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Special Issue "Model-Free Structural Health Monitoring Approaches"

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

Deadline for manuscript submissions: 30 November 2021.

Special Issue Editors

Dr. Donya Hajializadeh
E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, University of Surrey, Guildford CM2 7XH, UK
Interests: virtual monitoring of bridges; data-drive structural health monitoring; advanced numerical modeling; risk and reliability assessment of bridges
Dr. Boulent Imam
E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences (c5), University of Surrey, Guildford GU2 7XH, UK
Interests: structural health monitoring of bridges; fatigue assessment; metallic bridges; scour and corrosion assessment; reliability assessment of bridges
Special Issues and Collections in MDPI journals
Dr. Ying Wang
E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, University of Surrey, Guildford GU2 7XH, UK
Interests: Structural health monitoring; Structural dynamics; Guided wave; Artificial intelligence algorithm and data analytics for civil infrastructure; Concrete with waste materials

Special Issue Information

Dear Colleagues,

With many structures and infrastructures typically well aged and used past their life expectancy and carrying loads beyond their original design capacity, there is an urgent need to develop efficient and reliable structural health monitoring and damage identification systems.

In a broad categorization, structural health monitoring (SHM) systems can be divided into model-based and model-free (data-driven) approaches. The model-based approach detects damages using a numerical model and physical description of the structure behavior. The model-free approach generally relies on the analysis of the structure behavior using data-driven algorithms and without developing a numerical model of the structure. The main advantage of the model-free approach of SHM is its great potential for network-based real-time SHM. This Special Issue will be focused on studies that present novel data-driven and model-free structural health monitoring systems for any type of structure or infrastructure. We welcome all studies that demonstrate the application of physical sensors and remote and smart sensing for developing a data-driven SHM system.

Dr. Donya Hajializadeh
Dr. Boulent Imam
Dr. Ying Wang
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. 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 2200 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

  • structural health monitoring (SHM)
  • data-driven
  • model-free
  • machine learning

Published Papers

This special issue is now open for submission.
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