Special Issue "Data-Driven Fault Diagnosis for Electric Drives"

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Machines Testing and Maintenance".

Deadline for manuscript submissions: closed (15 June 2023) | Viewed by 304

Special Issue Editors

Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China
Interests: fault diagnosis; deep learning; vibration signal processing; active magnetic bearing; mechatronics
Dr. Chenan Zhang
E-Mail Website
Guest Editor
State Key Laboratory of High Temperature Gas Dynamics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
Interests: intelligent fault diagnosis
Dr. Zhe Sun
E-Mail Website
Guest Editor
Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China
Interests: dynamics, control and diagnosis of rotating machinery

Special Issue Information

Dear Colleagues,

Electric drives are widely used in industry and residential life. The operation of electric drives should be safe, and real-time health monitoring and fault diagnosis have become essential functions. With the development of deep learning, automatic fault monitoring and diagnosis based on data is a hot spot for research, which is vital for liberating human resources and improving the overall automation level of the equipment.

This Special Issue will focus on the fault diagnosis technology of electric devices, including fault principle analysis, the applications of machine learning methods, and signal processing techniques, covering various electric devices.

Dr. Xunshi Yan
Dr. Chenan Zhang
Dr. Zhe Sun
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

  • data-driven fault diagnosis
  • fault detection
  • electric drives
  • power system
  • mechatronics
  • deep learning
  • machine learning
  • signal processing
  • data fusion

Published Papers

There is no accepted submissions to this special issue at this moment.
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