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Incipient Fault Detection and Diagnosis, Fault-Tolerant Control
This special issue belongs to the section “F: Electrical Engineering“.
Special Issue Information
Dear Colleagues,
Of all the current issues in industry, safety, reliability and availability are clearly at the forefront. One way to meet the ever-increasing constraints is to implement Condition-Based Maintenance (CBM). As a result, CBM is drawing huge attention from both industry and academia. The implementation of CBM requires efficient health monitoring and fault-tolerance strategies.
Currently, particular attention is paid to incipient fault—meaning the fault level is in the same range as the nuisances. Indeed, incipient fault—if not detected at its earliest stage—may increase gradually and silently and finally leads to catastrophic failures.
Health monitoring includes fault detection, fault isolation and fault estimation. It can be based on modelling (physics-based or data driven), or information processing, to retrieve and analyse the most relevant features, to make the most reliable and accurate decision regarding the health status of the process under study.
Once the fault has been diagnosed and the alarm sent, the fault-tolerant strategy is engaged to mitigate the fault occurrence, in order to avoid any unpredicted and unwanted stoppages. This can be done with the same level of performances, as long as it is sustainable or with degraded performances. The fault-tolerance strategy is mainly based on the application of theoretical tools from control and information processing.
Therefore, this Special Issue has a wide potential audience, including both practitioners and academics working in different areas (energy, transportation, etc…).
We invite them all to contribute to this Special Issue and share their valuable experience.
Prof. Dr. Demba Diallo
Prof. Antonio J. MARQUES CARDOSO
Dr. Claude DELPHA
Guest Editors
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Keywords
- incipient fault
- fault detection and diagnosis
- fault tolerant control
- Condition-based Maintenance
- modelling
- data, signal and information processing
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