Abstract
Ultrasonic guided wave is suitable for non-destructive testing of engineering components due to its advantages such as slow energy attenuation, large detection range, and strong defect recognition ability. However, because of their multi-mode and dispersion characteristics, it is difficult to directly use their echo signals to locate defect. To address this problem, this paper proposed an adaptive modes separation and parameterized identification (AMS-PI) model for guided wave aliasing modes. Firstly, based on the differences in vibration characteristics between different modes, a fixed frequency decomposition model for the guided wave signals was constructed, achieving the separation of aliasing modes. Secondly, based on the difference in dispersion characteristics between different guided wave modes, a parameterized identification model for guided wave modes was constructed. Finally, the effectiveness of the proposed model was demonstrated through weld defect localization experiments.
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