Smart Structures and Systems

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Reliability analysis for fatigue damage of railway welded bogies using Bayesian update based inspection

  • Zuo, Fang-Jun (School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China) ;
  • Li, Yan-Feng (Center for System Reliability and Safety, University of Electronic Science and Technology of China) ;
  • Huang, Hong-Zhong (Center for System Reliability and Safety, University of Electronic Science and Technology of China)
  • Received : 2017.05.08
  • Accepted : 2018.03.19
  • Published : 2018.08.25
⟨ Previous Next ⟩

Abstract

From the viewpoint of engineering applications, the prediction of the failure of bogies plays an important role in preventing the occurrence of fatigue. Fatigue is a complex phenomenon affected by many uncertainties (such as load, environment, geometrical and material properties, and so on). The key to predict fatigue damage accurately is how to quantify these uncertainties. A Bayesian model is used to account for the uncertainty of various sources when predicting fatigue damage of structural components. In spite of improvements in the design of fatigue-sensitive structures, periodic non-destructive inspections are required for components. With the help of modern nondestructive inspection techniques, the fatigue flaws can be detected for bogie structures, and fatigue reliability can be updated by using Bayesian theorem with inspection data. A practical fatigue analysis of welded bogies is utilized to testify the effectiveness of the proposed methods.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China

