A damage imaging method for variable-thickness thin-walled structures based on 2D-CWT local wave number analysis

The 2D-CWT local wavenumber analysis method simplifies the detection process of thin-walled structures with varying thickness, improves the effectiveness and accuracy of signal processing, accurately reflects the location and distribution of damage, and achieves efficient damage imaging.

CN122171680APending Publication Date: 2026-06-09BEIJING MECHANICAL EQUIP INST
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING MECHANICAL EQUIP INST
Filing Date
2024-12-06
Publication Date
2026-06-09

AI Technical Summary

Technical Problem

Existing technologies are complex to detect thin-walled structures with varying thicknesses, have poor signal processing effectiveness and accuracy, make it difficult to effectively identify the causes of abnormal guided wave signals, and have stringent detection requirements.

Method used

The method based on 2D-CWT local wavenumber analysis is adopted. After generating guided wave signals at preset excitation points, three-dimensional wavefield signals are acquired, and three-dimensional Fourier transform and filtering are performed to extract the two-dimensional wavenumber-amplitude array. Then, inverse Fourier transform and continuous wavelet transform are performed to generate damage imaging map.

Benefits of technology

It simplifies the detection process, improves the effectiveness and accuracy of signal processing, accurately reflects the location and distribution of damage, and has high detection efficiency and a simple process.

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Abstract

This invention relates to a damage imaging method for variable-thickness thin-walled structures based on 2D-CWT local wavenumber analysis, belonging to the field of nondestructive testing technology. The method involves exciting the test object at a preset excitation point on the variable-thickness thin-walled structure to generate guided wave signals. The guided wave signals on the test object surface are sampled to obtain a three-dimensional wavefield signal. This signal is then subjected to a three-dimensional Fourier transform, and the wavenumber-amplitude array corresponding to the center frequency is extracted. After filtering, the A0 mode signal, which better reflects structural changes, is retained. After conversion back to the spatial domain, multiple wavelet transforms are performed to extract multiple wavelet coefficient spectra. Finally, the multiple wavelet coefficient spectra are superimposed to obtain a damage image that reflects the distribution and changes in damage location. Compared with existing technologies, this embodiment not only simplifies the detection process but also solves the problems of effectiveness and accuracy in signal processing and the difficulty in imaging damage in variable-thickness thin-walled structures.
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