Approaches in Correlation Analysis and Application on Oil Field Data

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The paper deals with selected approaches which unite several correlation analysis principles. Field data very often has various forms and contents. The comparison of different approaches will help to determine more precisely which correlation analysis is better for assessing input and output data. In this paper we introduce several correlation principles which can help to select the most suitable correlation approach. We present a traditional correlation analysis and compare it with Pearson and Spearman correlation coefficients. The value of our article lies in comparing several different approaches of the correlation analysis in which the oil field data from diesel combustion engine are used

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77-82

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June 2016

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© 2016 Trans Tech Publications Ltd. All Rights Reserved

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[1] J. Anděl: Statistical methods, Matfyzpress, Prague (2003).

Google Scholar

[2] K. Pietrucha-Urbanik: Failure analysis and assessment on the exemplary water supply network, Engineering Failure Analysis, Volume 57 (2015), p.137–142.

DOI: 10.1016/j.engfailanal.2015.07.036

Google Scholar

[3] D. Valis, L. Zak & O. Pokora: On approaches for non-direct determination of system deterioration, Eksploatacja i Niezawodnosc - Maintenance and Reliability, 14(1) (2014), pp.33-41.

Google Scholar

[4] J. Stodola, & P. Stodola: Mechanical System Wear and Degradation Process Modelling, Transactions of Famena, 34(4)(2010), p- 19-32.

Google Scholar

[5] A. Glowacz: Diagnostics of direct current machine based on analysis of acoustic signals with the use of symlet wavelet transform and modified classifier based on words, Eksploatacja i Niezawodnosc-Maintenance and Reliability, 16(4) (2014).

Google Scholar

[6] A. Glowacz: Diagnostics of induction motor based on analysis of acoustic signals with the application of eigenvector method and k-nearest neighbour classifier, Archives of metallurgy and materials, 57(2) (2012a), pp.403-407.

DOI: 10.2478/v10172-012-0039-y

Google Scholar

[7] A. Glowacz: Diagnostics of dc machine based on analysis of acoustic signals with application of mfcc and classifier based on words, Archives of metallurgy and materials, 57(1) (2012b), pp.179-183.

DOI: 10.2478/v10172-012-0007-6

Google Scholar

[8] K. Pietrucha-Urbanik: Assessment model application of water supply system management in crisis situations, Global NEST Journal, 16(5) (2014), pp.893-900.

DOI: 10.30955/gnj.001414

Google Scholar

[9] K. Pietrucha-Urbanik: Failure Prediction in Water Supply System – Current Issues, Theory and Engineering of Complex Systems and Dependability, Advances in Intelligent Systems and Computing Volume 365 (2015), pp.351-358.

DOI: 10.1007/978-3-319-19216-1_33

Google Scholar

[10] J. Stodola & P. Stodola: Engine Failure and its Avoidance-Tribology´s Contribution to Efficient Maintenance. In: ICMT'09, University of Defence, Brno (2009).

Google Scholar

[11] D. Vališ & L. Žák: Assessment of Off-line Diagnostic Oil Data with Using Selected Mathematical Tools, in: Applied Mechanics and Materials. Trans Tech Publications, Switzerland (2015), pp.141-146.

DOI: 10.4028/www.scientific.net/amm.772.141

Google Scholar

[12] A. Breznicka, A. Chovanec and J. Stodola: Discrete simulation with a variable time step in assessing costs to mission. In: ICMT'15, University of Defence, Brno (2015).

DOI: 10.1109/miltechs.2015.7153684

Google Scholar

[13] A. Chovanec & A. Breznicka: Modeling a Stochastic Approach to the Cost of Maintenance, in: Transport Means (2014), pp.453-456.

Google Scholar

[14] T. Cisowski & J. Stoklosa: Intermodal transport over short and long distances, Eksploatacja i Niezawodnosc - Maintenance and Reliability, 3 (2008), pp.77-82.

Google Scholar

[15] K. Pietrucha-Urbanik: Assessment model application of water supply system management in crisis situations, Global NEST Journal, 16(5) (2014), pp.893-900.

DOI: 10.30955/gnj.001414

Google Scholar

[16] D. Mazurkiewicz: Computer-aided maintenance and reliability management systems for conveyor belts, Eksploatacja i Niezawodnosc - Maintenance and Reliability, 16(3) (2014), pp.377-382.

Google Scholar

[17] D. Mazurkiewicz: Tests of extendability and strength of adhesive-sealed joints in the context of developing a computer system for monitoring the condition of belt joints during conveyor operation, Eksploatacja i Niezawodnosc - Maintenance and Reliability, 3 (2010).

Google Scholar

[18] D. Mazurkiewicz: A knowledge base of the functional properties of the conveyor belt adhesive joint for fem simulation of its stress and strain state, Journal of adhesion science and technology, 26(10-11), pp.1429-1442.

DOI: 10.1163/156856111x618308

Google Scholar

[19] S. Cornak et al: Lifetime extension of engine oil using additives, in: MendelNet (2011), pp.905-914.

Google Scholar

[20] L. Novák, & Š. Čorňák: A contribution to shooting resistance evaluation of military vehicles, in ICMT´15, University of Defence, Brno (2015).

Google Scholar

[21] S. Cornak et al: Perspective methods of vehicles maintenance, in: Transport Means (2006), pp.183-186.

Google Scholar

[22] A. Kierzkowski & T. Kisiel: Functional Readiness of the Check-In Desk System at an Airport, Theory and Engineering of Complex Systems and Dependability, Advances in Intelligent Systems and Computing Vol. 365 (2015), pp.223-233.

DOI: 10.1007/978-3-319-19216-1_21

Google Scholar

[23] A. Kierzkowski & T. Kisiel: Functional Readiness of the Security Control System at an Airport with Single-Report Streams, Theory and Engineering of Complex Systems and Dependability, Advances in Intelligent Systems and Computing Vol. 365 (2015).

DOI: 10.1007/978-3-319-19216-1_20

Google Scholar

[24] M. Zajac: Principles Oof Work Load in Intermodal Transshipment Point, in. CLC (2013), pp.685-690.

Google Scholar

[25] M. Zajac & J. Swieboda: An Unloading Work Model at an Intermodal Terminal, Theory and Engineering of Complex Systems and Dependability, Advances in Intelligent Systems and Computing Vol. 365 (2015), pp.573-582.

DOI: 10.1007/978-3-319-19216-1_55

Google Scholar