Sensor Developments in Fault Diagnosis and Fault-Tolerant Control

Dear Colleagues,

Condition monitoring and fault diagnosis electrical machines are a crucial matter because electrical machines are vital components to industrial and domestic applications. For example, in applications such as electrical mobility, renewable energy, robots, unmanned aerial vehicles, robots, and traditional processes, industrial processes are necessary to prevent or minimize the impact of sudden failures.

The aim of this Special Issue is to improve the reliability of electrical drives based on the integration of condition monitoring systems in the available control and/or information systems, increasing the efficiency of the processes. These systems help to prevent failures, and it also means that these systems can be managed better.

To effectively integrate condition monitoring systems in control and/or information systems, different expertise from a broad set of disciplines is required, such as artificial intelligence, adaptive observer design, statistical estimation, data dimension reduction techniques, etc. Moreover, the information needed can be stored, processed, and delivered using modern cloud-based software services and big data technologies or local traditional systems.

We invite researchers from both academia and industry to submit original and unpublished manuscripts to this Special Issue to showcase some of the recent developments within these topics.

Topics of interest for this Special Issue include, but are not limited to: 

• Condition fault diagnosis and fault-tolerant control of data-driven and model-based sensors;
• Condition monitoring and fault-tolerant control of high-volume sensor data from electrical drives;
• Electrical drives as sensors in industrial processes;
• Cloud-based software services for fault diagnosis and fault-tolerant control of electrical drives;
• Methods, concepts, and performance assessment for improving the fault diagnosis or the fault-tolerant control of existing techniques in the field of electrical machines;
• Sensors in advanced electrical machines—fault diagnosis and fault-tolerant control applications in different industrial sectors;
• Fault diagnosis and fault-tolerant control applications in electrical vehicles.

Prof. Dr. Ruben Puche-Panadero
Prof. Dr. van Khang Huynh
Prof. Dr. Javier Martinez-Roman
Prof. Dr. Jordi Burriel-Valencia
Prof. Dr. Angel Sapena-Bano
Guest Editors

Manuscript Submission Information

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