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Sensors
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Sensing Technologies for Health Monitoring of Smart Structures and Systems
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Sensing Technologies for Health Monitoring of Smart Structures and Systems

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

Deadline for manuscript submissions: 20 November 2024 | Viewed by 1359

Special Issue Editor

Dr. Shirsendu Sikdar

E-Mail Website
Guest Editor
School of Computing and Engineering, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK
Interests: smart monitoring; NDE; vibration & noise control; computational modelling; nonlinear ultrasonics; cyber-physical systems and digital twins

Special Issue Information

Dear Colleagues,

This Special Issue, entitled "Sensing Technologies for Health Monitoring of Smart Structures and Systems", focuses on the development of industry-grade sensing technologies for Structural Health Monitoring (SHM) of smart structures and systems. As we witness ongoing technological transformations in our surroundings, the integration of smart structures and systems has become increasingly prominent. This Special Issue is dedicated to exploring state-of-the-art sensing technologies specifically designed for monitoring the health of intelligent systems and infrastructures.

Our focus aligns with the overarching mission of Sensors, acting as a conduit for disseminating research at the confluence of sensors and associated technologies. The incorporation of sensors for health monitoring not only amplifies the efficiency and safety of smart structures but also contributes significantly to the broader objective of creating more sustainable and resilient environments.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Sensing Technologies; 
  • Health Monitoring; 
  • Smart Structures and Systems;
  • Structural Health Monitoring and NDT;
  • Sensor Integration;
  • IoT Applications;
  • Signal Processing;
  • Wireless Sensor Networks;
  • Wearable Sensors;
  • Remote Sensing.

Dr. Shirsendu Sikdar
Guest Editor

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

  • sensing technologies
  • health monitoring
  • smart structures and systems
  • structural health monitoring and NDT
  • sensor integration
  • IoT applications
  • signal processing
  • wireless sensor networks
  • wearable sensors
  • remote sensing

Published Papers (1 paper)

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Research

20 pages, 14091 KiB  
Article
Augmented Reality-Based Real-Time Visualization for Structural Modal Identification
by Elliott Carter, Micheal Sakr and Ayan Sadhu
Sensors 2024, 24(5), 1609; https://doi.org/10.3390/s24051609 - 1 Mar 2024
Viewed by 1129
Abstract
In the era of aging civil infrastructure and growing concerns about rapid structural deterioration due to climate change, the demand for real-time structural health monitoring (SHM) techniques has been predominant worldwide. Traditional SHM methods face challenges, including delays in processing acquired data from [...] Read more.
In the era of aging civil infrastructure and growing concerns about rapid structural deterioration due to climate change, the demand for real-time structural health monitoring (SHM) techniques has been predominant worldwide. Traditional SHM methods face challenges, including delays in processing acquired data from large structures, time-intensive dense instrumentation, and visualization of real-time structural information. To address these issues, this paper develops a novel real-time visualization method using Augmented Reality (AR) to enhance vibration-based onsite structural inspections. The proposed approach presents a visualization system designed for real-time fieldwork, enabling detailed multi-sensor analyses within the immersive environment of AR. Leveraging the remote connectivity of the AR device, real-time communication is established with an external database and Python library through a web server, expanding the analytical capabilities of data acquisition, and data processing, such as modal identification, and the resulting visualization of SHM information. The proposed system allows live visualization of time-domain, frequency-domain, and system identification information through AR. This paper provides an overview of the proposed technology and presents the results of a lab-scale experimental model. It is concluded that the proposed approach yields accurate processing of real-time data and visualization of system identification information by highlighting its potential to enhance efficiency and safety in SHM by integrating AR technology with real-world fieldwork. Full article
(This article belongs to the Special Issue Sensing Technologies for Health Monitoring of Smart Structures and Systems)
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