A whole service time SHM damage quantification model hierarchical evolution mechanism

Accurate damage quantification for an individual aircraft by using structural health monitoring (SHM) technology poses a persistent challenge in practical engineering. Existing damage quantification models typically rely on prior data acquired from ground design and tests. However, an individual aircraft is subject to diverse uncertainties throughout its whole service time, such as time-varying environmental and operational conditions, different flight missions, and different damage morphologies. Consequently, employing a prior trained model for damage quantification inevitably introduces errors, thereby limiting the engineering applicability of SHM. To improve the damage quantification accuracy for individual aircraft under the influence of uncertainty, a new whole lifetime data-based damage quantification model hierarchical evolution mechanism is proposed in this paper. Multi-source data from the design, service, and maintenance stages of individual aircraft are adopted to continuously evolve the probabilistic damage diagnosis model, enabling it to characterize the specific data distribution and track the damage propagation. The proposed method is validated through fatigue tests of a landing gear beam structure, which is an important aircraft load-carrying component, with guided wave monitoring based hidden Markov model quantifying its crack propagation. The validation result demonstrates the effectiveness of the proposed method in ensuring the long-term reliability of the model and achieving more accurate damage quantification for an individual aircraft.