A rolling bearing fault evolution state indicator based on deep learning and its application
X Liu, G Chen, X Wei, Y Liu, H Wang - Journal of Mechanical Science and …, 2023 - Springer
Aiming at the limitation of early fault warning and the diagnosis of aero-engine main bearing
when there are only normal operation data, a rolling bearing fault evolution state indicator …
when there are only normal operation data, a rolling bearing fault evolution state indicator …
Research on Data-Driven Methodologies for Expressway Emergency Rescue Point Location
X Hu, Z Wang, J Zhao, R Wang, H Lei… - Transportation …, 2024 - journals.sagepub.com
The rapid expansion of expressway networks has highlighted the irregular distribution of
traffic flow in both spatial and temporal dimensions; there is an escalating demand for more …
traffic flow in both spatial and temporal dimensions; there is an escalating demand for more …
A lightweight complex-domain acoustic feature extraction method for rotating machinery fault detection
X Wei, L Ding, D Wang, L Ma… - … Science and Technology, 2024 - iopscience.iop.org
In the field of fault diagnosis for factory machinery systems, the development of deep
learning methods has been hindered by the challenge of acquiring fault data, highlighting …
learning methods has been hindered by the challenge of acquiring fault data, highlighting …
Feature selection and interpretability analysis of compound faults in rolling bearings based on the causal feature weighted network
C Yu, M Li, W Zongning, K Gao… - … Science and Technology, 2024 - iopscience.iop.org
Feature selection is a crucial step in fault diagnosis. When rolling bearings are susceptible
to compound faults, causal relationships are hidden within the signal features. Complex …
to compound faults, causal relationships are hidden within the signal features. Complex …
[CITACE][C] Special features on continuous learning based condition monitoring for crucial components
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