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Sensors Solutions for Mapping Mining Environments
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Sensors Solutions for Mapping Mining Environments

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

Deadline for manuscript submissions: closed (1 January 2023) | Viewed by 10713

Special Issue Editors

Prof. Dr. Fabio Remondino

E-Mail Website
Guest Editor
3D Optical Metrology (3DOM) Unit, Bruno Kessler Foundation (FBK), 38123 Trento, Italy
Interests: photogrammetry; laser scanning; optical metrology; 3D; AI; quality control
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Radosław Zimroz

E-Mail Website
Guest Editor
Faculty of Mining Engineering/Machinery Systems Division/VibroAcoustic Lab, Wroclaw University of Technology, 50-421 Wroclaw, Poland
Interests: mining; measurements; monitoring; analitics; acoustic; predictive maintenance
Special Issues, Collections and Topics in MDPI journals
Dr. Denis Guilhot

E-Mail Website
Guest Editor
WorldSensing, C/ Viriat 47, 08014 Barcelona, Spain
Interests: IoT; mining; monitoring; sensors; photonics; space technololgies; InSAR
Special Issues, Collections and Topics in MDPI journals
Dr. Vittorio Cannas

E-Mail Website
Guest Editor
SpacEarth Technology Srl, Via di Vigna Murata 605, 00143 Rome, Italy
Interests: InSAR; optical and thermal remote sensing; photonic devices; seismic monitoring
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Raw Material (RM) and mining industrial sectors rely on various systems of infrastructures for efficient and productive operations such as plants, buildings, gas and water pipes, sewages, tailing dams, underground tunnels, transportations, etc. Such systems, normally located in harsh environments, need periodic inspection, maintenance and monitoring to maximize efficiency and minimize costs and risks. Mining infrastructures and installations are rarely renewed due to high costs involved or to ensure production continuity.

In the last years, the RM industrial sector is slowly adopting innovative techniques to improve productivity from existing assets and infrastructure, leveraging on continuous innovations in sensor technology, machine connectivity, robotics and Artificial Intelligence. However, this digitalization process is not yet succesfully and fully deployed in the mining field. More effective solutions can be envisaged in order to innovate the RM sector and improve process efficiency.

This Special Issue, which stems from the EIT-RM project AMICOS – Autonomous Monitoring and Control System for Mining Plants (https://amicos.fbk.eu/), welcomes but is not limited to contributions in the following topics:

  • Sensor systems in the mining field;
  • 3D imaging and LiDAR;
  • Multispectral and hyperspectral sensors;
  • IoT in mining;
  • InSAR in mining;
  • Optical fiber;
  • UAV/UGV and robotics platforms in the mining field;
  • Sensor fusion;
  • Sensor applications for inspection and monitoring of mining structures;
  • Safety in the mining industry;
  • Case studies in mining.

You may choose our Joint Special Issue in Remote Sensing.

Dr. Fabio Remondino
Prof. Dr. Radosław Zimroz
Dr. Denis Guilhot
Dr. Vittorio Cannas
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. 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

  • raw material
  • mining
  • inspection and monitoring
  • unmanned air vehicles (UAV)
  • unmanned ground vehicles (UGV)
  • robotics
  • 3D mapping and visualization
  • 3D modeling
  • photogrammetry
  • remote sensing
  • LiDAR
  • SLAM
  • IoT
  • artificial intelligence
  • data fusion
  • photonics

Published Papers (3 papers)

