Uncertainty Identification of Damage Growth Parameters using Health Monitoring Data and Nonlinear Regression

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Alexandra Coppe Raphael T. Haftka Nam Ho Kim

Abstract

When it comes to identifying model parameters such as damage growth parameters in Paris law for example, Bayesian inference is a popular method. However, it involves substantial computational cost, especially with increasing number of parameters. When the prior distribution for the parameters is not narrow, non-linear regression may provide almost all the benefits of Bayesian updating at a small fraction of the computational cost. In this paper we apply this approach to the identification of damage growth parameters. As a first step we simplify the problem to a single parameter in order to compare it with the same problem solved using Bayesian inference. We then discuss the issues related to uncertainty quantification in the case of a highly non-linear problem.

How to Cite

Coppe, A., T. Haftka, R., & Ho Kim, N. (2010). Uncertainty Identification of Damage Growth Parameters using Health Monitoring Data and Nonlinear Regression. Annual Conference of the PHM Society, 2(1). https://doi.org/10.36001/phmconf.2010.v2i1.1750
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Keywords

remaining useful life (RUL), structural health monitoring, Uncertainty Quantification, prognosis, non-linear least square, damage propagation

References
(Coppe et al., 2009) A. Coppe, R. T. Haftka, N. H. Kim, and F. G. Yuan, Reducing uncertainty in damage growth properties by structural health monitoring, Annual Conference of the Prognostics and Health Management Society, 27 September - 1 October, 2009, San Diego, CA (Coppe et al., 2010) A. Coppe, R. T. Haftka, N. H. Kim and F. G. Yuan, Uncertainty reduction of damage growth properties using structural health monitoring, Journal of Aircraft, accepted, 2010 (Gallagher et al., 1984) J.P., Gallagher, F.J., Giessler, A.P, Berens AP, and R.M., Engle Jr, USAF damage tolerant design handbook: guidelines for the analysis and design of damage tolerant aircraft structures, Final report. 1984. (Giurgiutiu, 2008) V. Giurgiutiu, Structural health monitoring with piezoelectric wafer active sensors,Academic Press, 2008 (Lawson and Hanson, 1995) C.L. Lawson and R.J. Hanson, Solving least squares problems, Society of Industrial Mathematics, 1995 (Paris et al., 1999) P. C. Paris, H. Tada, and J. K. Donald. Service load fatigue damage—a historical perspective, International Journal of fatigue, vol. 21, pp. 35-46, 1999. (Seber and Wild, 1989) G.A.F Seber and C.J. Wild. Nonlinear Regression. New York: John Wiley and Sons, 1989. (Thomas, 1986) L. C. Thomas, A survey of maintenance and replacement models for maintainability and reliability of multi-item systems, Reliability Engineering, 16(4), 1986, 297309
Section
Poster Presentations

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