Abstract
The paper deals with modern ICT techniques and systems, and mechatronic systems for mining industry, with particular attention paid to results achieved by the authors and their research groups. IT systems concern process and machinery monitoring, fault detection and isolation of processes and machinery, and assessment of risk and hazards in mining industry. Furthermore, innovative applications of AI methods are addressed, including pattern recognition and interpretation for process control, classification of seismic events, estimating loads of conveyors, and the others. Special attention is paid to applications of mechatronic solutions, such as: unmanned working machinery and longwalls in coal mines, and specialised robots for basic work. Mobile robots for inspecting areas of mines affected by catastrophes are presented, too. Moreover, recent communication solutions for collision avoidance, localisation of mining machinery, and wireless transmission are addressed. The paper concludes with most likely development of ICT and mechatronic systems for mining industry.
The paper includes some results achieved during research carried out in the framework of research projects: Disesor partially financed by Polish National Centre for Research and Development under grant No. PBS2/B9/20/2013; TeleRescuer partially financed by the Research Fund for Coal and Steel under grant No. RFCR-CT-2014-00002 and by the Polish Ministry for Science and High Education.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bartelmus, W., Zimroz, R.: Vibration condition monitoring of planetary gearbox under varying external load. Mech. Syst. Signal Proc. 23(1), 246–257 (2009). Special Issue: Non-linear Structural Dynamics
Bartkowiak, A., Zimroz, R.: Outliers analysis and one class classification approach for planetary gearbox diagnosis. J. Phys. Conf. Ser. 305(1), 012031 (2011)
Bartkowiak, A., Zimroz, R.: Dimensionality reduction via variables selection - linear and nonlinear approaches with application to vibration-based condition monitoring of planetary gearbox. Appl. Acoust. 77, 169–177 (2014)
Brzychczy, E.: The intelligent computer-aided support in designing mining operations at underground hard coal mines. In: 23th World Mining Congress, August 11–15 2013, Montreal (2013)
Cempel, C.: Multidimensional condition monitoring of mechanical systems in operation. Mech. Syst. Signal Process. 17(6), 1291–1303 (2003)
Chekushina, E.V., Vorobev, A.E., Chekushina, T.V.: Use of expert systems in the mining. Middle-East J. Sci. Res. 18(1), 1–3 (2013)
Cholewa, W.: Expert systems in technical diagnostics. In: Korbicz, J., Kowalczuk, Z., Kościelny, J., Cholewa, W. (eds.) Fault Diagnosis, pp. 591–631. Springer, Heidelberg (2004)
Cioch, W., Knapik, O., Leśkow, J.: Finding a frequency signature for a cyclostationary signal with applications to wheel bearing diagnostics. Mech. Syst. Signal Process. 1(38), 55–64 (2013)
COIG. http://www.coig.pl/en/mining, (as of Aug. 2016)
CSIRO. Mining safety and automation. http://www.csiro.au/en/Research/EF/Areas/Coal-mining/Mining-safety-and-automation, (as of Aug. 2016)
EC-Europa. https://ec.europa.eu/growth/tools-databases/eip-rawmaterials/en/content/strategic-implementation-plan-sip-0, (as of Aug. 2016)
EIT. http://eitrawmaterials.eu/, (as of Aug. 2016)
EU-Robotics. https://eu-robotics.net/, (as of Aug. 2016)
Golak, S., Wieczorek, T.: Koncepcja system ekspertowego do oceny i poprawy ekoefektywności kopalń (in Polish). Studia Informatica 116(2), 213–222 (2014)
Hofmann, M., Klinkenberg, R.: RapidMiner: Data Mining Use Cases and Business Analytics Applications. Chapman & Hall/CRC, Boca Raton (2013)
IBM. http://www-935.ibm.com/industries/metalsmining/, (as of Aug. 2016)
Janusz, A., Sikora, M., Wróbel, L., Stawicki, S., Grzegorowski, M., Wojtas, P., Slezak, D.: Mining data from coal mines: IJCRS’15 data challenge. In: Yao, Y. (ed.) RSFDGrC 2015. LNCS, vol. 9437, pp. 429–438. Springer, Heidelberg (2015). doi:10.1007/978-3-319-25783-9_38
Kabiesz, J.: Effect of the form of data on the quality of mine tremors hazard forecasting using neural networks. Geotech. Geol. Eng. 24(5), 1131–1147 (2006)
