Real-time Monitoring, Diagnosis, Prognosis and Tolerant Control for Industrial Systems

Special Session Organized by

Zhiwei Gao, University of Northumbria, Newcastle, UK and  Lina Yao, Zhengzhou University, China

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Industrial systems, such as aero engine, power network, chemical automation process, wind turbine systems, and so forth, are safety-critical systems. Therefore, there is an ever-increasing demand to provide a high-level system reliability and safety for practical engineering systems by implementing real-time monitoring, fault diagnosis, prognosis and fault tolerant control and health management. This special session aims to provide a platform for the researchers and participants from both academic community and industrial sectors to report recent research and application progress in the field of condition monitoring, fault diagnosis, fault prognosis, fault tolerant control and their applications

Topics under this session include (but not limited to)

  • Machine-learning based monitoring and fault diagnosis
  • Signal-based monitoring and fault diagnosis
  • Model-based monitoring and fault diagnosis
  • Prognosis methods and remaining use life prediction
  • Digital-twin based fault diagnosis and prognosis
  • Resilience of safety-critical systems
  • Health monitoring and management for industrial systems
  • Real-time implementation of diagnosis, prognosis and tolerant control in engineering applications