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Effect of central and non-central frequency components on the quality of damage imaging

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Abstract

Accurate image reconstruction of damage through Lamb wave diffraction tomography (LWDT) requires substantial information of scatter field. This can be achieved using transducer network to collect the scatter field data. However, this requires a large number of transducers that creates logistical constraints for the practical applications of the technique. Various methods have been developed to improve the practicability of LWDT. One of the main approaches is to employ data at multiple frequencies within the bandwidth of the excitation signal. The objective of this study is to investigate the performance of using the data at non-central frequencies to reconstruct the damage image using LWDT. This provides an understanding on the influence of data at each individual frequency in the damage image reconstruction.In this paper, a series of numerical case studies with consideration of different damage sizes and shapes are carried out. Different non-central frequencies data is used to reconstruct the damage image. The results show that using the data at different non-central frequencies leads to different qualities of the reconstructed damage images. The quality of these reconstructed damage images are then compared to investigate the information contained of the data at each individual frequency. The study shows that the non-central frequencies data can provide additional information in the damage image reconstruction. Overall, the results of this study provide insights into the influences of the data at different frequencies, which is essential to advance the developments of the LWDT.

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Acknowledgements

The research described in this paper was financially supported by the Australian Research Council under Grant Number DE130100261. The support is greatly appreciated.

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Correspondence to Ching-Tai Ng.

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Pudipeddi, G.T., Ng, CT. & Kotousov, A. Effect of central and non-central frequency components on the quality of damage imaging. J Civil Struct Health Monit 8, 49–61 (2018). https://doi.org/10.1007/s13349-017-0258-z

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  • DOI: https://doi.org/10.1007/s13349-017-0258-z

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