Symmetry in Bearing Modeling and Intelligent Fault Diagnosis

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Engineering and Materials".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 202

Special Issue Editors

College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Interests: intelligent fault diagnosis; status assessment and trend forecasting; rotating machinery signal processing

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Guest Editor
School of Rail Transportation, Soochow University, Suzhou 215131, China
Interests: machinery intelligent fault diagnosis; health monitoring of rotating machines; adaptive signal decomposition
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Guest Editor
School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: industrial cyber-physical systems; prognostics and system health management; graph representation learning
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Special Issue Information

Dear Colleagues,

Bearings are the key supporting components of rotating equipment, such as aircraft engines, wind turbines, high-speed trains, etc., and have played a very important role in modern society. Due to the diverse requirements of equipment, bearings often operate under harsh conditions such as high speed, heavy load, and variable working conditions, which inevitably lead to fatigue damage and significant economic losses or casualties. It is necessary and meaningful to estiablish the model and intelligently diagnose the faults of bearings. In addition, some new methods have been developed based on symmetry in mathematical models, machine learning (including feature symmetry), deep learning, and transfer learning. These methods provide effective technical solutions for evaluating bearing status and identifying specific types of bearing faults.

Symmetry in bearing modeling and intelligent fault diagnosis is an interdisciplinary field that thrives on the dynamic exchange of ideas. This planned Special Issue of Symmetry aims to provide a forum for researchers and industrial engineers to exchange their latest findings on symmetry in bearing modeling and intelligent fault diagnosis, allowing for discussion on the vital issues, challenges, and potential future trends in modern prognostics and health management systems. Papers submitted to this Special Issue are expected to provide the latest developments in data-driven design approaches, especially new theoretical results with practical applications. We would like to invite experts worldwide to contribute their research, including, but not limited to, the areas listed below:

  • Symmetry in bearing mathematical modeling;
  • Intelligent fault diagnosis with imbalanced samples;
  • Active learning intelligent diagnosis with small samples;
  • Data-driven performance evaluation, decisions and their applications;
  • Transfer fault diagnosis.

Dr. Jiantao Lu
Dr. Xingxing Jiang
Dr. Jie Liu
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. Symmetry 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

  • symmetry in bearing modeling
  • intelligent fault diagnosis
  • data-driven fault diagnosis method
  • interpretable intelligent diagnosis
  • transfer learning
  • active learning

Published Papers

This special issue is now open for submission.
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