Advances in Fault Diagnosis and Predictive Maintenance of Electrical Machines
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Electrical Machines and Drives".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 21
Special Issue Editors
Interests: modeling; condition monitoring and design of electrical machines
Interests: modeling; condition monitoring; design of electrical machines
Special Issues, Collections and Topics in MDPI journals
Interests: signal processing; artificial intelligence; condition monitoring of electrical machines
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Electrical machines are at the core of countless industrial, automotive, and energy applications, where their uninterrupted performance is critical. As these systems operate under increasingly demanding conditions, the need for reliable fault diagnosis and predictive maintenance has become paramount. This Special Issue aims to present the latest advances in analytical, signal processing, data-driven, and hybrid techniques for detecting and diagnosing faults in electrical machines. We invite the submission of original research and review papers that explore innovations in condition monitoring, machine learning approaches, sensor integration, digital twin technology, and real-time diagnostic systems. The goal is to provide a comprehensive platform for academics and industry professionals to exchange ideas that improve machine reliability, reduce downtime, and enhance system efficiency across diverse applications.
Dr. Bilal Asad
Dr. Muhammad Usman Naseer
Dr. Toomas Vaimann
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 100 words) can be sent to the Editorial Office for announcement on this website.
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. Machines is an international peer-reviewed open access monthly 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 2400 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.
Keywords
- condition monitoring
- data-driven techniques
- digital twin
- electrical machines
- fault detection
- fault diagnosis
- hybrid models
- industrial applications
- machine learning
- motor faults
- predictive maintenance
- real-time monitoring
- sensor-based diagnostics
- signal processing
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