Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/140263
Title: Remote monitoring of bond line defects between a composite panel and a stiffener using distributed piezoelectric sensors
Authors: Yu, Xudong
Fan, Zheng
Puliyakote, Sreedhar
Castaings, Michel
Keywords: Engineering::Mechanical engineering
Issue Date: 2018
Source: Yu, X., Fan, Z., Puliyakote, S., & Castaings, M. (2018). Remote monitoring of bond line defects between a composite panel and a stiffener using distributed piezoelectric sensors. Smart Materials and Structures, 27(3), 035014-. doi:10.1088/1361-665x/aaa69b
Journal: Smart Materials and Structures
Abstract: Structural health monitoring (SHM) using ultrasonic guided waves has proven to be attractive for the identification of damage in composite plate-like structures, due to its realization of both significant propagation distances and reasonable sensitivity to defects. However, topographical features such as bends, lap joints, and bonded stiffeners are often encountered in these structures, and they are susceptible to various types of defects as a consequence of stress concentration and cyclic loading during the service life. Therefore, the health condition of such features has to be assessed effectively to ensure the safe operation of the entire structure. This paper proposes a novel feature guided wave (FGW) based SHM strategy, in which proper FGWs are exploited as a screening tool to rapidly interrogate the representative stiffener-adhesive bond-composite skin assembly. An array of sensors permanently attached to the vicinity of the feature is used to capture scattered waves from the localized damage occurring in the bond line. This technique is combined with an imaging approach, and the damage reconstruction is achieved by the synthetic focusing algorithm using these scattered signals. The proposed SHM scheme is implemented in both the 3D finite element simulation and the experiment, and the results are in good agreement, demonstrating the feasibility of such SHM strategy.
URI: https://hdl.handle.net/10356/140263
ISSN: 0964-1726
DOI: 10.1088/1361-665X/aaa69b
Rights: © 2018 IOP Publishing Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:MAE Journal Articles

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