Stochastic modeling of fatigue crack dynamics for on-line failure prognostics

被引：97
|
作者：
Ray, A
Tangirala, S
机构：
[1] Mechanical Engineering Department, Pennsylvania State University, University Park
来源：
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY | 1996年 / 4卷 / 04期
基金：
美国国家航空航天局; 美国国家科学基金会;
关键词：
D O I：
10.1109/87.508893
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a nonlinear stochastic model of fatigue crack dynamics for real-time computation of the time-dependent damage rate and accumulation in mechanical structures. The model configuration allows construction of a filter for estimation of the current damage state and prediction of the remaining service life based on the underlying principle of extended Kalman filtering instead of solving the Kolmogorov forward equation. This approach is suitable for on-line damage sensing, failure prognosis, life prediction, reliability analysis, decision-making for condition-based maintenance and operation planning, and life extending control in complex dynamical systems. The model results have been verified by comparison with experimentally generated statistical data of time-dependent fatigue cracks in specimens made of 2024-T3 aluminum alloy.
引用
收藏
页码：443 / 451
页数：9
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