flow or turbine trip that seriously
threaten the operation safety of nuclear power plants (NPPs). Artificial intelligence …
threaten the operation safety of nuclear power plants (NPPs). Artificial intelligence …
Modified stacked autoencoder using adaptive Morlet wavelet for intelligent fault diagnosis of rotating machinery
Intelligent fault diagnosis techniques play an important role in improving the abilities of
automated monitoring, inference, and decision making for the repair and maintenance of …
automated monitoring, inference, and decision making for the repair and maintenance of …
Fault detection in gears using fault samples enlarged by a combination of numerical simulation and a generative adversarial network
Y Gao, X Liu, J Xiang - IEEE/ASME Transactions on …, 2021 - ieeexplore.ieee.org
It is inevitable for gear to become damaged, which has a profound effect on the performance
of gear transmission systems. Solving the problem of gear fault detection using artificial …
of gear transmission systems. Solving the problem of gear fault detection using artificial …
State of AI-based monitoring in smart manufacturing and introduction to focused section
H Ding, RX Gao, AJ Isaksson… - IEEE/ASME …, 2020 - ieeexplore.ieee.org
Over the past few decades, intelligentization, supported by artificial intelligence (AI)
technologies, has become an important trend for industrial manufacturing, accelerating the …
technologies, has become an important trend for industrial manufacturing, accelerating the …
Novel fractional-order convolutional neural network based chatter diagnosis approach in turning process with chaos error mapping
The chatter not only brings about poor surface quality of the workpiece but also causes the
tool wear and then leads to the increase in production cost over time. For this reason, it …
tool wear and then leads to the increase in production cost over time. For this reason, it …
Intelligent fault diagnosis for planetary gearbox using time-frequency representation and deep reinforcement learning
Accurately and intelligently identifying faults of the planetary gearbox is essential in the safe
and reliable operation and maintenance of the mechanical drive system. Recently, fault …
and reliable operation and maintenance of the mechanical drive system. Recently, fault …
FedRUL: A new federated learning method for edge-cloud collaboration based remaining useful life prediction of machines
L Guo, Y Yu, M Qian, R Zhang, H Gao… - … ASME Transactions on …, 2022 - ieeexplore.ieee.org
In real industrial applications, intelligent methods are recently emerging for remaining useful
life (RUL) prediction. However, their development is hindered by two obstacles. First, it is …
life (RUL) prediction. However, their development is hindered by two obstacles. First, it is …
Manufacturing process monitoring using time-frequency representation and transfer learning of deep neural networks
On-line process monitoring increases product quality, improves process stability, and lowers
costs in manufacturing. This paper presents a study of using time-frequency representation …
costs in manufacturing. This paper presents a study of using time-frequency representation …
Feature extraction of multi-sensors for early bearing fault diagnosis using deep learning based on minimum unscented kalman filter
H Tang, Y Tang, Y Su, W Feng, B Wang, P Chen… - … Applications of Artificial …, 2024 - Elsevier
Bearing fault diagnosis is vital for ensuring reliability and safety of high-speed trains and
wind turbines. Therefore, a minimum unscented Kalman filter-aided deep belief network is …
wind turbines. Therefore, a minimum unscented Kalman filter-aided deep belief network is …