2022
1.
Dabek, Przemyslaw; Szrek, Jaroslaw; Zimroz, Radoslaw; Wodecki, Jacek
In: Energies, vol. 15, no. 2, pp. 601, 2022.
Links | BibTeX | Tags: AMICOS, Analytics, bearings, condition monitoring, damge, Diagnostics, fault detection, Measurements, Mining, mobile robot, Processing, Remote sensing, Robotics, Temperature, thermal hazard
@article{dabek2022automatic,
title = {An Automatic Procedure for Overheated Idler Detection in Belt Conveyors Using Fusion of Infrared and RGB Images Acquired during UGV Robot Inspection},
author = {Przemyslaw Dabek and Jaroslaw Szrek and Radoslaw Zimroz and Jacek Wodecki},
url = {https://doi.org/10.3390/en15020601},
doi = {10.3390/en15020601},
year = {2022},
date = {2022-01-14},
urldate = {2022-01-14},
journal = {Energies},
volume = {15},
number = {2},
pages = {601},
publisher = {Multidisciplinary Digital Publishing Institute},
keywords = {AMICOS, Analytics, bearings, condition monitoring, damge, Diagnostics, fault detection, Measurements, Mining, mobile robot, Processing, Remote sensing, Robotics, Temperature, thermal hazard},
pubstate = {published},
tppubtype = {article}
}
2021
2.
Szrek, Jaroslaw; Zimroz, Radoslaw; Wodecki, Jacek; Michalak, Anna; Goralczyk, Mateusz; Worsa-Kozak, Magdalena
Application of the infrared thermography and Unmanned Ground Vehicle for rescue action support in undergroundmine - the AMICOS project Journal Article
In: Remote Sensing , vol. 13, no. 1, pp. 69, 2021.
Abstract | Links | BibTeX | Tags: AMICOS, Remote sensing, Robotics
@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 = {AMICOS, Remote sensing, Robotics},
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.