Health Monitoring of Cement-Based Structures/Materials: Signal Processing and Artificial Intelligence Techniques

Dear colleagues,

The costs for repairing and maintaining cement-based structures currently represent a significant proportion of the gross national product in developed countries. Monitoring the health status of these structures is of utmost importance in order to plan timely management interventions and avoid the eventual failure of the structure itself. Many different measurement techniques can be adopted to monitor the health status of cement-based structures, including: electrical impedance measurements (to detect the ingress of contaminants, monitor the curing period, detect strain and crack formation, identify corrosion processes, sense temperature changes, etc.), computer vision techniques (e.g., to detect cracks or surface defects), ultrasound methods and/or thermal imaging (e.g., to evaluate the moisture content and the presence of delamination phenomena), and strain gauges (widely used in structural health monitoring (SHM) to monitor loads and related strain). In addition, various sensors can be combined to obtain more accurate results (sensor fusion).

Regardless of the technique, suitable signal processing techniques are needed to increase the robustness of the approach and safely exploit data provided as useful information for labelling the health status of the structures/materials under investigation. These processing strategies also involve artificial intelligence (AI), which in recent years has gained a lot of importance on the interpretation of big data collected in monitoring activities (e.g., to search for patterns typical of certain events like crack formation or to predict the strength or the durability of a certain type of concrete).

This Special Issue is intended to publish original research and review papers dealing with the analysis and interpretation of data collected in the monitoring/inspection of cement-based structures or elements.

Suitable topics include, but are not limited to, the following:

• Signal processing techniques for different types of signals acquired on cement-based structures and materials;
• Signal analysis related to non-destructive techniques (NDTs);
• Analysis of electrical impedance/resistivity measurements in cement-based structures and materials;
• AI techniques for the monitoring of cement-based structures and materials;
• AI techniques for crack detection;
• Signal processing techniques for SHM;
• Image processing for computer vision and thermal imaging on cement-based structures and materials;
• Analysis of correlations between electrical resistivity and ingress of contaminants;
• Data processing in sensor fusion applications.

Dr. Gloria Cosoli
Dr. Paolo Chiariotti
Dr. Eng. Alessandra Mobili
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. Signals is an international peer-reviewed open access quarterly 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 1000 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.

• Cement-based structures/materials 
• Monitoring techniques 
• Non-destructive techniques (NDTs) 
• Structural health monitoring (SHM) 
• Signal processing 
• Self-sensing materials 
• Sensor fusion 
• Artificial Intelligence 
• Durability