Kadlec, P., Gabrys, B., Strandt, S.: Data-driven soft sensors in the process industry. Comput. Chem. Eng. 33(4), 795–814 (2009)
Kalisch, M., Przystałka, P., Timofiejczuk, A.: A concept of meta-learning schemes for context-based fault diagnosis. In: XV International Technical Systems Degradation Conference, TSD International Conference, Liptovsky Mikulas, 30 March – 2 April 2016, pp. 113–114 (2016)
Kozielski, M., Sikora, M., Wróbel, Ł.: Disesor - decision support system for mining industry. In: Ganzha, M., Maciaszek, L., Paprzycki, M. (eds.) Proceedings of the 2015 Federated Conference on Computer Science and Information Systems, vol. 5 of Annals of Computer Science and Information Systems, pp. 67–74. IEEE (2015)
Leica Geosystems. Autonomous and remote controlled mining. http://mining.leica-geosystems.com/news/all-news/autonomous-and-remote-controlled-mining, (as of Aug. 2016)
Liebowitz, J.: The Handbook of Applied Expert Systems. CRC Press LLC, Boca Raton (1997)
Moczulski, W., Cyran, K., Januszka, M., Novak, P., Timofiejczuk, A.: Telerescuer - an innovative robotized system for supporting mining rescuers by inspecting roadways affected by catastrophes. In: 24th World Mining Congress (2016)
Przystałka, P., Moczulski, W., Timofiejczuk, A., Kalisch, M., Sikora, M.: Development of Expert System Shell for Coal Mining Industry. Springer, Heidelberg (2016)
RapidMiner: RapidMiner software website, August 2016. https://rapidminer.com/
Sáez, J.A., Krawczyk, B., Woźniak, M.: Analyzing the oversampling of different classes, types of examples in multi-class imbalanced datasets. Pattern Recogn. 57(C), 164–178 (2016)
Sikora, M., Moczulski, W., Timofiejczuk, A., Przystałka, P., Ślȩzak, D.: DISESOR: An integrated shell decision support system for systems of monitoring processes, equipment and hazards. In: Mechanizacja, automatyzacja i robotyzacja w górnictwie, pp. 39–47 (2015)
Sikora, M., Przystałka, P., (eds.): Zintegrowany, szkieletowy system wspomagania decyzji dla systemów monitorowania procesów, urza̧dzeń i zagrożeń (in Polish). Publishing House of the Institute for Sustainable Technologies, National Research Institute, Radom, Poland (2016) (in print)
Sokołowski, J., Obuchowski, J., Madziarz, M., Wyłomańska, A., Zimroz, R.: Features based on instantaneous frequency for seismic signals clustering. J. VibroEng. 18(3), 1654–1667 (2016)
Stefaniak, P., Zimroz, R., Bartelmus, W., Hardygóra, M.: Computerised decision-making support system based on data fusion for machinery systems management and maintenance. Appl. Mech. Mater. 683, 108–113 (2014)
Wang, C., Wang, Z.: Design and implementation of safety expert information management system of coal mine based on fault tree. J. Softw. 5(10), 1114–1120 (2010)
Xu, X., Dou, L., Lu, C., Zhang, Y.: Frequency spectrum analysis on micro-seismic signal of rock bursts induced by dynamic disturbance. Min. Sci. Technol. 20(5), 682–685 (2010)
Yingxu, Q., Hongguo, Y.: Design and application of expert system for coal mine safety. In: Second IITA International Conference on Geoscience and Remote Sensing (2010)
Zimroz, R., Hardygóra, M., Błażej, R.: Maintenance of belt conveyor systems in Poland - an overview. In: Proceedings of the 12th International Symposium Continuous Surface Mining - Aachen, pp. 21–30. Springer, Heidelberg (2015)
Zimroz, R., Wodecki, J., Król, R., Andrzejewski, M., Śliwiński, P., Stefaniak, P.: Self-propelled Mining Machine Monitoring System - Data Validation, Processing and Analysis. Springer, Heidelberg (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Moczulski, W., Przystałka, P., Sikora, M., Zimroz, R. (2016). Modern ICT and Mechatronic Systems in Contemporary Mining Industry. In: Flores, V., et al. Rough Sets. IJCRS 2016. Lecture Notes in Computer Science(), vol 9920. Springer, Cham. https://doi.org/10.1007/978-3-319-47160-0_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-47160-0_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-47159-4
Online ISBN: 978-3-319-47160-0
eBook Packages: Computer ScienceComputer Science (R0)