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Multi-Sensor Information Fusion, Advanced Signal Analysis, and Intelligent Fault Diagnosis—2nd Edition

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: 10 December 2024 | Viewed by 41

Special Issue Editors


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Guest Editor
Key Laboratory of Intelligent Manufacturing Technology, Ministry of Education, Department of Mechanical Engineering, College of Engineering, Shantou University, Daxue Road 243, Jinping District, 515063 Shantou, China
Interests: additive manufacturing process monitoring and control; intelligent fault diagnosis and useful life prediction
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy
Interests: sensor monitoring; sustainable manufacturing; machine learning; cyber physical systems
Special Issues, Collections and Topics in MDPI journals
Key Laboratory of Intelligent Manufacturing Technology, Ministry of Education, College of Engineering, Shantou University, 243 Daxue Road, Shantou 515063, China
Interests: laser spectroscopy technology; trace gas detection; infrared sensing system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recently, along with the rapid evolution of intelligence and informatization, sensors have begun to play an important role in industrial development. Multi-sensor information fusion is the integration of multiple sensor systems, which can collect sensor signals that characterize the state of mechanical equipment and diagnose or predict different target states through advanced signal analysis methods. Additionally, manufacturing-process monitoring and control based on multi-sensor information fusion have become research hotspots in academia and industry to ensure the reliability of component quality and the repeatability of manufacturing.

This Special Issue therefore aims to put together original research and review articles regarding recent advancements, technologies, solutions, applications, and new challenges in the field of multi-sensor information fusion.

Potential topics include but are not limited to the following:

  • Multi-sensor information fusion;
  • Advanced signal analysis and machine learning methods;
  • Intelligent fault diagnosis based on deep learning and digital twins;
  • Manufacturing process monitoring and control;
  • Data-driven smart manufacturing.

Dr. Fengtao Wang
Dr. Alessandro Simeone
Dr. Weilin Ye
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. Sensors 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 2600 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

  • multi-sensor information fusion
  • signal analysis
  • fault diagnosis

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This special issue is now open for submission.
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