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Special issue "Feature Papers in Fault Diagnosis and Prognosis" in Machines
发布者: 李响Xiang Li | 2022-02-08 | 495

Link: https://www.mdpi.com/journal/machines/special_issues/Prognosis_Machines

 

Dear Colleagues,

 

It is our great pleasure to announce this Special Issue to celebrate the 10th anniversary of Machines. Machinery condition monitoring is of great importance in the industries. Accurate condition estimation and prediction of the machines can significantly enhance operation safety, increase working efficiency and reduce maintenance costs. Through analysis of the collected machinery condition monitoring data, such as vibration, temperature, images. etc., using signal processing or artificial intelligence methods, the health states of the machines can be well reflected and evaluated. In the past few decades, machinery fault diagnosis and prognosis methodologies have been developing rapidly and achieved great success in both academic research and practical engineering problems. This Special Issue focuses on the recent advancements in machinery fault diagnosis and prognosis. Different perspectives in this research field are all welcomed, including the methodologies or industrial application cases based on physical models, signal processing, data-driven models, data-model fusion, digital twins model, etc. Both original research papers and review papers are invited.

 

Dr. Xiang Li
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 papers will be 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 1800 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
  • fault detection
  • prognosis
  • remaining useful life prediction
  • intelligent maintenance
  • signal analysis and processing
  • data-driven model
  • artificial intelligence
  • digital twins
  • interpretable deep learning theory