A nonlinear stochastic model of fatigue crack length for on-line damage sensing

This paper presents a nonlinear stochastic model of fatigue crack length in metallic materials for damage estimation and life prediction of machinery components. The model structure is built upon on the underlying principle of the Karhunen-Loeve (K-L) expansion. The statistic of the (non-stationary) crack length process is generated without solving the extended Kalman filter equation in the Wiener integral setting or the Kolmogorov forward equation in the Ito integral setting. The model results have been verified with experimental data of time-dependent fatigue crack statistics for 2024-T3 and 7075-T6 aluminum alloys.