Challenges and opportunities of AI-enabled monitoring, diagnosis & prognosis: A review

Z Zhao, J Wu, T Li, C Sun, R Yan, X Chen - Chinese Journal of Mechanical …, 2021 - Springer
Abstract Prognostics and Health Management (PHM), including monitoring, diagnosis,
prognosis, and health management, occupies an increasingly important position in reducing …

Enhanced transfer learning method for rolling bearing fault diagnosis based on linear superposition network

C Huo, Q Jiang, Y Shen, Q Zhu, Q Zhang - Engineering Applications of …, 2023 - Elsevier
Deep transfer learning is used to solve the problem of unsupervised intelligent fault
diagnosis of rolling bearings. However, when the data distribution between two domains is …

Intelligent fault diagnosis for planetary gearbox using transferable deep q network under variable conditions with small training data

H Wang, J Xu, R Yan - Journal of dynamics, monitoring and …, 2023 - ojs.istp-press.com
Effective fault diagnosis of planetary gearboxes is critical for ensuring the safety and
dependability of mechanical drive systems. Nevertheless, variable conditions and …

Balanced adaptation regularization based transfer learning for unsupervised cross-domain fault diagnosis

Q Hu, X Si, A Qin, Y Lv, M Liu - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
In fault diagnosis field, inconsistent distribution between training and testing data, resulted
from variable working conditions of rotating machinery, inevitably leads to degradation of …

New transfer learning fault diagnosis method of rolling bearing based on ADC-CNN and LATL under variable conditions

C Huo, Q Jiang, Y Shen, C Qian, Q Zhang - Measurement, 2022 - Elsevier
Convolutional neural network with transfer learning are effective methods for rolling bearing
unsupervised learning fault diagnosis. In view of the problem that 1D-CNN cannot give full …

Using data from similar systems for data-driven condition diagnosis and prognosis of engineering systems: A review and an outline of future research challenges

M Braig, P Zeiler - IEEE Access, 2022 - ieeexplore.ieee.org
Prognostics and health management (PHM) is an engineering approach dealing with the
diagnosis, prognosis, and management of the health state of engineering systems. Methods …

Deep residual joint transfer strategy for cross-condition fault diagnosis of rolling bearings

S Han, Z Feng - Journal of Dynamics, Monitoring and …, 2023 - ojs.istp-press.com
Rolling bearings are key components of the drivetrain in wind turbines, and their health is
critical to wind turbine operation. In practical diagnosis tasks, the vibration signal is usually …

A class-level matching unsupervised transfer learning network for rolling bearing fault diagnosis under various working conditions

C Huo, Q Jiang, Y Shen, X Lin, Q Zhu, Q Zhang - Applied Soft Computing, 2023 - Elsevier
As an effective method, deep transfer learning is used to solve the problem of unsupervised
fault diagnosis of rolling bearings. In the process of obtaining domain invariant features, the …

Bearing fault diagnosis using normalized diagnostic feature-gram and convolutional neural network

JK Alsalaet, A Hajnayeb… - Measurement Science and …, 2023 - iopscience.iop.org
Accurate fault diagnosis is vital for modern maintenance strategies to improve machinery
reliability and efficiency. Automated predictive tools, such as deep learning, are gaining …

A comparative experimental research on the diagnosis of tooth root cracks in asymmetric spur gear pairs with a one-dimensional convolutional neural network

OC Kalay, F Karpat - Mechanism and Machine Theory, 2024 - Elsevier
Gearboxes transfer rotational motion and handle precision functionalities in many fields,
including aviation, wind turbines, and industrial services. Their health management is …