Title :
Stochastic modeling of fatigue damage dynamics for failure prognostics and risk analysis
Author :
Ray, Avik ; Tangirala, S.
Author_Institution :
Pennsylvania State Univ., University Park, PA
Abstract :
Failure prognostics and risk analysis facilitate maintenance scheduling and operation planning of aging mechanical systems (e.g., power and processing plants, aircraft, and civil infrastructures such as bridges and industrial buildings). Decision tools for failure prognostics must have the capability of incorporating the dynamic behavior of material damage under both normal and off-normal operating conditions. This paper presents a nonlinear stochastic model of fatigue damage dynamics and a filter for online estimation of the first two moments of the time-dependent damage accumulation. The results have been verified with experimental data of fatigue damage statistics for the 2024-T3 Aluminum alloy
Keywords :
failure analysis; fatigue; maintenance engineering; modelling; reliability theory; risk management; stochastic processes; 2024-T3 Aluminum alloy; Al-Cu-Mg; aging mechanical systems; damage statistics; failure prognostics; fatigue damage dynamics; filter; maintenance scheduling; material damage; operation planning; risk analysis; stochastic modeling; Aging; Aircraft; Fatigue; Job shop scheduling; Mechanical systems; Power system modeling; Power system planning; Process planning; Risk analysis; Stochastic processes;
Conference_Titel :
American Control Conference, Proceedings of the 1995
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2445-5
DOI :
10.1109/ACC.1995.529779
