Sensors for Fault Diagnosis and Fault Tolerance Ⅱ
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Fault Diagnosis & Sensors".
Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 3247
Special Issue Editors
Interests: fault diagnosis of electrical machines; reduced order-modeling of electromagnetic devices; Industry 4.0
Special Issues, Collections and Topics in MDPI journals
Interests: fault diagnosis of electrical machines; control of electrical machines and drives
Special Issues, Collections and Topics in MDPI journals
Interests: induction motor fault diagnosis; numerical modeling of electrical machines; advanced automation processes and electrical installations
Special Issues, Collections and Topics in MDPI journals
Interests: induction motor fault diagnosis; numerical modeling of electrical machines; advanced automation processes and electrical installations
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Automation of industrial processes (smart factories, collaborative robots, Industry 4.0) and everyday life (smart buildings, automated driving) play an increasing role in the advancement of modern societies. Due to the complexity of automated installations, the prevention of safety hazards and huge production losses require the detection and identification of any kind of fault, as early as possible, and to minimize their impacts by implementing real-time fault detection (FD) and fault-tolerant (FT) operations systems. Therefore, FD and FT technologies have attracted an increasing amount of research and industrial attention in recent years. Modern FD and FT schemas demand high-volume, high-quality information from multiple types of sensor data, but sensors are also subject to failure, which must be included in the diagnostic systems. The integration of distributed sensor networks in model-based, signal-based, knowledge-based, and hybrid/active diagnostic systems is a challenging issue, which requires techniques from a broad set of disciplines, such as artificial intelligence, adaptive observers design, statistical estimation, data dimension reduction techniques, etc. Robust active and passive FT approaches that can tolerate discontinuities and errors in the flow of sensors data are needed to increase the reliability of automated systems. A particular, a growing trend in recent years has been the use of electric machines and electronic drives as a source of signals for FD/FT industrial systems, acting as sensors.
We invite academia and industry researchers to submit original and unpublished manuscripts to this Special Issue that develop research works related to these topics.
The goal of the Special Issue is to publish the most recent research results and industrial applications of sensors in FD and FT methods. Topics suited for this Special Issue include, but are not limited to:
- Data-driven and model-based sensor fault diagnosis.
- Self-healing, self-organizing, self-adaptive, automatic recovery of sensor networks.
- Integration of high-volume sensor data in the design of fault diagnosis and fault-tolerant control.
- Sensors in advanced FD/FT applications in different industrial sectors.
- Methods, concepts and performance assessment for improving FD/FT existing in industrial applications.
- Electrical drives as sensors in industrial processes.
- Sensors systems for fault tolerant electrical drives.
Prof. Dr. Manuel Pineda-Sanchez
Prof. Dr. Javier Martinez-Roman
Prof. Dr. Ruben Puche-Panadero
Prof. Dr. Angel Sapena-Bano
Guest Editors
Manuscript Submission Information
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Related Special Issue
- Sensors for Fault Diagnosis and Fault Tolerance in Sensors (13 articles)
