Digital twin-driven fault diagnosis method for composite faults by combining virtual and real data
The subsea production system is essential for the subsea production of oil and gas. Real-
time monitoring can ensure safe production. The subsea production control system is the …
time monitoring can ensure safe production. The subsea production control system is the …
Wasserstein GAN-based Digital Twin Inspired Model for Early Drift Fault Detection in Wireless Sensor Networks
In this Internet of Things (IoT) era, the number of devices capable of sensing their
surroundings is increasing day by day. Based on the data from these devices, numerous …
surroundings is increasing day by day. Based on the data from these devices, numerous …
A Blockchain-based data-driven fault-tolerant control system for smart factories in industry 4.0
Modern technologies and data-driven approaches have enabled fault-tolerant controllers in
Industry 4.0 smart factories to detect, identify, and mitigate anomalies in real-time with a high …
Industry 4.0 smart factories to detect, identify, and mitigate anomalies in real-time with a high …
[HTML][HTML] In situ virtual sensors in building digital twins: framework and methodology
A novel sensing system is essential for intelligent building operations and digitalization of
the building life cycle. Therefore, this study introduces the concept and framework of in situ …
the building life cycle. Therefore, this study introduces the concept and framework of in situ …
Deep Recurrent Graph Convolutional Architecture for Sensor Fault Detection, Isolation and Accommodation in Digital Twins
The rapid adoption of Internet-of-Things (IoT) and digital twins (DTs) technologies within
industrial environments has highlighted diverse critical issues related to safety and security …
industrial environments has highlighted diverse critical issues related to safety and security …
IDS-KG: An industrial dataspace-based knowledge graph construction approach for smart maintenance
With the development of information technology in manufacturing enterprises, a large
amount of equipment maintenance data and knowledge are recorded. These rich …
amount of equipment maintenance data and knowledge are recorded. These rich …
Practical Methods of Defective Input Feature Correction to Enable Machine Learning in Power Systems
J Liu, F Li, F Zelaya-Arrazabal… - … on Power Systems, 2023 - ieeexplore.ieee.org
In this research work, three practical correction methods are proposed to mitigate the impact
of defective input features in power system data measurement for machine learning (ML) …
of defective input features in power system data measurement for machine learning (ML) …
Optical fiber gas sensor with multi-parameter sensing and environmental anti-interference performance
G Chen, J Li, H Zhu, Y Wang, H Ji, F Meng - Journal of Industrial …, 2024 - Elsevier
Formic acid finds widespread applications in numerous fields, including the petrochemicals
production, rubber industry, and leather tanning process, in which the operational …
production, rubber industry, and leather tanning process, in which the operational …
Review on Fault Diagnosis and Fault-Tolerant Control Scheme for Robotic Manipulators: Recent Advances in AI, Machine Learning, and Digital Twin
This comprehensive review article delves into the intricate realm of fault-tolerant control
(FTC) schemes tailored for robotic manipulators. Our exploration spans the historical …
(FTC) schemes tailored for robotic manipulators. Our exploration spans the historical …
Fault detection and isolation for dynamic non-stationary processes with stationary subspace-based canonical variate analysis
H Ji, N Sheng, H Liu, K Huang - Chemical Engineering Science, 2024 - Elsevier
As modern science and technology advance, industrial processes have grown more
complex, characterized by dynamic and non-stationary features. Existing methods often …
complex, characterized by dynamic and non-stationary features. Existing methods often …