Our team worked hard until the very end of 2020, and we can see the fruits of this effort as the new year begins. Part of our articles, which have been submitted at the end of December to the: Energies, Sensors, and Remote Sensing journals by MDPI, together with Elsevier’s Measurement is now ready for you to read!
In the article published in the special issue of Energies journal: “Modelling and Calculation of Raw Material Industry” Dr Pavlo Krot and Prof. Radosław Zimroz, together with co-authors from the Institute of Engineering Mechanics and Transport of the Lviv Polytechnic National University propose a design of a dual-frequency vibrating drive, that can allow achieving better energy efficiency of vibrating machines.
The work of MSc. Anna Michalak, Dr. Jacek Wodecki, Dr. Agnieszka Wyłomańska, Prof. Radosław Zimroz in cooperation with the engineer Michał Drozda from the Polkowice ore beneficiation plant has been published in the Sensors’ special issue: “Sensing Technology and Data Interpretation in Machine Diagnosis and Systems Condition Monitoring”. The authors presented the initial approach to constructing the signal model of the industrial vibrating sieving screen suspension vibrations, which can be used for condition monitoring purposes.
@article{Michalak2021,
title = {Model of the Vibration Signal of the Vibrating Sieving Screen Suspension for Condition Monitoring Purposes},
author = {Anna Michalak and Jacek Wodecki and Michal Drozda and Agnieszka Wylomanska and Radoslaw Zimroz},
url = {https://www.mdpi.com/1424-8220/21/1/213},
doi = {https://doi.org/10.3390/s21010213},
year = {2021},
date = {2021-01-01},
journal = {Sensors},
volume = {21},
number = {1},
pages = {213},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Another special issue of the Sensors journal – “Sensors Solutions for Mapping Mining Environments”, published the article by Dr. Jarosław Szrek, MSc. Paweł Trybała, Prof. Radosław Zimroz, Dr. Jacek Wodecki, MSc. Anna Michalak, MSc. Mateusz Góralczyk, and Dr. Magdalena Worsa Kozak, which presents an evaluation of some techniques of mobile inspection robots localization.
@article{Szrek2021,
title = {Accuracy Evaluation of Selected Mobile Inspection Robot Localization Techniques in a GNSS-Denied Environment },
author = {Jaroslaw Szrek and Pawel Trybala and Mateusz Góralczyk and Anna Michalak and Bartlomiej Zietek and Radoslaw Zimroz},
url = {https://www.mdpi.com/1424-8220/21/1/141},
doi = {https://doi.org/10.3390/s21010141},
year = {2021},
date = {2021-01-01},
journal = {Sensors},
volume = {21},
number = {1},
pages = {141},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In Remote Sensing’s – “Remote Sensing Solutions for Mapping Mining Environments” special issue Dr. Jarosław Szrek, Prof. Radosław Zimroz, Dr. Jacek Wodecki, MSc. Anna Michalak, MSc. Mateusz Góralczyk and Dr. Magdalena Worsa Kozak are showing how thermography and unmanned ground vehicles (UGVs) can aid rescue actions in underground mines.
@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.
In the Data Fusion, Integration and Advances of Non-destructive Testing Methods in Engineering and Geosciences, in turn, MSc. Paweł Trybała, Dr. Jan Blachowski, Dr. Ryszard Błażej, and Prof. Radosław Zimroz described a remote sensing method for the assessment of belt conveyor condition utilizing Terrestrial Laser Scanner (TLS).
@article{Trybala2020,
title = {Damage Detection Based on 3D Point Cloud Data Processing from Laser Scanning of Conveyor Belt Surface},
author = {Pawel Trybala and Jan Blachowski and Ryszard Blazej and Radoslaw Zimroz},
url = {https://www.mdpi.com/2072-4292/13/1/55},
doi = {https://doi.org/10.3390/rs13010055},
year = {2020},
date = {2020-12-25},
journal = {Remote Sensing},
volume = {13},
number = {1},
pages = {55},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Moreover, MSc. Anna Michalak, Dr. Jacek Wodecki, Dr. Agnieszka Wyłomańska, and Prof. Radosław Zimroz once again appear in Measurement! This time, they present the study on the influence of the non-Gaussian noise on the effectiveness of cyclostationary analysis, and present a novel procedure for local damage detection based on vibration data analysis in the presence of Gaussian and heavy-tailed impulsive noise.
@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}
}
@article{WODECKI2021108400,
title = {Local damage detection based on vibration data analysis in the presence of Gaussian and heavy-tailed impulsive noise},
author = {Jacek Wodecki and Anna Michalak and Radoslaw Zimroz},
url = {http://www.sciencedirect.com/science/article/pii/S0263224120309349},
doi = {https://doi.org/10.1016/j.measurement.2020.108400},
issn = {0263-2241},
year = {2021},
date = {2021-01-01},
journal = {Measurement},
volume = {169},
pages = {108400},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
