Nonlinear Model-Based Fault Detection for Industrial Applications
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Fault Diagnosis & Sensors".
Deadline for manuscript submissions: closed (10 May 2023) | Viewed by 3336
Special Issue Editors
Interests: fault detection; fault tolerant control; wind turbines
Special Issues, Collections and Topics in MDPI journals
Interests: system identification and data analysis; artificial intelligence; neural networks; fuzzy systems; fault diagnosis; fault tolerant control; aircraft and spacecraft systems; energy conversion systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Motivated by the need for reliable and safe modern industrial systems, Fault Detection and Isolation (FDI) schemes are the most sought-after solutions in the last two decades. FDI schemes can help with timely detection, identification, and isolation of any faults. Then, corresponding corrective measures can be taken. Moreover, FDI information can be used to optimize the maintenance procedures and reduce the operational cost.
As a standard definition, deviation from the normal or standard condition of any parameter of the system can be translated as a fault, categorized as actuator faults, sensor faults, and plant faults. The concept of redundancy is often used to construct FDI schemes, amongst these, the model-based FDI has received a great deal of attention, since it can be specifically designed for the system of interest and the fault could be directly detected and isolated. Moreover, it resolves the problems associated with hardware redundancy approaches.
However, model-based FDI approaches have been mostly designed for the simple or linearized model of systems. This also requires the accurate knowledge of system dynamics. Moreover, the inevitable sources of unknown nonlinearities, model uncertainties, exogenous disturbances, and inadequate measurable outputs make the FDI design for industrial systems challenging.
This motivates the aim of this Special Issue of Sensors. Accordingly, I cordially invite researchers to contribute original and unique articles, as well as review papers. The topics of interest include (with emphasis on practical industrial systems), but are not limited to:
- Condition monitoring;
- Fault detection and isolation;
- Data-driven approaches including machine learning methods;
- Fault detection and diagnosis;
- Incipient faults;
- Industrial systems;
- Model-based approaches;
- Nonlinear models;
- Observer design;
- Unknown inputs.
Dr. Hamed Habibi
Dr. Silvio Simani
Guest Editors
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