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

Gaozheng Zhao,Ning Yang,Lingyu Sun,Changchao Liu,Lei Jia,Qingmei Sui,Mingshun Jiang,Lei Zhang

doi:10.32604/sdhm.2022.016905

Abstract

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.

Highlights

IntroductionPrognostics and health management (PHM) has recently become a novel engineering research hotspot [1–6], and it deals with the real-time assessment of a system under its practical operating conditions
KEYWORDS Structural health monitoring; fatigue crack prognostics; particle filter; lamb wave; paris law Prognostics and health management (PHM) has recently become a novel engineering research hotspot [1–6], and it deals with the real-time assessment of a system under its practical operating conditions
This paper proposes an ultrasonic Lamb wave fatigue damage detection method according to the particle filter algorithm

Summary

Introduction

Prognostics and health management (PHM) has recently become a novel engineering research hotspot [1–6], and it deals with the real-time assessment of a system under its practical operating conditions. When a guided wave signal acts on damage that exits inside the structure during propagation, it produces reflection and scattering. According to the propagation characteristics of guided waves inside the structure, appropriate feature extraction technology can be used to analyze the collected wave signals that indicate damage information [8]. Fatigue crack is an important aspect of PHM research, which significantly involves developing safety features as well as the extension of working time [13]. Xu et al [14] developed a novel method for fatigue crack identification based on nonlinear pseudo-force that appears at the location of a fatigue crack and vanished elsewhere. The ultrasonic nonlinear relative coefficient was used to

Methods

Discussion

Conclusion