This paper presents a nonlinear stochastic model for the real-time computation of the first two moments of fatigue crack length in metallic materials. The model structure allows estimation of the current stochastic damage state and prediction of the remaining service life based on the underlying principle of Gauss-Markov processes without solving the extended Kalman filter equations in the Wiener integral setting or the Kolmogorov forward equation in the Ito integral setting. This approach is suitable for on-line damage sensing, failure prognosis, life prediction, reliability analysis, decision-making for condition-based maintenance & operation planning, and life extending control in complex dynamic systems. The model results have been verified with experimental data of time-dependent fatigue crack length in specimens made of 2024-T3 Aluminum alloy and 7075-T6 Aluminum alloy.
Publication Source: Trends in NDE Science & Technology; Proceedings of the 14th World Conference on Non-Destructive Testing, New Delhi, 8-13 December 1996.Vol. 3, pages 1825 - 1830 Publisher:Ashgate Publishing Company
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