We are exceedingly happy to announce that the Digital Mining Center team has published a record number of journal articles at the end of this year. In the last two months of 2020, as many as 11 new papers appeared. The studies present the progress of the research conducted in the scope of all the four projects (MEITIM, AMICOS, OPMO, SafeMe4Mine) in which the team is currently involved and some more. We invite the reader to get acquainted with these works listed below:
@article{Adach-Pawelus2020,
title = {Towards Sustainable Mining in the Didactic Process—MEITIM Project as an Opportunity to Increase the Attractiveness of Mining Courses (A Case Study of Poland) },
author = {Karolina Adach-Pawelus and Anna Gogolewska and Justyna Gorniak-Zimroz and Juan Herrera Herbert and Arturo Hidalgo and Barbara Kielczawa and Joanna Krupa-Kurzynowska and Matti Lampinen and Maria A. Mamelkina and Gabriela Paszkowska and Danuta Szyszka and Ritva Tuunila and Magdalena Worsa-Kozak and Justyna Wozniak},
url = {https://www.mdpi.com/2071-1050/12/23/10138},
doi = {10.3390/su122310138},
year = {2020},
date = {2020-12-04},
journal = {Sustainability},
volume = {12},
number = {23},
abstract = {Mining has been embedded in the public consciousness as a dirty, non-innovative, outdated and environmentally harmful industry. Proper education, especially the academic one, becomes crucial to successfully change this image. This article depicts the initial assumptions of the international project Master in Entrepreneurship, Innovation and Technology Integration in Mining (MEITIM), co-financed by EIT Raw Materials, that aims to diagnose the current state of Polish higher education in the field of mining at, among others, the Wroclaw University of Science and Technology (WUST), concerning the experience of the Technical University of Madrid (UPM) and Lappeenranta University of Technology (LUT). The MEITIM project allowed identifying the directions of necessary changes in the didactic process as an indispensable set of skills and knowledge for a future mining graduate. Such activities are dictated by many guidelines and arrangements, among others, at the level of the European Commission or key industry institutions such as the International Council on Mining and Metals. These are key competencies that require significant changes in university curricula supporting sustainable development goals in innovative mining. The authors show that there is a link between the condition of the mining industry in Poland, its reputation, and the number of people who want to study mining},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mining has been embedded in the public consciousness as a dirty, non-innovative, outdated and environmentally harmful industry. Proper education, especially the academic one, becomes crucial to successfully change this image. This article depicts the initial assumptions of the international project Master in Entrepreneurship, Innovation and Technology Integration in Mining (MEITIM), co-financed by EIT Raw Materials, that aims to diagnose the current state of Polish higher education in the field of mining at, among others, the Wroclaw University of Science and Technology (WUST), concerning the experience of the Technical University of Madrid (UPM) and Lappeenranta University of Technology (LUT). The MEITIM project allowed identifying the directions of necessary changes in the didactic process as an indispensable set of skills and knowledge for a future mining graduate. Such activities are dictated by many guidelines and arrangements, among others, at the level of the European Commission or key industry institutions such as the International Council on Mining and Metals. These are key competencies that require significant changes in university curricula supporting sustainable development goals in innovative mining. The authors show that there is a link between the condition of the mining industry in Poland, its reputation, and the number of people who want to study mining
This article depicts the initial assumptions of
the international project Master in Entrepreneurship, Innovation and Technology
Integration in Mining (MEITIM), co-financed by EIT Raw Materials, that aims to
diagnose the current state of Polish higher education in the field of mining
at, among others, the Wroclaw University of Science and Technology (WUST),
concerning the experience of the Technical University of Madrid (UPM) and
Lappeenranta University of Technology (LUT). The MEITIM project allowed for
identifying the directions of necessary changes in the didactic process so as
to provide an indispensable set of skills and knowledge for a future mining
graduate.
