Literature DB >> 32193014

Environmental and operational conditions effects on Lamb wave based structural health monitoring systems: A review.

Rahim Gorgin1, Ying Luo1, Zhanjun Wu2.   

Abstract

Lamb wave is widely recognized as one of the most encouraging tools for structural health monitoring (SHM) systems. In spite of many favourable characteristics of Lamb wave for SHM, real-world application of these systems is still quite limited. Beside the complexities derived from multi-modal, dispersive and multi-path characteristics of Lamb waves, one of the main challenges in Lamb wave based SHM is sensitivity of these systems to environmental and operational conditions (EOCs) parameters. This paper provides a state of the art review of the effects of EOCs parameters including: temperature, moisture, load, vibration and bonding (adhesive layer shear modulus and thickness, bond defects), on Lamb wave propagation. Moreover, this paper provides a summary of compensation strategies to account for EOCs effects as well as baseline free techniques. An objective is also to understand the future directions and areas requiring attention of the researchers.
Copyright © 2020 Elsevier B.V. All rights reserved.

Keywords:  Baseline free techniques; Compensation strategies; Environmental and operational conditions; Lamb waves; Structural health monitoring (SHM)

Year:  2020        PMID: 32193014     DOI: 10.1016/j.ultras.2020.106114

Source DB:  PubMed          Journal:  Ultrasonics        ISSN: 0041-624X            Impact factor:   2.890


  4 in total

Review 1.  Structural Health Monitoring in Composite Structures: A Comprehensive Review.

Authors:  Sahar Hassani; Mohsen Mousavi; Amir H Gandomi
Journal:  Sensors (Basel)       Date:  2021-12-27       Impact factor: 3.576

2.  Mechanic-Electric-Thermal Directly Coupling Simulation Method of Lamb Wave under Temperature Effect.

Authors:  Xiaofei Yang; Zhaopeng Xue; Hui Zheng; Lei Qiu; Ke Xiong
Journal:  Sensors (Basel)       Date:  2022-09-02       Impact factor: 3.847

3.  Lamb Wave Detection for Structural Health Monitoring Using a ϕ-OTDR System.

Authors:  Rizwan Zahoor; Enis Cerri; Raffaele Vallifuoco; Luigi Zeni; Alessandro De Luca; Francesco Caputo; Aldo Minardo
Journal:  Sensors (Basel)       Date:  2022-08-09       Impact factor: 3.847

4.  Damage Detection in Flat Panels by Guided Waves Based Artificial Neural Network Trained through Finite Element Method.

Authors:  Donato Perfetto; Alessandro De Luca; Marco Perfetto; Giuseppe Lamanna; Francesco Caputo
Journal:  Materials (Basel)       Date:  2021-12-10       Impact factor: 3.623

  4 in total

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