Deep learning techniques in intelligent fault diagnosis and prognosis for industrial systems: a review
S Qiu, X Cui, Z Ping, N Shan, Z Li, X Bao, X Xu - Sensors, 2023 - mdpi.com
Fault diagnosis and prognosis (FDP) tries to recognize and locate the faults from the
captured sensory data, and also predict their failures in advance, which can greatly help to …
captured sensory data, and also predict their failures in advance, which can greatly help to …
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 …
Intelligent diagnosis using continuous wavelet transform and gauss convolutional deep belief network
H Zhao, J Liu, H Chen, J Chen, Y Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Bearing fault diagnosis is of significance to ensure the safe and reliable operation of a
motor. Deep learning provides a powerful ability to extract the features of raw data …
motor. Deep learning provides a powerful ability to extract the features of raw data …
Dual-threshold attention-guided GAN and limited infrared thermal images for rotating machinery fault diagnosis under speed fluctuation
End-to-end intelligent diagnosis of rotating machinery under speed fluctuation and limited
samples is challenging in industrial practice. The existing limited samples methods usually …
samples is challenging in industrial practice. The existing limited samples methods usually …
Feature extraction using parameterized multisynchrosqueezing transform
X Li, H Zhao, L Yu, H Chen, W Deng… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
Parametrized time-frequency analysis (PTFA) can effectively improve time-frequency energy
aggregation of non-stationary signal and immunity of cross term interference, but it exists the …
aggregation of non-stationary signal and immunity of cross term interference, but it exists the …
Ventilation diagnosis of minigrinders using thermal images
A Glowacz - Expert Systems with Applications, 2024 - Elsevier
A technique of analysis of thermal images of minigrinders is presented in the paper. The
following states of minigrinders were analyzed: healthy minigrinder (HM), minigrinder with 2 …
following states of minigrinders were analyzed: healthy minigrinder (HM), minigrinder with 2 …
Multiscale deep graph convolutional networks for intelligent fault diagnosis of rotor-bearing system under fluctuating working conditions
The rotor-bearing system is widely used in various high-end electro-hydraulic equipment,
which provides specific support, rotation, and other integral functions. However, the …
which provides specific support, rotation, and other integral functions. However, the …
Deep continual transfer learning with dynamic weight aggregation for fault diagnosis of industrial streaming data under varying working conditions
Catastrophic forgetting of learned knowledges and distribution discrepancy of different data
are two key problems within fault diagnosis fields of rotating machinery. However, existing …
are two key problems within fault diagnosis fields of rotating machinery. However, existing …
Intelligent fault diagnosis of bevel gearboxes using semi-supervised probability support matrix machine and infrared imaging
Fault diagnosis is of great significance to ensure the reliability and safety of complex bevel
gearbox systems. Most existing intelligent fault diagnosis approaches of bevel gearboxes …
gearbox systems. Most existing intelligent fault diagnosis approaches of bevel gearboxes …
Vibration and infrared thermography based multiple fault diagnosis of bearing using deep learning
The occurrence of multiple faults is a practical problem in the bearings of rotating machines,
and early diagnosis of such issues in an intelligent manner is vital in the era of industry 4.0 …
and early diagnosis of such issues in an intelligent manner is vital in the era of industry 4.0 …