Zietek, Bartlomiej; Banasiewicz, Aleksandra; Zimroz, Radoslaw; Szrek, Jaroslaw; Gola, Sebastian
@article{Zitek2020,
title = {A Portable Environmental Data-Monitoring System for Air Hazard Evaluation in Deep Underground Mines},
author = {Bartlomiej Zietek and Aleksandra Banasiewicz and Radoslaw Zimroz and Jaroslaw Szrek and Sebastian Gola},
url = {https://doi.org/10.3390/en13236331},
doi = {10.3390/en13236331},
year = {2020},
date = {2020-01-01},
journal = {Energies},
volume = {13},
number = {23},
pages = {6331},
publisher = {MDPI AG},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The aim of this paper is to present a system, which uses low-cost gas sensors and microcontrollers, and takes advantage of commonly used smartphones as a computing and visualization tool to be used in air hazard evaluation. The results of the monitoring system tests in one of the Polish underground mines are presented in the article.
@article{Szrek2020b,
title = {Application of the infrared thermography and Unmanned Ground Vehicle for rescue action support in undergroundmine - the AMICOS project},
author = {Jaroslaw Szrek and Radoslaw Zimroz and Jacek Wodecki and Anna Michalak and Mateusz Goralczyk and Magdalena Worsa-Kozak },
url = {https://www.mdpi.com/2072-4292/13/1/69},
doi = {https://doi.org/10.3390/rs13010069},
year = {2021},
date = {2021-01-01},
journal = {Remote Sensing },
volume = {13},
number = {1},
pages = {69},
abstract = {Extraction of raw materials, especially in extremely harsh underground mine conditions is irrevocably associated with high risk and probability of accidents. Natural hazards, heavy-duty machines, used technologies even if all perfectly organized - may result in an accident. In such critical situation, rescue actions may require advanced technologies as an autonomous mobile robot, the various sensory system including gas detector, infrared thermography, image acquisition, advanced analytics, etc. In the paper, we describe several scenarios related to rescue action in an underground mine with the assumption that searching for sufferers should be done with potential seismic, gas, high temperature, etc. hazards. Thus the possibility of rescue team activities in such areas may be highly risky. This work reports results of testing of UGV robotic system in underground mine developed in the frame of AMICOS project. The system consists of UGV with a sensory system and an image processing module based on the adaptation of YOLO and HOG algorithms. The experiment was very successful, human detection efficiency was very promising. Future work will be related to test the AMICOS technology in deep copper ore mines. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Extraction of raw materials, especially in extremely harsh underground mine conditions is irrevocably associated with high risk and probability of accidents. Natural hazards, heavy-duty machines, used technologies even if all perfectly organized - may result in an accident. In such critical situation, rescue actions may require advanced technologies as an autonomous mobile robot, the various sensory system including gas detector, infrared thermography, image acquisition, advanced analytics, etc. In the paper, we describe several scenarios related to rescue action in an underground mine with the assumption that searching for sufferers should be done with potential seismic, gas, high temperature, etc. hazards. Thus the possibility of rescue team activities in such areas may be highly risky. This work reports results of testing of UGV robotic system in underground mine developed in the frame of AMICOS project. The system consists of UGV with a sensory system and an image processing module based on the adaptation of YOLO and HOG algorithms. The experiment was very successful, human detection efficiency was very promising. Future work will be related to test the AMICOS technology in deep copper ore mines.
This fruit of cooperation between the Faculty of Mechanical Engineering, and the Faculty of Geoengineering, Mining, and Geology of Wrocław University of Science and Technology shows how unmanned ground vehicles can help rescue teams to find victims of an underground accident. It constitutes a scientific report from tests of the UGV robotic system developed in the scope of the AMICOS project in realistic conditions – in an underground mine. The robot equipped with infrared and RGB cameras, together with an image processing module has been proven to successfully detect a human in the mine’s environment.
