R Wang, W Huang, Y Lu, J Wang, C Ding… - Expert Systems with …, 2024 - Elsevier
The data-driven fault diagnostic methods have made significant advances and breakthroughs in the past decades. However, due to the huge time and labor costs, single …
Y Wang, J Yan, Z Yang, Y Dai, J Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Deep learning-driven diagnostic methods have shown significant ability to diagnose certain types of insulation defects. However, for these methods to achieve excellent results, it is …
X Chen, X Chen, H Wang, S Lu, R Yan - Manufacturing Letters, 2023 - Elsevier
Remaining useful life (RUL) prediction has achieved considerable success through centralized learning methods. However, traditional data aggregation may cause privacy …
TA Chen, SC Chen, W Tang, BT Chen - Sensors, 2022 - mdpi.com
The Internet of Things (IoT) has become critical to the implementation of Industry 4.0. The successful operation of smart manufacturing depends on the ability to connect everything …
Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition …
SHM Rizvi, M Abbas - Engineering Research Express, 2023 - iopscience.iop.org
Owing to recent advancements in sensor technology, data mining, Machine Learning (ML) and cloud computation, Structural Health Monitoring (SHM) based on a data-driven …
S Sun, H Huang, T Peng… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The continuous operation of the equipment degrades the performance of the critical parts, which can cause the equipment to fail and stop at a particular and unexpected moment …
B Li, P Song, C Zhao - Information Fusion, 2024 - Elsevier
Recently, federated fault diagnosis has garnered growing attention due to its promising capabilities in information fusion with privacy preservation. However, most of the existing …
Cross-domain fault diagnosis methods have been successfully and widely developed in the past years, which focus on practical industrial scenarios with training and testing data from …