contributor author | Jiaqi Zhang | |
contributor author | Zhanjun Wu | |
contributor author | Zhengyan Yang | |
contributor author | Chang Gao | |
contributor author | Kehai Liu | |
contributor author | Yuebin Zheng | |
contributor author | Kai Zhou | |
date accessioned | 2022-01-30T20:12:23Z | |
date available | 2022-01-30T20:12:23Z | |
date issued | 2020 | |
identifier other | %28ASCE%29AS.1943-5525.0001134.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4266684 | |
description abstract | Guided waves have been widely utilized in various structural health monitoring (SHM) techniques because of their long propagation distance and high sensitivity to small-scale defects in structural types such as plates and bars. In particular, T-bars are typical structural components commonly used in aerospace engineering, playing significant roles in load-carrying. Thus, the health states of T-bars largely affect the integrity and safety of aircraft structures. This paper presents a novel defect-detection method for T-bars relying on the examination of propagation characteristics of multimode guided waves. To select proper wave frequencies and modes that are sensitive to different locations of defects in T-bars, the dispersion curves and cross-sectional mode shapes of multimode guided waves are investigated systematically using the semianalytical finite element (SAFE) method. A defect localization strategy is then developed based on the multimode characteristics, able of identifying defects both along the longitudinal direction and the cross-sectional region. A weighted gathering method is presented to reduce the interference from the modes other than the selected ones, giving rise to increased accuracy of defect identification. Both finite element (FE) simulations and experiments are performed for an aluminum T-bar structure to validate the feasibility and precision of the proposed method. | |
publisher | ASCE | |
title | Multimode Guided Waves–Based Structural Defect Localization Longitudinally and Cross-Sectionally in T-Bars | |
type | Journal Paper | |
journal volume | 33 | |
journal issue | 4 | |
journal title | Journal of Aerospace Engineering | |
identifier doi | 10.1061/(ASCE)AS.1943-5525.0001134 | |
page | 04020017 | |
tree | Journal of Aerospace Engineering:;2020:;Volume ( 033 ):;issue: 004 | |
contenttype | Fulltext | |