Journal of Korean Society for Quality Management (품질경영학회지)

Korean Society for Quality Management (한국품질경영학회)
권호 표지

Statistical Analysis and Comparison of Fatigue Curve Models

피로곡선 모형의 통계적 분석 및 비교

  • 서순근 (동아대학교 공과대학 산업시스템공학과) ;
  • 조유희 (동아대학교 공과대학 산업시스템공학과)
  • Published : 2003.06.01
Download PDF
⟨ Previous Next ⟩

Abstract

The fatigue has been considered to the most important failure mode where optimal design or reliability prediction of the machinery in aircraft, atomic reactors, and structure systems, etc., is required. When the statistical analysis of fatigue life data is performed, some difficulties are present because of the following facts : nonlinear relationship, heteroscedastic data, large scatter in the data, censored data (runouts), and existence of fatigue limit. To find the S-N curve models that characterize fatigue strength better, this research compares existing fatigue curve models developed recently in terms of the residual mean square and the estimate of fatigue limit, etc. for various fatigue data sets.

Keywords

References

  1. ASTM(1981). Statistical Analysis of Fatigue Data (ASTM STP 744), eds. Little, R. E. and Ekrall, J. C., The American Society for Testing and Materials
  2. Castillo, E. and Hadi, A. S.(1995), 'Modeling Lifetime Data with Application to Fatigue Models', Journal of the American Statistical Association, Vol. 90, pp. 1041-1054 https://doi.org/10.2307/2291341
  3. Cohen A. and Whitten, B. J.(1988), Parameter Estimation in Reliability and Life Span Models, Marcel Dekker
  4. Dupuis, D. J.(1998), 'Parameter andQuantile Estimation for a FatigueModel', Computational Statistics & Data Analysis, Vol. 29, pp. 55-68 https://doi.org/10.1016/S0167-9473(98)00050-4
  5. Efron, B. and Tibshirani, R. J.(1993),An Introduction to the Bootstrap, Chapman and Hall
  6. Little, R. E. and Jebe. E. H.(1975). Statistical Design of FatigueExperiments, Applied SciencePublishers
  7. MathSoft(2000), S-Plus 2000 Programmer's Guide, MathSoft Inc..
  8. Meeker, W. Q. and Escobar, L.A.(1998), Statistical Methods forReliability Data, John Wiley andSons
  9. Nelson, W.(1984), 'Fitting of FatigueCurves with Nonconstant Standard Deviation to Data with Runouts', Journal of Testing and Evaluation,Vol. 12, pp. 69-77 https://doi.org/10.1520/JTE10700J
  10. Nelson, W.(1990), AcceleratedTesting : Statistical Models, TestPlans. and Data Analysis, John Wileyand Sons
  11. Pascual, F. G. and Meeker, W.Q.(1997), 'Analysis of Fatigue Datawith Runouts Based on a Modelwith Nonconstant Standard Deviation and a Fatigue Limit Parameter', Journal of Testing and Evaluation, Vol. 25, pp. 292-301 https://doi.org/10.1520/JTE11341J
  12. Pascual, F. G. and Meeker, W.Q.(1999), 'Estimating Fatigue Curveswith the Random Fatigue-LimitModel', Technometrics, Vol. 41, pp.277-302 https://doi.org/10.2307/1271342
  13. Schmee, J. and Hahn, G. J.(1979),'A Simple Method for RegressionAnalysis With Censored Data'Technometrics, Vol. 21, pp. 417-434 https://doi.org/10.2307/1268280
  14. Schmee, J. and Hahn, G. J.(1981),'A Computer Program for SimpleLinear Regression with CensoredData', Journal of Quality Technology,Vol. 13, pp. 264-269
  15. Shen, C. L.(1994), 'The Statistical Analysis of Fatigue Data', Ph. D. Dissertation, University of Arizona