Determination of Paris' law constants and crack length evolution via Extended and Unscented Kalman filter: An application to aircraft fuselage panels

• Published in: Mechanical systems and signal processing 2016-12, Vol.80, p.262-281
• Main Authors: Wang, Yiwei, Binaud, Nicolas, Gogu, Christian, Bes, Christian, Fu, Jian
• Format: Article
• Language: English
• Subjects: Aging aircraft; Aircraft; Aircraft components; Crack growth; Crack propagation; Engineering Sciences; Extended Kalman filter; Fatigue cracks; Fuselages; Mathematical models; Mechanical engineering; Mechanics; Paris; Paris' law constants; Uncertainty; Unscented Kalman filter
• ISSN: 0888-3270; 1096-1216
• DOI: 10.1016/j.ymssp.2016.04.027

Prediction of fatigue crack length in aircraft fuselage panels is one of the key issues for aircraft structural safety since it helps prevent catastrophic failures. Accurate estimation of crack length propagation is also meaningful for helping develop aircraft maintenance strategies. Paris' law is often used to capture the dynamics of fatigue crack propagation in metallic material. However, uncertainties are often present in the crack growth model, measured crack size and pressure differential in each flight and need to be accounted for accurate prediction. The aim of this paper is to estimate the two unknown Paris' law constants m and C as well as the crack length evolution by taking into account these uncertainties. Due to the nonlinear nature of the Paris' law, we propose here an on-line estimation algorithm based on two widespread nonlinear filtering techniques, Extended Kalman filter (EKF) and Unscented Kalman filter (UKF). The numerical experiments indicate that both EKF and UKF estimated the crack length well and accurately identified the unknown parameters. Although UKF is theoretical superior to EKF, in this Paris' law application EKF is comparable in accuracy to UKF and requires less computational expense. •EKF involves significantly lower computational cost than UKF.•Both EKF and UKF algorithms show good identification accuracy.•On-line estimation algorithms based on EKF and UKF are proposed.•Estimation of Paris' law constants is formalized as a nonlinear filtering problem.