Contribution to Mathematical Modelling of Oil Field Data

Abstract:

The paper deals with application of selected suitable analytical methods use to analyse field data from medium off-road military vehicles. Some pieces of information from oil are interpreted thank to diagnostics in form of polluting particles. Such particles represent processes in the engine like wear (e.g. Fe, Cu, Pb, etc.) and oil condition (like e.g. Mn, Si, Zn, etc.). These particles can give us information both about system state and about oil state. Thank to good recording system we have data from field operation available. Therefore we decided to use selected analytical – algebraic methods for determining the specific particles generating trend. Based on the outcomes we hope to be able to determine the system condition (e.g. residual operation life, maintenance modifications in the intervals, etc.). Selected methods like regression analysis, base functions and fuzzy inference system will be used for the data assessment. The results itself might be beneficial in other forthcoming analysis like quality, risk and dependability management processes, e.g. for optimization during an operation and maintenance phase, logistics and spare parts planning, life cycle costing, mission planning, etc.

• Periodical: Applied Mechanics and Materials (Volume 332)
• Pages: 455-462
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.332.455
• Online since: July 2013
• Authors: David Valis, Libor Zak, Josef Glos, Agata Walek
• Keywords: Field Data, Fuzzy Logic, Maintenance Optimization, Off-Line Diagnostics, Regression Analysis, Residual Life Estimation, Tribo-Diagnostics

References

[1] Gesellschaft für Tribologie e.V. GfT Arbeitsblatt 7: Tribologie – Verschleiß, Reibung, Definitionen, Begriffe, Prüfung (GfT, Moers, 2002). In German.

[2] H. Czichos, K-H. Habig: Tribologie-Handbuch; Reibung und Verschleiß, 2nd edition. Weisbaden: Vieweg. 2003,In German.

[3] M. Koucky, D. Valis: Suitable approach for non-traditional determination of system health and prognostics. Zeszyty naukowe, Styczen – Marzec, Vol.1, No 159, pp.123-134. ISSN 1731 – 8157, (2011).

DOI: 10.5604/01.3001.0002.2884

[4] J. Lippay: Tribological diagnostics of heavy of road lorries Tatra 815 engines which operate with OA-M6 ADS II oil. Inauguration Thesis, (Brno: Military Academy, 1991), In Czech.

[5] J. Rak, K. Pietrucha-Urbanik: Some factors of crisis management in water supply system. Environment Protection Engineering, Vol. 34(2) (2008), pp.57-65.

[6] A. Studziński, K. Pietrucha-Urbanik: 2012. Risk Indicators of Water Network Operation. Chemical Engineering Transactions, Vol. 26 (2012), pp.189-194.

[7] J. Stodola, P. Lipták: Combustion Engines Model of Lubricating Oil Filling-up, Modification, and Degradation. In: Transport Means. Kaunas Litva: Univerzita Kaunas, pp.32-36. ISSN 1822-296X. (2010).

[8] J. Stodola, P. Stodola: Mechanical System Wear and Degradation Process Modelling. Transaction of FAMENA, Vol. XXXIV (2010), no. 1, pp.25-33. ISSN 1333-1124.

[9] J. Stodola, P. Stodola: Engine Failure and its Avoidance-Tribology´s Contribution to Efficient Maintenance. In: Proceedings of the International Conference on Military Technologies (ICMT'09). (Brno: University of Defence, 2009). ISBN 978-80-7231-649-6.

[10] D. Vališ, M. Koucký and L. Žák: On approaches for non-direct determination of system deterioration. Eksploatacja i Niezawodnosc – Maintenance and Reliability, vol. 14 (2012), no. 1, pp.33-41. ISSN 1507-2711.