@article{Góralczyk2020,
title = {Increasing Energy Efficiency and Productivity of the Comminution Process in Tumbling Mills by Indirect Measurements of Internal Dynamics—An Overview },
author = {Mateusz Goralczyk and Pavlo Krot and Radoslaw Zimroz and Szymon Ogonowski},
url = {https://www.mdpi.com/1996-1073/13/24/6735},
doi = {https://doi.org/10.3390/en13246735},
year = {2020},
date = {2020-12-21},
journal = {Energies},
volume = {13},
number = {24},
abstract = {Tumbling mills have been widely implemented in many industrial sectors for the grinding of bulk materials. They have been used for decades in the production of fines and in the final stages of ore comminution, where optimal levels for the enrichment particles’ sizes are obtained. Even though these ubiquitous machines of relatively simple construction have been subjected to extensive studies, the industry still struggles with a very low energy efficiency of the comminution process. Moreover, obtaining an optimal size for the grinding product particles is crucial for the effectiveness of the following processes and waste production reduction. New, innovative processing methods and machines are being developed to tackle the problem; however, tumbling mills are still most commonly used in all ranges of the industry. Since heavy equipment retrofitting is the most costly approach, process optimization with dedicated models and control systems is the most preferable solution for energy consumption reduction. While the classic technological measurements in mineral processing are well adopted by the industry, nowadays research focuses on new methods of the mill’s internal dynamics analysis and control. This paper presents a retrospective overview of the existing models of internal load motion, an overview of the innovations in process control, and some recent research and industrial approaches from the energy consumption reduction point of view.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Tumbling mills have been widely implemented in many industrial sectors for the grinding of bulk materials. They have been used for decades in the production of fines and in the final stages of ore comminution, where optimal levels for the enrichment particles’ sizes are obtained. Even though these ubiquitous machines of relatively simple construction have been subjected to extensive studies, the industry still struggles with a very low energy efficiency of the comminution process. Moreover, obtaining an optimal size for the grinding product particles is crucial for the effectiveness of the following processes and waste production reduction. New, innovative processing methods and machines are being developed to tackle the problem; however, tumbling mills are still most commonly used in all ranges of the industry. Since heavy equipment retrofitting is the most costly approach, process optimization with dedicated models and control systems is the most preferable solution for energy consumption reduction. While the classic technological measurements in mineral processing are well adopted by the industry, nowadays research focuses on new methods of the mill’s internal dynamics analysis and control. This paper presents a retrospective overview of the existing models of internal load motion, an overview of the innovations in process control, and some recent research and industrial approaches from the energy consumption reduction point of view.
This paper, which is an overview of the innovations in process control presents an insight into the existing models of the internal load motion in tumbling mills. Recent research and industrial approaches that can be valuable for the reduction of energy consumption in this most energetically-demanding mining process are presented.
@article{nowicki2020local,
title = {Local Defect Detection in Bearings in the Presence of Heavy-Tailed Noise and Spectral Overlapping of Informative and Non-Informative Impulses},
author = {Jakub Nowicki and Justyna Hebda-Sobkowicz and Radoslaw Zimroz and Agnieszka Wylomanska},
url = {https://www.mdpi.com/1424-8220/20/22/6444},
doi = {https://doi.org/10.3390/s20226444},
year = {2020},
date = {2020-11-11},
journal = {Sensors},
volume = {20},
number = {22},
pages = {6444},
publisher = {Multidisciplinary Digital Publishing Institute},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The main purpose of this article is to
investigate how spectral overlapping of informative and non-informative
impulsive components will affect diagnostic procedures. According to our
knowledge, this problem has not been considered in the literature for the
non-Gaussian signals earlier.
@article{Wodecki2020b,
title = {Influence of non-Gaussian noise on the effectiveness of cyclostationary analysis - simulations and real data analysis},
author = {Jacek Wodecki and Anna Michalak and Agnieszka Wylomanska and Radoslaw Zimroz },
url = {https://doi.org/10.1016/j.measurement.2020.108814},
doi = {10.1016/j.measurement.2020.108814},
year = {2021},
date = {2021-01-01},
journal = {Measurement},
pages = {108814},
publisher = {Elsevier BV},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
By using simulations covering the model of signal, α-stable distribution, and Monte Carlo simulations it has been shown that indeed – the increasing presence of non-Gaussian noise worsens the quality of diagnostic information extracted from the CSC map.
