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

Author

Ray, Asok ; Tangirala, Sekhar

Author_Institution

Dept. of Mech. Eng., Pennsylvania State Univ., University Park, PA, USA

Volume

4

fYear

1996

fDate

11-13 Dec 1996

Firstpage

3676

Abstract

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

Keywords

aluminium alloys; fatigue cracks; fatigue testing; life testing; stochastic processes; 2024-T3 Al alloy; 7075-T6 Al alloy; Al-Cu-Mg; Al-Zn-Mg; Karhunen-Loeve expansion; damage estimation; fatigue crack length; life prediction; machinery components; metallic materials; nonlinear stochastic model; nonstationary crack length process; on-line damage sensing; statistic; time-dependent fatigue crack statistics; Fatigue; Indium tin oxide; Inorganic materials; Integral equations; Life estimation; Machinery; Nonlinear equations; Predictive models; Statistics; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1996., Proceedings of the 35th IEEE Conference on

Conference_Location

Kobe

ISSN

0191-2216

Print_ISBN

0-7803-3590-2

Type

conf

DOI

10.1109/CDC.1996.577214

Filename

577214