Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach: A review of two decades of research

S Gawde, S Patil, S Kumar, P Kamat, K Kotecha… - … Applications of Artificial …, 2023 - Elsevier
Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of
machinery. The majority of these machines comprise rotating components and are called …

A scoping review on multi-fault diagnosis of industrial rotating machines using multi-sensor data fusion

S Gawde, S Patil, S Kumar, K Kotecha - Artificial Intelligence Review, 2023 - Springer
Rotating machines is an essential part of any manufacturing industry. The sudden
breakdown of such machines due to improper maintenance can also lead to the industries' …

The emerging graph neural networks for intelligent fault diagnostics and prognostics: A guideline and a benchmark study

T Li, Z Zhou, S Li, C Sun, R Yan, X Chen - Mechanical Systems and Signal …, 2022 - Elsevier
Deep learning (DL)-based methods have advanced the field of Prognostics and Health
Management (PHM) in recent years, because of their powerful feature representation ability …

Bayesian transfer learning with active querying for intelligent cross-machine fault prognosis under limited data

R Zhu, W Peng, D Wang, CG Huang - Mechanical Systems and Signal …, 2023 - Elsevier
Most existing deep learning (DL)-based health prognostic methods assume that the training
and testing datasets are from identical machines operating under similar conditions …

Bayesian deep-learning for RUL prediction: An active learning perspective

R Zhu, Y Chen, W Peng, ZS Ye - Reliability Engineering & System Safety, 2022 - Elsevier
Deep learning (DL) has been intensively exploited for remaining useful life (RUL) prediction
in the recent decade. Although with high precision and flexibility, DL methods need sufficient …

[HTML][HTML] Intelligent manufacturing for the process industry driven by industrial artificial intelligence

T Yang, X Yi, S Lu, KH Johansson, T Chai - Engineering, 2021 - Elsevier
Based on the analysis of the characteristics and operation status of the process industry, as
well as the development of the global intelligent manufacturing industry, a new mode of …

Novel fractional-order convolutional neural network based chatter diagnosis approach in turning process with chaos error mapping

PH Kuo, YR Tseng, PC Luan, HT Yau - Nonlinear Dynamics, 2023 - Springer
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 …

A fuzzy logic-based approach for fault diagnosis and condition monitoring of industry 4.0 manufacturing processes

M Mazzoleni, K Sarda, A Acernese, L Russo… - … Applications of Artificial …, 2022 - Elsevier
Since the introduction of the industry 4.0 paradigm, manufacturing companies are investing
in the development of algorithmic diagnostic solutions for their industrial equipment, relying …

Industrial‐generative pre‐trained transformer for intelligent manufacturing systems

H Wang, M Liu, W Shen - IET Collaborative Intelligent …, 2023 - Wiley Online Library
Manufacturing enterprises are facing how to utilise industrial knowledge and continuously
accumulating massive unlabelled data to achieve human‐cyber‐physical collaborative and …

Deep reinforcement learning-based online domain adaptation method for fault diagnosis of rotating machinery

G Li, J Wu, C Deng, X Xu, X Shao - IEEE/ASME Transactions on …, 2021 - ieeexplore.ieee.org
Deep-learning-based methods have been successfully applied to fault diagnosis of rotating
machinery. However, the domain mismatch among different operating conditions …