References

  1. Aid, A., Amrouche, A., Bouiadjra, B.B., Benguediab, M. and Mesmacque, G. (2011), "Fatigue life prediction under variable loading based on a new damage model", Mater. Des., 32(1), 183-191. https://doi.org/10.1016/j.matdes.2010.06.010
  2. Chiachio, J., Chiachio, M., Saxena, A., Sankararaman, S., Rus, G. and Goebel, K. (2015), "Bayesian model selection and parameter estimation for fatigue damage progression models in composites", Int. J. Fatigue, 70, 361-373. https://doi.org/10.1016/j.ijfatigue.2014.08.003
  3. Cross, R., Makeev, A. and Armanios, E. (2007), "Simultaneous uncertainty quantification of fracture mechanics based life prediction model parameters", Int. J. Fatigue, 29(8), 1510-1515. https://doi.org/10.1016/j.ijfatigue.2006.10.027
  4. Dong, P. (2001), "A structural stress definition and numerical implementation for fatigue analysis of welded joints", Int. J. Fatigue, 23(10), 865-876. https://doi.org/10.1016/S0142-1123(01)00055-X
  5. Edwards, G. (1984), "A bayesian procedure for drawing inference from random data", Reliab. Eng., 9(1), 1-17. https://doi.org/10.1016/0143-8174(84)90002-7
  6. Fatemi, A. and Yang, L. (1998), "Cumulative fatigue damage and life prediction theories: a survey of the state of the art for homogenous materials", Int. J. Fatigue, 20(1): 9-34. https://doi.org/10.1016/S0142-1123(97)00081-9
  7. Foreman, R.G., Keart, V.E. and Engle, R.M. (1967), "Numerical analysis of crack propagation in cycle-loaded structures", J. Basic Eng., 89(3), 459-464. https://doi.org/10.1115/1.3609637
  8. Gelman, A., Carlin, J.B., Stern, H.S., Dunson, D.B., Vehtari, A. and Rubin, D.B. (2014), "Bayesian Data Analysis", CRC press, Boca Raton, FL, USA.
  9. Ghodrati, A., Seyed, R. and Bagheri, A. (2011), "Damage detection in plates based on pattern search and genetic algorithms," Smart Struct. Syst., 7(2), 117-132. https://doi.org/10.12989/sss.2011.7.2.117
  10. Guo, J., Li Z. and Pecht, M. (2015), "A Bayesian approach for Li-Ion battery capacity fade modeling and cycles to failure prognostics", J. Power Sources, 281, 173-184. https://doi.org/10.1016/j.jpowsour.2015.01.164
  11. Huang, H. and Yang, J.N. (2008), "Damage identification of substructure for local health monitoring". Smart Struct. Syst., 4(6), 795-807. https://doi.org/10.12989/sss.2008.4.6.795
  12. Huang, H.Z., Cui, P., Peng, W., Gao, H. and Wang, H.K. (2014), "Fatigue lifetime assessment of aircraft engine disc via multisource information fusion", Int. J. Turbo Jet Eng., 31(2), 167-174. https://doi.org/10.1515/tjj-2013-0043
  13. Huang, H.Z., Huang, C.G., Peng, Z., Li, Y.F. and Yin, H. (2017), "Fatigue life prediction of fan blade using nominal stress method and cumulative fatigue damage theory", Int. J. Turbo Jet Eng., DOI: https://doi.org/10.1515/tjj-2017-0015.
  14. Li, X.Y., Huang, H.Z., Li, Y.F. and Zio, E. (2018), "Reliability assessment of multi-state phased mission system with non-repairable multi-state components", Appl. Math. Model., 61, 181-199. https://doi.org/10.1016/j.apm.2018.04.008
  15. Li, Y.F., Zhu, S.P., Li, J., Peng, W. and Huang, H.Z. (2015), "Uncertainty analysis in fatigue life prediction of gas turbine blades using Bayesian inference", Int. J. Turbo Jet Eng., 32(4), 319-324.
  16. Li, Z., Deng, Y. and Mastrangelo, C. (2015), "Model selection for degradation-based Bayesian reliability analysis", J. Manuf. Syst., 37, 72-82. https://doi.org/10.1016/j.jmsy.2015.09.005
  17. Liu, Y. and Mahadevan, S. (2005), "Multiaxial high-cycle fatigue criterion and life prediction for metals", Int. J. Fatigue, 27(7), 790-800. https://doi.org/10.1016/j.ijfatigue.2005.01.003
  18. Luo, J. and Bowen, P. (2003), "A probabilistic methodology for fatigue life prediction", Acta. Mater., 51(12), 3537-3550. https://doi.org/10.1016/S1359-6454(03)00172-1
  19. Lv, Z., Huang, H.Z., Gao, H, Zuo, F.J. and Wang, H.K. (2015), "Lifetime prediction for turbine discs based on a modified Walker strain model", J. Mech. Sci. Techno., 29(10), 4143-4152. https://doi.org/10.1007/s12206-015-0908-1
  20. Makeev, A., Nikishkov, Y. and Armanios, E. (2007), "A concept for quantifying equivalent initial flaw size distributions in fracture mechanics based life prediction models", Int. J. Fatigue, 29(1), 141-145. https://doi.org/10.1016/j.ijfatigue.2006.01.018
  21. Mahadevan, S. and Rebba, R. (2006), "Validation of reliability computational models using Bayes networks", Reliab. Eng. Syst. Safe., 87(2), 223-232. https://doi.org/10.1016/j.ress.2004.05.001
  22. Mi, J., Li, Y.F., Peng, W. and Huang, H.Z. (2018), "Reliability analysis of complex multi-state system with common cause failure based on evidential networks", Reliab. Eng. Syst. Safe., 174, 71-81. https://doi.org/10.1016/j.ress.2018.02.021
  23. Paris, P.C. (1964), "The fracture mechanics approach to fatigue", New York: Syracuse University Press, 107-132.
  24. Rebba, R. (2005), "Model validation and design under uncertainty", PhD dissertation, Vanderbilt University, Nashville.
  25. Richard, C. and Andrew, M. (2007), "Simultaneous uncertainty quantification of fracture mechanics based life prediction model parameters", Int. J. Fatigue, 29(8), 1510-1515. https://doi.org/10.1016/j.ijfatigue.2006.10.027
  26. Sankararaman, S., Ling, Y., Shantz, C. and Mahadevan, S. (2009), "Uncertainty quantification in fatigue damage prognosis", The proceedings of the 1st annual conference of the Prognostics and Health Management Society, San Diego, CA. September 27-October 1.
  27. Sankararaman, S., Ling Y. and Mahadevan, S. (2010), "Statistical inference of equivalent initial flaw size with complicated geometry and multi-axial loading", Int. J. Fatigue, 32(10), 1689-1700. https://doi.org/10.1016/j.ijfatigue.2010.03.012
  28. Sankararaman, S., Ling, Y., Shantz, C. and Mahadevan, S. (2011), "Inference of equivalent initial flaw size under multiple sources of uncertainty", Int. J. Fatigue, 33(2), 75-89. https://doi.org/10.1016/j.ijfatigue.2010.06.008
  29. Soares, C. G. and Garbatov, Y. (1999), "Reliability of maintained, corrosion protected plates subjected to non-linear corrosion and compressive loads", Mar. Struct., 12(6), 425-445. https://doi.org/10.1016/S0951-8339(99)00028-3
  30. Weertman, J. (1966), "Rate of growth of fatigue cracks calculated from the theory of infinitesimal dislocations distributed on a plane", Int. J. Frac. Mech., 2(2), 460-467. https://doi.org/10.1007/BF00183823
  31. Xiang, J., Matsumoto, T., Long, J., Wang, Y. and Jiang, Z. (2012), "A simple method to detect cracks in beam-like structures", Smart Struct. Syst., 9(4), 335-353. https://doi.org/10.12989/sss.2012.9.4.335
  32. Zheng, B., Huang, H.Z., Guo, W., Li, Y.F. and Mi, J. (2018), "Fault diagnosis method based on supervised particle swarm optimization classification algorithm", Intell. Data Anal., 22(1), 191-210. https://doi.org/10.3233/IDA-163392
  33. Zhang, R.X. and Mahadevan, S. (2000), "Model uncertainty and Bayesian updating in reliability-based inspection", Struct. Saf., 22(2), 145-160. https://doi.org/10.1016/S0167-4730(00)00005-9
  34. Zhao, Z., Haldar, A. and Breen, Jr. (1994), "Fatigue reliability updating through inspection of steel bridges", J. Struct. Eng., 120(5), 1624-1641. https://doi.org/10.1061/(ASCE)0733-9445(1994)120:5(1624)
  35. Zheng, R. and Ellingwood, B. (1998), "Role of non-destructive evaluation in time-dependent reliability analysis", Struct. Saf., 20(4), 303-323. https://doi.org/10.1016/S0167-4730(98)00020-4
  36. Zhou, J., Huang, H.Z. and Peng, Z. (2017), "Fatigue life prediction of turbine blades based on modified equivalent strain model", J. Mech. Sci. Technol., 31(9), 4203-4213 https://doi.org/10.1007/s12206-017-0818-5

Cited by

  1. Fatigue Reliability Analysis of Motor Hanger for High-Speed Train Based on Bayesian Updating and Subset Simulation vol.2020, pp.None, 2018, https://doi.org/10.1155/2020/3012471