Fault diagnosis with bidirectional guided convolutional neural networks under noisy labels
In recent years, supervised deep learning methods have proven to be feasible and
advanced for fault diagnosis. They do, however, rely on large amounts of accurately labeled …
advanced for fault diagnosis. They do, however, rely on large amounts of accurately labeled …
A semisupervised method with swarm intelligence optimization for intelligent fault diagnosis
Z Xu, Z Feng, Q Wu, S Yang - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
With the recent development of deep learning, machine-learning-based methods have
gained promising achievements for fault diagnosis. However, most of these methods are …
gained promising achievements for fault diagnosis. However, most of these methods are …
A novel abnormal data detection method based on dynamic adaptive local outlier factor for the vibration signals of rotating parts
H Wang, S Yang, Y Liu, Q Li - Measurement Science and …, 2023 - iopscience.iop.org
Abnormal signals are inevitable in big data acquired from harsh industrial environments.
Abnormal data detection is a crucial component of condition monitoring for rotating parts and …
Abnormal data detection is a crucial component of condition monitoring for rotating parts and …
[HTML][HTML] Self-Supervised Health Index Curve Generation for Condition-Based Predictive Maintenance
Modern machine degradation trend evaluation relies on the unsupervised model-based
estimation of a health index (HI) from asset measurement data. This minimizes the need for …
estimation of a health index (HI) from asset measurement data. This minimizes the need for …
An active federated method driven by inter-client informativeness variability of labeled data
F Zhou, C Wang, X Hu, C Wang, T Wang - Signal, Image and Video …, 2023 - Springer
Federated learning does well in jointly training multiple deep learning models for fault
diagnosis. The accuracy of local model may affect the effectiveness of federated learning. In …
diagnosis. The accuracy of local model may affect the effectiveness of federated learning. In …
Deep-learning-based information fusion methodology for oil film coefficient identification of squeeze film dampers
W Zhang, J Zhang, X Li - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Squeeze film damper (SFD) is one of the key components in the sophisticated rotating
machines in the high-end aerospace industry. Rolling bearings in the aeroengine spindle …
machines in the high-end aerospace industry. Rolling bearings in the aeroengine spindle …
Fault Diagnosis and Prognostics of Stochastic Distribution Systems
Y Gao, L Yao, YC Sun - … Transactions on Circuits and Systems II …, 2024 - ieeexplore.ieee.org
A novel fusion method is proposed for fault diagnosis and prognosis in nonlinear stochastic
distribution control systems. Technically, a mapping relationship between fault increments …
distribution control systems. Technically, a mapping relationship between fault increments …