@article{Tubis2020b,
title = {Cyber-Attacks Risk Analysis Method for Different Levels of Automation of Mining Processes in Mines Based on Fuzzy Theory Use},
author = {Agnieszka Tubis and Sylwia Werbinska-Wojciechowska and Mateusz Goralczyk and Adam Wroblewski and Bartlomiej Zietek},
url = {https://www.mdpi.com/1424-8220/20/24/7210},
doi = {https://doi.org/10.3390/s20247210},
year = {2020},
date = {2020-12-16},
journal = {Sensors},
volume = {20},
number = {24},
abstract = {The rising automation level and development of the Industry 4.0 concept in the mining sector increase the risk of cyber-attacks. As a result, this article focuses on developing a risk analysis method that integrates Kaplan’s and Garrick’s approach and fuzzy theory. The proposed approach takes into account the level of automation of the operating mining processes. Moreover, it follows five main steps, including identifying the automation level in a selected mine, definition of cyber-attack targets, identification of cyber-attack techniques, definition of cyber-attack consequences, and risk ratio assessment. The proposed risk assessment procedure was performed according to three cyber-attack targets (databases, internal networks, machinery) and seven selected types of cyber-attack techniques. The fuzzy theory is implemented in risk parameter estimation for cyber-attack scenario occurrence in the mining industry. To illustrate the given method’s applicability, seven scenarios for three levels of mine automation are analyzed. The proposed method may be used to reveal the current cybersecurity status of the mine. Moreover, it will be a valuable guide for mines in which automation is planned in the near future.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The rising automation level and development of the Industry 4.0 concept in the mining sector increase the risk of cyber-attacks. As a result, this article focuses on developing a risk analysis method that integrates Kaplan’s and Garrick’s approach and fuzzy theory. The proposed approach takes into account the level of automation of the operating mining processes. Moreover, it follows five main steps, including identifying the automation level in a selected mine, definition of cyber-attack targets, identification of cyber-attack techniques, definition of cyber-attack consequences, and risk ratio assessment. The proposed risk assessment procedure was performed according to three cyber-attack targets (databases, internal networks, machinery) and seven selected types of cyber-attack techniques. The fuzzy theory is implemented in risk parameter estimation for cyber-attack scenario occurrence in the mining industry. To illustrate the given method’s applicability, seven scenarios for three levels of mine automation are analyzed. The proposed method may be used to reveal the current cybersecurity status of the mine. Moreover, it will be a valuable guide for mines in which automation is planned in the near future.
The proposed risk assessment procedure was
performed according to three cyber-attack targets (databases, internal
networks, machinery) and seven selected types of cyber-attack techniques. The
fuzzy theory is implemented in risk parameter estimation for cyber-attack
scenario occurrence in the mining industry.
