Early Detection of Faults in Induction Motors II

Dear Colleagues,

Induction motors are a crucial element in many industry fields, in transportation, and in the service and utility sector. Although they are considered robust machines, they are also subject to failures that, if not detected in time, can lead to catastrophic breakdowns. This can lead to increased costs for companies, unplanned production stops, destruction of facilities, or service interruptions.

For these reasons, the interest of industry and academia in developing early detection systems to prevent these incipient failures from evolving into catastrophic ones has been renovated and boosted. Techniques for early fault detection would allow the implementation of predictive maintenance systems, which are an essential element of Industry 4.0.

Condition monitoring of induction motors has been traditionally based on the analysis of the stator current or motor vibrations. However, currently, new solutions based on the analysis of other signals, such as stray flux, sound, and speed, have been proposed.

This Special Issue has therefore a broad scope, though it is focused on the induction motor. Submitted works may deal with the early detection of any type of fault in motors working in stationary or transient regimes and line- or inverter-fed. Innovative papers related to advanced signal processing techniques, machine learning, artificial intelligence, big data, and sensors will be welcome.

Prof. Dr. Daniel Morinigo-Sotelo
Dr. Ignacio Martin-Diaz
Guest Editors

Manuscript Submission Information

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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. Energies 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.

• induction motors
• condition monitoring
• predictive maintenance
• fault detection and diagnosis
• early detection and diagnosis
• detection in transient regimes
• detection in steady-state regimes
• line- and inverter-fed motors
• signal processing for monitoring and diagnosis
• smart sensors for monitoring electric motors
• monitoring and diagnosis of electric motors in Industry 4.0

• Early Detection of Faults in Induction Motors in Energies (10 articles)