Investigation on the opportunity to introduce prognostic techniques in railways axles maintenance

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Mattia Vismara

Abstract

In this study the opportunity to introduce PHM (prognostic and health monitoring) concepts into a cracked railway axle management is investigated.
The performances of two different prognostic algorithm are assessed on the basis of their RUL (remaining useful life) predictions accuracy: a prognostic model based on the Bayesian theory and a physical prognostic model. Both models rely on the measured crack size. The measured crack growth measure has been built from simulated probabilistic crack growth path by adding measurements errors. The effect of monitoring frequency and the measurement HW and SW infrastructure size error to RUL predictions’ accuracy is assessed as well, trying to evaluate the hypothetical measuring infrastructure capabilities’ (sensors + layout) effect on the overall PHM predictions. Furthermore the PHM approach is compared to the classical preventive maintenance approach to railway axle maintenance management based on expensive and regular NDT.

How to Cite

Vismara, M. (2011). Investigation on the opportunity to introduce prognostic techniques in railways axles maintenance. Annual Conference of the PHM Society, 3(1). https://doi.org/10.36001/phmconf.2011.v3i1.2072
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Keywords

condition based maintenance (CBM), POD, Railways axles, Crack propagation

References
A.K Sheikh, M. A. (1983). Renewal Analysis Using Bernstein Distribution. Reliability Engineering, 5, 1-19.

A.Saxena, J. C. (2008). Metrics for Evaluating Performance of Prognostic Techniques. International Conference on prognostics and health management, (pp. 1-17). Denver, CO.

Anonymus. (2006). Fracture Mechanics and Fatigue Crack Growth 4.2. NASA Technical report .

C.J. Lu, W. M. (1993). Using Degradation Measures to Estimate a Time-to-Failure Distribution. American Society for Quality , 35 (2), 161-174.

C.P. Lonsdale, D. S. (2004). North american axle failure experience. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit , 218 (4), 293–298.

D. V. Lindley, A. F. (1972). Bayes estimates for the linear model. Journal of the Royal Statistical Society, Series B, Statistical , 34 (1), 1–41.

D.A. Virkler, B. H. (1979). The statistical nature of fatigue crack propagation. ASME, Transactions, Journal of Engineering Materials and Technology , 101, 148-153.
EN13103. (2001). Railway applications – wheelsets and bogies – non powered axles – design method.

Gassner, E. (1956). Performance fatigue testing with respect to aircraft design. In E. Gassner, Fatigue in Aircraft Stuctures. New York: Academic Press.

Hoddinot, D. (2004). Railway axle failure investigations and fatigue crack growth monitoring of an axle. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit , 218, 283–292.

J.L Bogdanoff, F. K. (1985). Probabilistic models of cumulative damage. New York: John Wiley & Sons.

K.Ortiza, A. (1988). Stochastic modeling of fatigue crack growth. Engineering Fracture Mechanics , 29 (3), 317-334.

M. Carboni, S. B. (2007). Effect of probability of detection upon the definition of inspection intervals for railway axles. Proceedings of the Institution of Mechanical Engineers, Part F:
Journal of Rail and Rapid Transit , 221 (3), 409- 417.

N. Gebraeel, J. P. (2008). Prognostic Degradation Models for Computing and Updating Residual Life Distributions in a Time-Varying Environment. IEEE Transaction on Reliability , 57 (4), 539-549.

N. Gebraeel, M. L. (2005). Life distributions from component degradation signals: A Bayesian approach. IIE Trans. , 37 (6), 543–557.

N.Z Gebraeel, K. K. (2009). Predictive Maintenance Management Using Sensor-Based Degradation Models. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 39 (4), 840-849.

R.A. Smith, S. (2004). A brief historical overview of the fatigue of railway axles. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit , 218 (4), 267-277.

S. Beretta, M. C. (2004). Application of fatigue crack growth algorithms to railway axles and comparison of two steel grades. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 218 (4).

S. Beretta, M. C. (2006). Experiments and stochastic model for propagation lifetime of railway axles. Engineering Fracture Mechanics, 73, 2627–2641.

S.Beretta, M. M. (2006). SIF solutions for cracks at notches under rotating bending. Proceedings of the 16th European Conference on Fracture (ECF16). Alexandropoulos.

S.Beretta, M. (2005). Rotating vs. plane bending for crack growth in railway axles. ESIS-TC24 Meeting. Geesthacht.

S.Beretta, M. (2005). Simulation of fatigue crack propagation in railway axles. J ASTM Int , 2 (5), 1-14.

Schijve, J. (2001). Fatigue of structures and materials. Dordrecht: Kluwer Academic Publishers.

U. Zerbst, K. M. (2005). Fracture mechanics in railway applications––an overview. Engineering Fracture Mechanics, 72, 163–194.

U. Zerbst, M. V. (2005). The development of a damage tolerance concept for railway components and its demonstration for a railway axle. Engineering Fracture Mechanics, 72, 209–239.
Section
Technical Papers