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Detecting fatigue-induced progressive damage under varying environmental conditions remains a major challenge in structural health monitoring (SHM). This study investigates a baseline-free nonlinear guided wave method, which extracts nonlinear parameters to detect fatigue cracks without requiring baseline signals from the pristine state. The method demonstrates reliable detection of cracks around 3 mm in size, with the nonlinear parameter serving as a sensitive indicator of damage initiation and growth. Its independence from baseline signals enhances practicality for in-service monitoring applications. However, experimental results reveal that the method’s performance is sensitive to temperature variations, with irregular responses observed at different temperatures, which may affect detection consistency. These findings highlight both the potential and the limitations of nonlinear guided wave methods, underscoring the need for temperature compensation strategies to improve their robustness under variable environmental conditions. Overall, the proposed approach contributes to advancing baseline-free SHM techniques by offering a viable solution for progressive crack detection in realistic service environment.
Czasopismo
Rocznik
Tom
Strony
119--130
Opis fizyczny
Bibliogr. 35 poz., rys., tab., wykr.
Twórcy
autor
- City and Guilds Building, Department of Aeronautics, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
autor
- City and Guilds Building, Department of Aeronautics, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
autor
- City and Guilds Building, Department of Aeronautics, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
Bibliografia
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- García-Macías, E., & Ubertini, F. (2022). Real-time Bayesian damage identification enabled by sparse PCE-Kriging meta-modelling for continuous SHM of large-scale civil engineering structures. Journal of Building Engineering, 59, 105004. https://doi.org/10.1016/j.jobe.2022.105004
- Giannakeas, I. N., Mazaheri, F., Bacarreza, O., Khodaei, Z. S., & Aliabadi, F. M. H. (2023). Probabilistic residual strength assessment of smart composite aircraft panels using guided waves. Reliability Engineering & System Safety, 237, 109338. https://doi.org/10.1016/j.ress.2023.109338
- He, J., Guan, X., Peng, T., Liu, Y., Saxena, A., Celaya, J., & Goebel, K. (2013). A multi-feature integration method for fatigue crack detection and crack length estimation in riveted lap joints using Lamb waves. Smart Materials and Structures, 22(10), 105007. https://doi.org/10.1088/0964-1726/22/10/105007
- Khazaee, M., Derian, P., & Mouraud, A. (2022). A comprehensive study on Structural Health Monitoring (SHM) of wind turbine blades by instrumenting tower using machine learning methods. Renewable Energy, 199, 1568-1579. https://doi.org/10.1016/j.renene.2022.09.032
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- Li, M., & He, J. (2021). Effect of high temperature on ultrasonic velocity in graphite. Diamond and Related Materials, 116, 108368. https://doi.org/10.1016/j.diamond.2021.108368
- Liu, H., & Zhang, Y. (2019). Deep learning based crack damage detection technique for thin plate structures using guided lamb wave signals. Smart Materials and Structures, 29(1), 015032. https://doi.org/10.1088/1361-665x/ab58d6
- Mardanshahi, A., Nasir, V., Kazemirad, S., & Shokrieh, M. M. (2020). Detection and classification of matrix cracking in laminated composites using guided wave propagation and artificial neural networks. Composite Structures, 246, 112403. https://doi.org/10.1016/j.compstruct.2020.112403
- Martinez-Luengo, M., Kolios, A., & Wang, L. (2016). Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm. Renewable and Sustainable Energy Reviews, 64, 91-105. https://doi.org/10.1016/j.rser.2016.05.085
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- Mishra, M., Lourenço, P. B., & Ramana, G. V. (2022). Structural health monitoring of civil engineering structures by using the internet of things: A review. Journal of Building Engineering, 48, 103954. https://doi.org/10.1016/j.jobe.2021.103954
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- Ren, F., Giannakeas, I. N., Sharif Khodaei, Z., & Aliabadi, M. H. F. (2023b). Theoretical and experimental investigation of guided wave temperature compensation for composite structures with different thicknesses. Mechanical Systems and Signal Processing, 200, 110594. https://doi.org/10.1016/j.ymssp.2023.110594
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Uwagi
This article was presented at the 32nd Symposium of ICAF https://www.icaf2025.com/
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8c4dd2fe-5a88-4061-b0d1-f798d109bc82
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