基于导波-高斯混合模型蒙特卡罗迁移度量的结构损伤定量化诊断方法研究

Research on Quantitative Diagnosis Method of Structural Damage Based on Guided Wave-Gaussian Mixture Model Monte Carlo Migration Measurement

在线准确定量诊断飞行器结构疲劳裂纹损伤对于保证结构安全、降低维护费用具有重要意义,为了提升复杂服役条件环境下结构损伤定量化诊断的可靠性,本文提出了一种导波-高斯混合模型(Gaussian mixture model,GMM)蒙特卡罗迁移度量的损伤定量化诊断方法。首先建立表征结构不同状态下导波特征概率分布的GMM,再通过大数据随机采样的蒙特卡罗方法计算监测状态GMM相对于基准GMM的迁移距离,该方法在避免了复杂积分计算的同时,能够更准确地计算GMM的迁移距离,实现复杂服役条件下损伤扩展的准确定量化追踪诊断。选取重要飞行器耳片连接结构进行了孔边裂纹监测,有效实现了裂纹定量化监测,结果表明,相比传统的最小匹配迁移距离计算方法,本文提出的方法使裂纹定量化精度提高了29%。

On-line quantitative diagnosis of fatigue crack damage of aircraft structure is of great significance to ensure structural safety and reduce maintenance cost.In order to improve the reliability of quantitative diagnosis of structural damage under complex service conditions,this paper proposes a damage quantitative diagnosis method based on guided wave-Gaussian Mixture Model(GMM)Monte Carlo migration metric.Firstly,GMM is established to characterize the probability distribution of guided wave characteristics in different states of the structure,and then the migration distance of GMM in the monitored state is calculated by Monte Carlo method of random sampling of big data.This method can not only avoid complex integral calculation,but also calculate the migration distance of GMM more accurately,and realize the quasi-definite quantitative tracking diagnosis of damage propagation under complex service conditions.The crack at the hole edge is monitored by selecting an important aircraft lug connection structure,and the quantitative monitoring of crack is effectively realized.The results show that compared with the traditional calculation method of minimum matching migration distance,the quantitative accuracy of crack is improved by 29%by the proposed method.