加筋复合材料结构分层损伤的贝叶斯诊断及预测

针对复合材料结构疲劳损伤的在线监测和预测问题，提出了一种基于结构健康监测 (Structural health monitoring, SHM) 和贝叶斯理论的结构分层损伤诊断及结构剩余使用寿命预测方法。在贝叶斯概率理论框架下，采用指数模型描述复合材料结构疲劳分层损伤面积的先验演化规律，融合在线SHM数据对结构分层损伤状态，以及损伤面积演化模型的参数进行联合后验估计，即为损伤诊断结果。进一步通过后验估计得到的损伤状态和模型参数预测未来时刻结构分层损伤面积的演化，从而得到当前复合材料结构的剩余使用寿命预测结果。通过有限元仿真的加筋复合材料结构疲劳分层扩展对所提出的方法进行了验证。结果表明，方法可以在线准确地诊断结构分层损伤状态以及预测结构的剩余使用寿命。 

Bayesian diagnosis and prognosis of delamination damage in the stiffened composite structure

Aiming at the on-line diagnosis and prognosis of composite structures, a method for structural delamination diagnosis and remaining useful life (RUL) prediction was proposed based on structural health monitoring (SHM) and the Bayesian theory. Within the Bayesian probabilistic framework, an exponential model was adopted to describe the prior progression of the fatigue delamination in the composite structure. Then, on-line SHM data were incorporated for diagnosing the delamination state, as well as parameters of the damage area progression model. The posterior estimations denoted the diagnosis result, based on which the progression of the delamination area in the future was predicted, giving the RUL of the current composite structure. The proposed method was validated on the simulated fatigue delamination growth in a stiffened composite structure through the finite element method. The result shows the accuracy of this method for on-line diagnosing the delamination damage, as well as predicting the RUL of the structure.