Towards Electric Motors and Drives: Condition Monitoring, Performance Prediction and Fault Diagnosis
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Electrical Machines and Drives".
Deadline for manuscript submissions: 1 July 2024 | Viewed by 140
Special Issue Editors
Interests: mechanical fault diagnosis; deep learning; signal processing
Special Issue Information
Dear Colleagues,
Electric motors and drives are important power systems for modern industrial equipment. Facilitated by novel design concepts and advancements in new technologies such as sensing, manufacturing, communication, management, and systems integrity, electric motors and drives have become more sophisticated than ever, making performance prediction and fault diagnosis a challenging problem to ensure reliable operations. However, accurate and timely performance prediction and fault diagnosis are difficult due to the following factors: (i) performance prediction and fault diagnosis is a coupled subject involving modeling analysis, sensing and monitoring, signal processing, and decision making; (ii) it relies on a comprehensive understanding and analysis of the interactive working mechanism under varying environment.
This Special Issue welcomes the submission of new perspectives, theories and algorithms to the challenging problems of performance prediction and fault diagnosis towards electric motors and drives. Research areas may include, but are not limited to, the following topics:
- Data cleaning and data quality improvement;
- Advanced modeling techniques;
- Signal processing and feature extraction;
- Condition monitoring and health assessment;
- Data-driven intelligent fault diagnosis and performance prediction;
- Edge computation for fault diagnosis;
- Digital-twin-based diagnosis and prediction.
Prof. Dr. Jinglong Chen
Dr. Tongyang Pan
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
- fault diagnosis
- condition monitoring
- signal processing
- deep learning
- electric motors and drives
