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

Asok Ray, Sekhar Tangirala

Research output: Contribution to journalArticle

116 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)443-451
Number of pages9
JournalIEEE Transactions on Control Systems Technology
Volume4
Issue number4
DOIs
StatePublished - Dec 1 1996

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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