Assessing Strand Steel Wire Prestress Level Using Guided Wave Dispersion Properties

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Proceedings of the UNIfied Conference of DAMAS, IncoME and TEPEN Conferences (UNIfied 2023) (TEPEN 2023, IncoME-V 2023, DAMAS 2023)

Abstract

As an effective non-destructive testing method, guided waves have been widely used in assessing the condition of various structures, such as pipelines, rails, plates, etc. In this paper, the characteristic equations of steel strands are obtained by the updated semi-analytic finite element method, on the basis of spatial arrangement law of spiral period structure. From the characteristic equations, the frequency disperses behavior for guided waves propagating in the steel wire waveguide is investigated, and the disperse curves for the group velocity are obtained. Then, from the characteristic equation, the axial stress level of the strand steel wires, can be estimated from the dispersion properties available such as group velocity. Finally, a numerical example for a 7-wire steel strand is adopted to demonstrate the accuracy of the proposed method. From the obtained results, the proposed method can accurately estimate the axial prestress level of the stranded streel wires by using the guided wave group velocity available.

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Acknowledgements

The authors are very grateful for the financial supports received from the National Key Research and Development Program of China (Grant No. 2021YFE0105600), the National Natural Science Foundation of China (Grant No. 51978263), the Key Project for Scientific and Technological Cooperation Scheme of Jiangxi Province (Grant Nos. 20212BDH80022 and 20223BBH80002), and the Jiangxi Postgraduate Innovation Funding Program (YC2022-s500).

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Correspondence to Hua-Peng Chen .

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Li, H., Chen, HP. (2024). Assessing Strand Steel Wire Prestress Level Using Guided Wave Dispersion Properties. In: Ball, A.D., Ouyang, H., Sinha, J.K., Wang, Z. (eds) Proceedings of the UNIfied Conference of DAMAS, IncoME and TEPEN Conferences (UNIfied 2023). TEPEN IncoME-V DAMAS 2023 2023 2023. Mechanisms and Machine Science, vol 152. Springer, Cham. https://doi.org/10.1007/978-3-031-49421-5_73

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  • DOI: https://doi.org/10.1007/978-3-031-49421-5_73

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