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Research

14 pages, 4523 KiB  
Article
Optimization of Dominant Frequency and Bandwidth Analysis in Multi-Frequency 3D GPR Signals to Identify Contaminated Areas
by David Paredes-Palacios, Francisco Mota-Toledo, Bárbara Biosca, Lucía Arévalo-Lomas and Jesús Díaz-Curiel
Sensors 2022, 22(24), 9851; https://doi.org/10.3390/s22249851 - 15 Dec 2022
Viewed by 2143
Abstract
Ground-penetrating radar (GPR) has been widely used in investigations of contaminated areas because of its sensitivity to variations associated with the nature of pore fluids. However, most of the studies were usually based on the visual interpretation of radargrams or on a time [...] Read more.
Ground-penetrating radar (GPR) has been widely used in investigations of contaminated areas because of its sensitivity to variations associated with the nature of pore fluids. However, most of the studies were usually based on the visual interpretation of radargrams or on a time domain amplitude analysis. In this work, we propose a methodology that consists of analyzing the spectral content of the signal recorded in multi-frequency 3D GPR profiles. A remarkable advantage of this type of antenna is its step-frequency system, which provides a much wider emission spectrum than the one corresponding to conventional single-frequency antennas. From the data in the frequency domain, the dominant frequency and bandwidth were calculated as parameters whose variation could be related to the presence of light non-aqueous phase liquid (LNAPL) in the subsurface. By analyzing the variations of these two parameters simultaneously, we were able to delimit the contaminated zones in a case study, associating them with a significant shift of the frequency spectrum with respect to the average of the study area. Finally, as a validation method of the proposed methodology, the results of the frequency analysis were compared with resistivity data obtained with an electromagnetic conductivity meter, showing a very good correlation between the results. Full article
(This article belongs to the Special Issue Sensors Solutions for Mapping Mining Environments)
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15 pages, 10250 KiB  
Article
Monitoring and Analysis of Ground Surface Settlement in Mining Clusters by SBAS-InSAR Technology
by Huini Wang, Kanglun Li, Jun Zhang, Liang Hong and Hong Chi
Sensors 2022, 22(10), 3711; https://doi.org/10.3390/s22103711 - 13 May 2022
Cited by 12 | Viewed by 2475
Abstract
In this paper, we use the small baseline set technology and the early geological hazard identification method based on the selection of Permanent Scatter (PS) and Distributed Scatter (DS) points to carry out the research on surface deformation monitoring caused by underground activities [...] Read more.
In this paper, we use the small baseline set technology and the early geological hazard identification method based on the selection of Permanent Scatter (PS) and Distributed Scatter (DS) points to carry out the research on surface deformation monitoring caused by underground activities in mining cluster areas. We adopted the Small Baseline Subset InSAR (SBAS-InSAR) technique to process Sentinel-1A SAR images over the research area from March 2017 to May 2021. The deformation estimation technology based on the robustness of PS points and DS points can be used for early identification of high-density surface subsidence in a large area of mines. The surface subsidence information can be obtained quickly and accurately, and the advantages of using InSAR technology to monitor long-time surface subsidence in complex mining cluster areas was explored in this study. By comparing the monitoring data of the Global Navigation Satellite System (GNSS) ground monitoring equipment, the accuracy error of large-scale surface settlement information is controlled within 8 mm, which has high accuracy. Meanwhile, according to the spatial characteristics of cluster mining areas, it is analyzed that the relationship between adjacent mining areas through groundwater easily leads to regional associated large-area settlement changes. Compared with the D-InSAR (Differential InSAR) technology applied in mine monitoring at the early stage, this proposed method can monitor a large range of long time series and optimize the problem of decoherence to some extent in mining cluster areas. It has important reference significance for early monitoring and early warning of subsidence disaster evolution in mining intensive areas. Full article
(This article belongs to the Special Issue Sensors Solutions for Mapping Mining Environments)
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23 pages, 24163 KiB  
Article
Accuracy Evaluation of Selected Mobile Inspection Robot Localization Techniques in a GNSS-Denied Environment
by Jarosław Szrek, Paweł Trybała, Mateusz Góralczyk, Anna Michalak, Bartłomiej Ziętek and Radosław Zimroz
Sensors 2021, 21(1), 141; https://doi.org/10.3390/s21010141 - 28 Dec 2020
Cited by 13 | Viewed by 4359
Abstract
Locating an inspection robot is an essential task for inspection missions and spatial data acquisition. Giving a spatial reference to measurements, especially those concerning environmental parameters, e.g., gas concentrations may make them more valuable by enabling more insightful analyses. Thus, an accurate estimation [...] Read more.
Locating an inspection robot is an essential task for inspection missions and spatial data acquisition. Giving a spatial reference to measurements, especially those concerning environmental parameters, e.g., gas concentrations may make them more valuable by enabling more insightful analyses. Thus, an accurate estimation of sensor position and orientation is a significant topic in mobile measurement systems used in robotics, remote sensing, or autonomous vehicles. Those systems often work in urban or underground conditions, which are lowering or disabling the possibility of using Global Navigation Satellite Systems (GNSS) for this purpose. Alternative solutions vary significantly in sensor configuration requirements, positioning accuracy, and computational complexity. The selection of the optimal solution is difficult. The focus here is put on the assessment, using the criterion of the positioning accuracy of the mobile robot with no use of GNSS signals. Automated geodetic surveying equipment is utilized for acquiring precise ground truth data of the robot’s movement. The results obtained, with the use of several methods, compared: Wheel odometry, inertial measurement-based dead-reckoning, visual odometry, and trilateration of ultra-wideband signals. The suitability, pros, and cons of each method are discussed in the context of their application in autonomous robotic systems, operating in an underground mine environment. Full article
(This article belongs to the Special Issue Sensors Solutions for Mapping Mining Environments)
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