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

Asok Ray, Sekhar Tangirala

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

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 Karhunen-Loeve (K-L) expansion. The statistics 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 experimentally data of time-dependent fatigue crack statistics for 2024-T3 and 7075-T6 Aluminum alloys.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Conference on Decision and Control
Editors Anon
Pages3676-3681
Number of pages6
StatePublished - Dec 1 1996
EventProceedings of the 35th IEEE Conference on Decision and Control. Part 4 (of 4) - Kobe, Jpn
Duration: Dec 11 1996Dec 13 1996

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume4
ISSN (Print)0191-2216

Other

OtherProceedings of the 35th IEEE Conference on Decision and Control. Part 4 (of 4)
CityKobe, Jpn
Period12/11/9612/13/96

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Fingerprint Dive into the research topics of 'Nonlinear stochastic model of fatigue crack length for on-line damage sensing'. Together they form a unique fingerprint.

Cite this