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A model-based prognostics method for fatigue crack growth in fuselage panels

Chinese Journal of Aeronautics 2019年第2期32卷 396-408页

作者： Yiwei WANG christian gogu Nicolas BINAUD christian BES Jian FU School of Mechanical Engineering and Automation Beihang University Institut Clément Ader (UMR CNRS 5312) INSA/UPS/ISAE/Mines Albi Université de Toulouse

This paper proposes a model-based prognostics method that couples the Extended Kalman Filter(EKF) and a new developed linearization method. The proposed prognostics method is developed in the context of fatigue crack propagation in fuselage panels where the model parameters are unknown and the crack propagation is affected by different types of uncertainties. The coupled method is composed of two steps. The first step employs EKF to estimate the unknown model parameters and the current damage state. In the second step, the proposed efficient linearization method is applied to compute analytically the statistical distribution of the damage evolution path in some future time. A numerical case study is implemented to evaluate the performance of the proposed method. The results show that the coupled EKF-linearization method provides satisfactory results: the EKF algorithm well identifies the model parameters, and the linearization method gives comparable prediction results to Monte Carlo(MC) method while leading to very significant computational cost saving. The proposed prognostics method for fatigue crack growth can be used for developing predictive maintenance strategy for an aircraft fleet, in which case, the computational cost saving is significantly meaningful.

关键词： Aircraft fuselage panels Extended Kalman filter Fatigue crack propagation Linearization method Model-based prognostics

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A cost driven predictive maintenance policy for structural airframe maintenance

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Chinese Journal of Aeronautics 2017年第3期30卷 1242-1257页

作者： Yiwei WANG christian gogu Nicolas BINAUD christian BES Raphael T.HAFTKA Nam H.KIM Universite de Toulouse INSA/UPS/ISAE/Mines Albi ICA UMR CNRS 5312 Toulouse 31400 Frallce Department of Mechanical & Aerospace Engineering University of Florida Gainesville 32611 USA

Airframe maintenance is traditionally performed at scheduled maintenance *** decision to repair a fuselage panel is based on a fixed crack size threshold,which allows to ensure the aircraft safety until the next scheduled maintenance *** progress in sensor technology and data processing techniques,structural health monitoring（SHM） systems are increasingly being considered in the aviation *** systems track the aircraft health state continuously,leading to the possibility of planning maintenance based on an actual state of aircraft rather than on a fixed *** paper builds upon a model-based prognostics framework that the authors developed in their previous work,which couples the Extended Kalman filter（EKF） with a firstorder perturbation（FOP） *** using the information given by this prognostics method,a novel cost driven predictive maintenance（CDPM） policy is proposed,which ensures the aircraft safety while minimizing the maintenance *** proposed policy is formally derived based on the trade-off between probabilities of occurrence of scheduled and unscheduled maintenance.A numerical case study simulating the maintenance process of an entire fleet of aircrafts is *** the condition of assuring the same safety level,the CDPM is compared in terms of cost with two other maintenance policies：scheduled maintenance and threshold based SHM *** comparison results show CDPM could lead to significant cost savings.

关键词： Extended Kalman filter First-order perturbation method Model-based prognostic Predictive maintenance Structural airframe maintenance

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