Abstract
Continuous improvement of production efficiency, safety and reliability of machines’ operation requires implementation of modern technology in the company, including monitoring systems, IT solutions, computer aided management tools etc. Gathering of data describing processes, extraction of information and knowledge discovery in automatic way seem to be key strategy in order to enhance company’s performance in many contexts. In this paper we will refer to the current status of the system being developed in one of the biggest Polish mining companies. A special attention will be paid to signal validation, pre-processing and analysis in order to retrieve unknown knowledge about machine condition, processes executed on a daily basis and machine/operator performance.
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References
Description of SMIFU project. http://www.rocktechcentre.se/core-business/smifu/
The I2Mine Website (Innovative Technologies and Concepts for the Intelligent Deep Mine of the Future), i2mine.eu/
http://www.nrcan.gc.ca/mining-materials/green-mining/8178, Website of Natural Recourses of Canada
Andrzejewski M, Sliwinski P, Zimroz R (2014) Monitoring Samojezdnych Maszyn Gorniczych, jako narzedzie do optymalizacji procesu wydobycia urobku w kopalniach KGHM Polska Miedz S.A. Proceedings of the 23rd School of Underground Mining, Krakow, 24–28/02/2014 / Instytut Gospodarki Surowcami Mineralnymi i Energia Polskiej Akademii Nauk, Katedra Gornictwa Podziemnego. Akademia Gorniczo-Hutnicza. Krakow : Szkola Eksploatacji Podziemnej, pp 1–10
Dyczko et al. Koncepcja monitoringu i transmisji danych technologicznych pracy samojezdnych maszyn górniczych w KGHM Polska Miedź S.A. (in Polish), unpublishedtechnical report prepared for KGHM PM SA
Kicki J, Dyczko A (2010) The concept of automation and monitoring of the production process in an underground mine. New Tech Technol Min Proc Sch Undergr Min, pp 245–253
Kohler JL, SottileJr J, Cawley JC (1994) On-board electrical diagnostic system to improve the availability of continuous mining machines. Min Eng 46(8):987–990
Luo C, Li W, Wang Y, Fan Q, Yang H (2013) A distributed positioning detection method of shearer under wireless sensor networks. J Comput Inf Syst 9(9):3619–3626
McBain J, Timusk M (2012) Software architecture for condition monitoring of mobile underground mining machinery a framework extensible to intelligent signal processing and analysis. In: IEEE conference on prognostics and health management (PHM), pp 1–12. doi:10.1109/ICPHM.2012.6299543
Okrent K, Studying the impact of the drilling process on the durability of cutting tools, PhD Thesis (in Polish), available at: http://winntbg.bg.agh.edu.pl/rozprawy2/10566/full10566.pdf
Ralston JC, Hainsworth, DW, McPhee RJ, Reid DC, Hargrave CO (2003) Application of signal processing technology for automatic underground coal mining machinery. In: Proceedings. (ICASSP’03). IEEE international conference on acoustics, speech, and signal processing, vol 2, pp 249–252. doi:10.1109/ICASSP.2003.1202341
Zimroz R, Wodecki J, Krol R, Andrzejewski M, Sliwinski P, Stefaniak PK (2014) Self-propelled mining machine monitoring system—data validation, processing and analysis mine planning and equipment selection. In: Carsten D, Raj S (eds) Proceedings of the 22nd MPES conference, Dresden, Germany, vol. 2, 14th–19th Oct 2013. Springer, Berlin, pp 1285–1294
Wyłomańska A, Zimroz R (2014) Signal segmentation for operational regimes detection of heavy duty mining mobile machines—a statistical approach. Diagnostyka 15(2):33–42
Wyłomańska A, Zimroz R (2014) Signals analysis from LHD mining machine on-board monitoring system. In: Proceedings of XIXth symposium VISHNO (Vibration, SHocks and Noise), France
Wyłomańska A, Zimroz R (2015) The analysis of stochastic signal from LHD mining machine. Stochastic models, statistics and their applications. Springer proceedings in mathematics & statistics, vol 122, pp 469–478
Wyłomańska A, Zimroz R (2014) Temperature signal analysis for processes and condition monitoring of LHD mining machines. In: 13th international technical systems degradation conference. Liptovski Mikulas, Slovakia
Ray A (1991) An introduction to sensor signal validation in redundant measurement systems control systems, IEEE 11(2):44–49
Jablonski A, Barszcz T (2013) Validation of vibration measurements for heavy duty machinery diagnostics. Mech Syst Signal Process 38(1):248–263
Bartkowiak A, Zimroz R (2011) Outliers analysis and one class classification approach for planetary gearbox diagnosis. J Phy Conf Ser 305(1):012031
Bartkowiak A, Zimroz R (2014) Dimensionality reduction via variables selection—linear and non-linear approaches with application to vibration-based condition monitoring of planetary gearbox. Appl Acoust 77:169–177
Acknowledgments
Pawel Stefaniak and Radoslaw Zimroz are supported by I2Mine Project (KGHM Cuprum).
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Stefaniak, P.K., Zimroz, R., Sliwinski, P., Andrzejewski, M., Wyłomanska, A. (2016). Multidimensional Signal Analysis for Technical Condition, Operation and Performance Understanding of Heavy Duty Mining Machines. In: Chaari, F., Zimroz, R., Bartelmus, W., Haddar, M. (eds) Advances in Condition Monitoring of Machinery in Non-Stationary Operations. CMMNO 2014. Applied Condition Monitoring, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-319-20463-5_15
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DOI: https://doi.org/10.1007/978-3-319-20463-5_15
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