Aluminum Alloy Fatigue Crack Damage Prediction Based on Lamb Wave-Systematic Resampling Particle Filter Method  

作　　者：Gaozheng Zhao Changchao Liu Lingyu Sun Ning Yang Lei Zhang Mingshun Jiang Lei Jia Qingmei Sui 

机构地区：[1]College of Control Science and Engineering,Shandong University,Jinan,250061,China [2]Shandong Institute of Space Electronic Technology,Yantai,264010,China

出　　处：《Structural Durability & Health Monitoring》2022年第1期81-96,共16页结构耐久性与健康监测（英文）

基　　金：This work was supported by the National Natural Science Foundation of China(62073193,61903224,61873333);National Key Research and Development Project(2018YFE02013);Key research and development plan of Shandong Province(2019TSLH0301,2019GHZ004).

摘　　要：Fatigue crack prediction is a critical aspect of prognostics and health management research.The particle filter algorithm based on Lamb wave is a potential tool to solve the nonlinear and non-Gaussian problems on fatigue growth,and it is widely used to predict the state of fatigue crack.This paper proposes a method of lamb wavebased early fatigue microcrack prediction with the aid of particle filters.With this method,which the changes in signal characteristics under different fatigue crack lengths are analyzed,and the state-and observation-equations of crack extension are established.Furthermore,an experiment is conducted to verify the feasibility of the proposed method.The Root Mean Square Error(RMSE)of the three different resampling methods are compared.The results show the system resampling method has the highest prediction accuracy.Furthermore,the factors affected by the accuracy of the prediction are discussed.

关 键 词：Structural health monitoring fatigue crack prognostics particle filter lamb wave paris law 

分 类 号：TG115[金属学及工艺—物理冶金]