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Intelligent Diagnostic and Prognostic Methods for Electronic Systems and Mechanical Systems

This special issue belongs to the section “Mechanical Engineering“.

Special Issue Information

Dear Colleagues,

The scale of modern electronic systems or mechanical systems is becoming more complex, but the testable parameters are becoming less, which makes it difficult to locate the fault, and thus, the diagnosis cost is high. This Special Issue calls for papers on the fault diagnosis and prediction technology of complex electronic and mechanical systems such as analog circuits, lithium batteries, and gears, including but not limited to fault feature extraction, diagnostic reasoning methods, performance degradation, life prediction, etc.

Prof. Dr. Bing Long
Prof. Dr. Zhen 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 250 words) can be sent to the Editorial Office for assessment.

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. Applied Sciences 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 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
  • diagnostics
  • diagnostic reasoning
  • fault feature extraction
  • prognostics
  • performance degradation
  • life prediction
  • residual useful life (RUL)
  • analog circuits
  • lithium-ion battery
  • gears system
  • data-driven methods
  • model-based methods
  • machine learning
  • neural network

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Appl. Sci. - ISSN 2076-3417