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

被引：1
作者：
Zhao G. [1 ]
Liu C. [1 ]
Sun L. [1 ]
Yang N. [2 ]
Zhang L. [1 ]
Jiang M. [1 ]
Jia L. [1 ]
Sui Q. [1 ]
机构：
[1] College of Control Science and Engineering, Shandong University, Jinan
[2] Shandong Institute of Space Electronic Technology, Yantai
来源：
SDHM Structural Durability and Health Monitoring | 2022年 / 16卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Fatigue crack prognostics; Lamb wave; Paris law; Particle filter; Structural health monitoring;
D O I：
10.32604/SDHM.2022.016905
中图分类号：
学科分类号：
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 wave-based 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. © 2022 Tech Science Press. All rights reserved.
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页码：81 / 96
页数：15
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