Trends and Recent Advancements in Structural Health Monitoring

Dear Colleagues,

Structural health monitoring (SHM) is a technique that can be classified as a non-destructive evaluation (NDE), however, the system is automated and provides continuous monitoring. Typically, this procedure is triggered by damage-tolerant design where the damage has to be checked and inspected at defined intervals/continuously based on NDE modern sensing hardware that is integrated into the structural materials. It is further combined with advanced signal processing software, causing NDE to become a segmented part of the materials and structures and hence automating the conventional inspection process.

A vast amount of work has been performed in this field, and major developments have taken place in various types of structures including, but not limited to, aerospace, mechanical and civil structures. This is despite the many associated challenges with the implementation of SHM technology, such as sensor selection and placement on the structure, data communication and management, data analytics (feature extraction), as well as visualization (data fusion).

This call for papers welcomes manuscripts dealing with recent advancements in the fields of SHM that cover material characterizations and structural components, with a specific focus on additively manufactured components. We invite researchers to submit their related work on any types of sensors (contact and non-contact) applied to SHM systems, innovative research, and reviews. 

The topics include, but are not limited to:

• Wired and wireless sensing for SHM
• In situ contact and non-contact sensors in additive manufacturing
• Sensor integration/embedment during manufacturing
• Feature extraction and data fusion of sensor networks
• Damage localization and assessment in additively manufactured systems

Prof. Dr. Ali Abdul-Aziz
Prof. Dr. Pawel H. Malinowski
Dr. Samir Mustapha
Guest Editors

Manuscript Submission Information

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• SHM research
• sensor technology
• wireless sensing
• material characterizations
• additive manufacturing
• data fusion
• aerospace