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Remote Sensing for Health Monitoring of Infrastructure

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

Deadline for manuscript submissions: closed (20 January 2022) | Viewed by 5472

Special Issue Editor


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Guest Editor
Division of Nuclear Science and Engineering, Argonne National Laboratory (ANL), Lemont, IL 60439, USA
Interests: sensors; millimeter waves; remote sensing; non-destructive evaluation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are inviting papers for a Special Issue on remote inspection and monitoring of infrastructure to ensure its safety, health, and structural integrity. The aging infrastructure worldwide poses serious public safety issues and can cause heavy collateral damage if not frequently inspected and maintained. Major parts of infrastructure that would require immediate attention are roadways, railways, waterways, bridge decks, dams, pipelines, electrical grid, and forestry. 

The current practice of manual inspection, contact sensing, and in situ or point sensing, and nondestructive testing approaches are inadequate and expensive due to their vastness and labor-intensive nature. Remote and spatial monitoring techniques are therefore required to ensure their safety and efficient management. The requirements for sensing and measurements are application-specific and may consist of internal variables such as displacements, bending, vibration, effluents, leaks, heat, noise, cracks, and voids, and external variables such as quakes, storms, fire, and sabotage. Relevant techniques may include electromagnetic, acoustic, photoacoustic, microwaves, optical, lasers, geographical information systems, global navigation satellite systems, sensor networks, big data, machine learning, and probabilistic risk assessments. Successful remote monitoring techniques for these applications would reap enormous benefits in the rapid detection of catastrophic defects, prediction of failure probabilities, efficient infrastructure management, cost saving, and public safety.

Papers dealing with

  • Scoping study;
  • Ground-based, airborne, and spaceborne system concepts;
  • Geospatial imaging techniques;
  • Laser/radar sensing;
  • Sensor network and data fusion;
  • Modeling and design of sensor and imaging systems;
  • Simulation and experimental results;
  • Prototyping of sensor platforms;
  • Proof-of-principle testing;
  • Field testing;
  • Probabilistic risk assessments;

are encouraged for various applications described above. Papers may focus on the remote measurement of observables and signatures related to structural variables as they would serve as fast search and curing techniques for further focused investigation. The definition of remote sensing for this purpose can include standoff sensing, networked sensing with central point or cloud computing, and air- and space-borne systems.

Dr. Nachappa Gopalsami
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

  • Infrastructure
  • Structural health monitoring
  • Remote sensing
  • Wide area monitoring
  • Geospatial sensing
  • Satellite imaging
  • Hyperspectral techniques
  • Sensor networks
  • Nondestructive inspection techniques
  • Machine learning
  • Probabilistic risk assessments

Published Papers (2 papers)

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Research

24 pages, 32335 KiB  
Article
Performance Assessment of Reference Modelling Methods for Defect Evaluation in Asphalt Concrete
by Pauli Putkiranta, Matti Kurkela, Matias Ingman, Aino Keitaanniemi, Aimad El Issaoui, Harri Kaartinen, Eija Honkavaara, Hannu Hyyppä, Juha Hyyppä and Matti T. Vaaja
Sensors 2021, 21(24), 8190; https://doi.org/10.3390/s21248190 - 8 Dec 2021
Cited by 1 | Viewed by 2583
Abstract
The deterioration of road conditions and increasing repair deficits pose challenges for the maintenance of reliable road infrastructure, and thus threaten, for example, safety and the fluent flow of traffic. Improved and more efficient procedures for maintenance are required, and these require improved [...] Read more.
The deterioration of road conditions and increasing repair deficits pose challenges for the maintenance of reliable road infrastructure, and thus threaten, for example, safety and the fluent flow of traffic. Improved and more efficient procedures for maintenance are required, and these require improved knowledge of road conditions, i.e., improved data. Three-dimensional mapping presents possibilities for large-scale collection of data on road surfaces and automatic evaluation of maintenance needs. However, the development and, specifically, evaluation of large-scale mobile methods requires reliable references. To evaluate possibilities for close-range, static, high-resolution, three-dimensional measurement of road surfaces for reference use, three measurement methods and five instrumentations are investigated: terrestrial laser scanning (TLS, Leica RTC360), photogrammetry using high-resolution professional-grade cameras (Nikon D800 and D810E), photogrammetry using an industrial camera (FLIR Grasshopper GS3-U3-120S6C-C), and structured-light handheld scanners Artec Leo and Faro Freestyle. High-resolution photogrammetry is established as reference based on laboratory measurements and point density. The instrumentations are compared against one another using cross-sections, point–point distances, and ability to obtain key metrics of defects, and a qualitative assessment of the processing procedures for each is carried out. It is found that photogrammetric models provide the highest resolutions (10–50 million points per m2) and photogrammetric and TLS approaches perform robustly in precision with consistent sub-millimeter offsets relative to one another, while handheld scanners perform relatively inconsistently. A discussion on the practical implications of using each of the examined instrumentations is presented. Full article
(This article belongs to the Special Issue Remote Sensing for Health Monitoring of Infrastructure)
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29 pages, 12852 KiB  
Article
Processing Strategy and Comparative Performance of Different Mobile LiDAR System Grades for Bridge Monitoring: A Case Study
by Yi-Chun Lin, Jidong Liu, Yi-Ting Cheng, Seyyed Meghdad Hasheminasab, Timothy Wells, Darcy Bullock and Ayman Habib
Sensors 2021, 21(22), 7550; https://doi.org/10.3390/s21227550 - 13 Nov 2021
Cited by 6 | Viewed by 2315
Abstract
Collecting precise as-built data is essential for tracking construction progress. Three-dimensional models generated from such data capture the as-is conditions of the structures, providing valuable information for monitoring existing infrastructure over time. As-built data can be acquired using a wide range of remote [...] Read more.
Collecting precise as-built data is essential for tracking construction progress. Three-dimensional models generated from such data capture the as-is conditions of the structures, providing valuable information for monitoring existing infrastructure over time. As-built data can be acquired using a wide range of remote sensing technologies, among which mobile LiDAR is gaining increasing attention due to its ability to collect high-resolution data over a relatively large area in a short time. The quality of mobile LiDAR data depends not only on the grade of onboard LiDAR scanners but also on the accuracy of direct georeferencing information and system calibration. Consequently, millimeter-level accuracy is difficult to achieve. In this study, the performance of mapping-grade and surveying-grade mobile LiDAR systems for bridge monitoring is evaluated against static laser scanners. Field surveys were conducted over a concrete bridge where grinding was required to achieve desired smoothness. A semi-automated, feature-based fine registration strategy is proposed to compensate for the impact of georeferencing and system calibration errors on mobile LiDAR data. Bridge deck thickness is evaluated using surface segments to minimize the impact of inherent noise in the point cloud. The results show that the two grades of mobile LiDAR delivered thickness estimates that are in agreement with those derived from static laser scanning in the 1 cm range. The mobile LiDAR data acquisition took roughly five minutes without having a significant impact on traffic, while the static laser scanning required more than three hours. Full article
(This article belongs to the Special Issue Remote Sensing for Health Monitoring of Infrastructure)
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