Sensors for Electric Machines Fault Diagnosis and Condition Monitoring

Dear Colleagues,

Electrical machines are key components in industrial and domestic applications. Nowadays, their vital role has increased due to the rising interest in electrical mobility, renewable energy, robots, unmanned aerial vehicles, etc. Therefore, condition monitoring and fault diagnosis is a crucial matter for these applications in order to prevent or minimize the impact of sudden failures.

The integration of condition monitoring systems in control and information systems, SCADA sytems and even Cloud Services must improve the reliability and the efficiency of the processes.

Additionally, in recent years, the integration of sensors monitoring different magnitudes to develop fault diagnosis and monitoring technologies of electrical machines has attracted increasing attention from both academia and industry.

The effective integration of distributed sensor networks in diagnostic systems is a challenging issue which requires expertise from a broad set of disciplines, such as artificial intelligence, adaptive observer design, statistical estimation, data dimension reduction techniques, etc. On the other hand, the acquired information can be stored, processed, and delivered using modern cloud-based software services and big-data technologies.

We invite researchers from both academia and industry to submit original and unpublished manuscripts to this Special Issue to showcase some of the recent developments within these topics.

The goal of the Special Issue is to publish the most recent research results and industrial applications in sensors for electric machine fault diagnosis and condition monitoring. Topics that are suitable for this Special Issue include, but are not limited to: 

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

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

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.