Fault diagnosis and self-healing for smart manufacturing: a review
Manufacturing systems are becoming more sophisticated and expensive, particularly with
the development of the intelligent industry. The complexity of the architecture and concept of …
the development of the intelligent industry. The complexity of the architecture and concept of …
Intelligent condition monitoring of industrial plants: An overview of methodologies and uncertainty management strategies
Condition monitoring plays a significant role in the safety and reliability of modern industrial
systems. Artificial intelligence (AI) approaches are gaining attention from academia and …
systems. Artificial intelligence (AI) approaches are gaining attention from academia and …
Profitability related industrial-scale batch processes monitoring via deep learning based soft sensor development
Data-driven soft sensor technology has been widely developed to estimate quality-related
variables, while following difficulties still limit its application in batch processes, such as …
variables, while following difficulties still limit its application in batch processes, such as …
[HTML][HTML] Design and implementation of an autonomous systems training environment framework for control algorithm evaluation in autonomous plant operation
The shortage of trained plant operators who can control complex systems in the process and
energy industry is leading to an increasing need for more autonomy of such plants. In future …
energy industry is leading to an increasing need for more autonomy of such plants. In future …
Root cause localization for wind turbines using physics guided multivariate graphical modeling and fault propagation analysis
C Feng, C Liu, D Jiang - Knowledge-Based Systems, 2024 - Elsevier
Under the background of widespread utilization of wind energy, the improvement of power
generation efficiency and the reduction of operation and maintenance costs have increased …
generation efficiency and the reduction of operation and maintenance costs have increased …
[PDF][PDF] Multi-source domain adaptation for cross-domain fault diagnosis of chemical processes
Fault diagnosis is an essential component in process supervision. Indeed, it determines
which kind of fault has occurred, given that it has been previously detected, allowing for …
which kind of fault has occurred, given that it has been previously detected, allowing for …
FPGA-Flux Proprietary System for Online Detection of Outer Race Faults in Bearings
Online fault detection in industrial machinery, such as induction motors or their components
(eg, bearings), continues to be a priority. Most commercial equipment provides general …
(eg, bearings), continues to be a priority. Most commercial equipment provides general …
The arc loss challenge: A novel industrial benchmark for process analytics and machine learning
Rapid development in data-driven process monitoring has provided a rich selection of
models and data preprocessing strategies for applications such as fault detection and …
models and data preprocessing strategies for applications such as fault detection and …
Data-Driven Process Monitoring and Fault Diagnosis: A Comprehensive Survey
This paper presents a comprehensive review of the historical development, the current state
of the art, and prospects of data-driven approaches for industrial process monitoring. The …
of the art, and prospects of data-driven approaches for industrial process monitoring. The …
Distance matrix patterns for visual and interpretable process data analytics
A novel methodology for visual process data analytics based on distance matrices is
proposed. A distance matrix is a two-dimensional representation that reflects intrinsic data …
proposed. A distance matrix is a two-dimensional representation that reflects intrinsic data …