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Remote or Standoff Sensing Technologies for Infrastructure Monitoring

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

Deadline for manuscript submissions: closed (20 October 2022) | Viewed by 4371

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 invite papers for a Special Issue on remote inspection and monitoring of infrastructure for assuring its safety, health, and structural integrity. Aging infrastructure worldwide poses a serious public safety issue and may cause heavy collateral damage if not frequently inspected and maintained. Major parts of infrastructure that require immediate attention are roadways, railways, waterways, bridge decks, dams, pipelines, electrical grids, and forestry. 

The current practice of manual inspection, contact sensing, 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 technique are therefore required for assuring 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, voids, and external variables such as quakes, storms, fire, and sabotage.  Relevant techniques may include electromagnetic, acoustic, photo-acoustic, microwave, optical, laser, geographical information system, global navigation satellite system, sensor network, big data, machine learning, and probabilistic risk assessment techniques. 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 efficiency, and public safety.

Papers dealing with

  • scoping study;
  • ground-based, air-borne, and space-borne system concepts;
  • geospatial imaging techniques;
  • laser/radar sensing;
  • sensor network and data fusion;
  • modelling and design of sensor and imaging systems;
  • simulation and experimental results;
  • prototyping of sensor platforms;
  • proof-of-principle testing;
  • field testing;
  • and probabilistic risk assessments

are encouraged for the 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 cuing 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

13 pages, 4332 KiB  
Article
A Geometric-Feature-Based Method for Automatic Extraction of Anchor Rod Points from Dense Point Cloud
by Siyuan Li, Dongjie Yue, Dehua Zheng, Dongjian Cai and Chuang Hu
Sensors 2022, 22(23), 9289; https://doi.org/10.3390/s22239289 - 29 Nov 2022
Viewed by 1483
Abstract
As the technology of high-precision 3D laser scanning becomes increasingly prevalent in the fields of hydraulic building modeling and deformation monitoring, the quality of point clouds plays an increasingly crucial role in data processing. This paper investigates an automatic extraction method of anchor [...] Read more.
As the technology of high-precision 3D laser scanning becomes increasingly prevalent in the fields of hydraulic building modeling and deformation monitoring, the quality of point clouds plays an increasingly crucial role in data processing. This paper investigates an automatic extraction method of anchor rod points based on geometric features, which focuses on the influence of anchor rod points and mixed pixels in the data of an underground powerhouse of a pumped storage power station on modeling and deformation monitoring during the construction period. This workflow consists of two steps that can automatically extract anchor rod points from high-density point cloud data. Triangular mesh features in the local neighborhood and the parameters of the anchor rods are used to locate the anchor rod in downsampled data, and curvature features are used to extract anchor rod points precisely. The experiment of extracting anchor rods shows that the accuracy of this method of initial identification is 97.2%. Furthermore, precise extraction based on curvature curve fitting is applicable. This method can accurately separate the three types of anchor rods from the dense point cloud on the rough surface of a cavern roof; the false-extraction rate of anchor rod points is about 0.11% to 5.09%. This method can provide high-quality and dependable data sources for the precise registration, modeling and deformation analysis of point clouds in a construction cavern. Full article
(This article belongs to the Special Issue Remote or Standoff Sensing Technologies for Infrastructure Monitoring)
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16 pages, 6448 KiB  
Article
Application of Edge Computing in Structural Health Monitoring of Simply Supported PCI Girder Bridges
by Yi-Ching Lin, Chin-Yu Hsiao, Jian-Hua Tong, Chih-Pin Liao, Shin-Tai Song, Hsin-Chu Tsai and Jui-Lin Wang
Sensors 2022, 22(22), 8711; https://doi.org/10.3390/s22228711 - 11 Nov 2022
Cited by 1 | Viewed by 2494
Abstract
This study proposes an innovative method for structural health monitoring of simply supported PCI girder bridges based on dynamic strain and edge computing. Field static and dynamic load tests were conducted on a bridge consisting of a span with newly replaced PCI girders [...] Read more.
This study proposes an innovative method for structural health monitoring of simply supported PCI girder bridges based on dynamic strain and edge computing. Field static and dynamic load tests were conducted on a bridge consisting of a span with newly replaced PCI girders and numerous spans with old PCI girders. Both the static and dynamic test results showed that the flexural rigidity of the old PCI girders decreased significantly due to deterioration. To improve the efficiency of on-site monitoring data transmission and data analysis, this study developed a smart dynamic strain gauge node with the function of edge computing. Continuous data with a sampling frequency of 100 Hz were computed at the sensor node. Among the computed results, only the maximum dynamic strain data caused by the passage of the heaviest vehicle within 1 min were transmitted. The on-site monitoring results indicated that under routine traffic conditions, the dynamic strain response of the new PCI girder was smaller than that of the deteriorated PCI girder. When the monitored dynamic strain response has a tendency to magnify, attention should be paid to the potential prestress loss or other deterioration behaviors of the bridge. Full article
(This article belongs to the Special Issue Remote or Standoff Sensing Technologies for Infrastructure Monitoring)
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