@article{Krot2020d,
title = {Vibration-Based Diagnostics of Radial Clearances and Bolts Loosening in the Bearing Supports of the Heavy-Duty Gearboxes},
author = {Pavlo Krot and Volodymyr Korennoi and Radoslaw Zimroz},
url = {https://www.mdpi.com/1424-8220/20/24/7284},
doi = {https://doi.org/10.3390/s20247284},
year = {2020},
date = {2020-12-18},
journal = {Sensors},
volume = {20},
number = {24},
abstract = {The problem solved in this research is the diagnosis of the radial clearances in bearing supports and the loosening of fastening bolts due to their plastic elongation (creep) or weak tightening using vibration signals. This is an important issue for the maintenance of the heavy-duty gearboxes of powerful mining machines and rolling mills working in non-stationary regimes. Based on a comprehensive overview of bolted joint diagnostic methods, a solution to this problem based on a developed nonlinear dynamical model of bearing supports is proposed. Diagnostic rules are developed by comparing the changes of natural frequency and its harmonics, the amplitudes and phases of shaft transient oscillations. Then, the vibration signals are measured on real gearboxes while the torque is increasing in the transmission during several series of industrial trials under changing bearings and bolts conditions. In parallel, dynamical torque is measured and its interrelation with vibration is determined. It is concluded that the radial clearances are the most influencing factors among the failure parameters in heavy-duty gearboxes of industrial machines working under impulsive and step-like loading. The developed diagnostics algorithm allows condition monitoring of bearings and fastening bolts, allowing one to undertake timely maintenance actions to prevent failures.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The problem solved in this research is the diagnosis of the radial clearances in bearing supports and the loosening of fastening bolts due to their plastic elongation (creep) or weak tightening using vibration signals. This is an important issue for the maintenance of the heavy-duty gearboxes of powerful mining machines and rolling mills working in non-stationary regimes. Based on a comprehensive overview of bolted joint diagnostic methods, a solution to this problem based on a developed nonlinear dynamical model of bearing supports is proposed. Diagnostic rules are developed by comparing the changes of natural frequency and its harmonics, the amplitudes and phases of shaft transient oscillations. Then, the vibration signals are measured on real gearboxes while the torque is increasing in the transmission during several series of industrial trials under changing bearings and bolts conditions. In parallel, dynamical torque is measured and its interrelation with vibration is determined. It is concluded that the radial clearances are the most influencing factors among the failure parameters in heavy-duty gearboxes of industrial machines working under impulsive and step-like loading. The developed diagnostics algorithm allows condition monitoring of bearings and fastening bolts, allowing one to undertake timely maintenance actions to prevent failures.
The problem solved in this research is the
diagnosis of the radial clearances in bearing supports and the loosening of
fastening bolts due to their plastic elongation (creep) or weak tightening
using vibration signals. This is an important issue for the maintenance of the
heavy-duty gearboxes of powerful mining machines and rolling mills working in
non-stationary regimes.
@article{Kope2020,
title = {Application of Remote Sensing, GIS and Machine Learning with Geographically Weighted Regression in Assessing the Impact of Hard Coal Mining on the Natural Environment},
author = {Anna Kopec and Pawel Trybala and Dariusz Glabicki and Anna Buczynska and Karolina Owczarz and Natalia Bugajska and Patrycja Kozinska and Monika Chojwa and Agata Gattner},
url = {https://doi.org/10.3390/su12229338},
doi = {10.3390/su12229338},
year = {2020},
date = {2020-01-01},
journal = {Sustainability},
volume = {12},
number = {22},
pages = {9338},
publisher = {MDPI AG},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this article, research was carried out on the environmental impact of underground hard coal mining in the Bogdanka mine, located in southeastern Poland. For this purpose, spectral indexes, satellite radar interferometry, Geographic Information System (GIS) tools and machine learning algorithms were utilized
@article{Borkowski2020,
title = {Comminution of Copper Ores with the Use of a High-Pressure Water Jet},
author = {Przemyslaw Borkowski},
url = {https://doi.org/10.3390/en13236274},
doi = {10.3390/en13236274},
year = {2020},
date = {2020-01-01},
journal = {Energies},
volume = {13},
number = {23},
pages = {6274},
publisher = {MDPI AG},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The article presents research on the
comminution of copper ore in a mill of
the author’s design using high-pressure water jet energy to investigate the
usefulness of such a method for comminuting copper ore. As a result of such a
treatment, a significant increase in the specific surface of ore particles is
obtained, which in turn can facilitate and improve further processing of the
mineral.
The study aimed to recognize if groundwater stratification occurs in the shaft. In 2015, a sample of the water outflowing through the “Aleksander” adit was taken to check the potential influence of mine flooding on the environment and to confirm the changes in groundwater chemistry over time. These were the first, and so far, the only studies on the chemical composition of water in the flooded mine in that area.
