High-precision measurement method for near-surface defect depth of metal components under sub-Nyquist sampling conditions
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School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China

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TN06

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    Abstract:

    In order to solve the problem that the defect echo overlaps with the surface echo when measuring the defect depth near the surface of metal components under sub-Nyquist sampling condition which leads to inaccurate depth measurement, a high-precision measurement method for the near-surface defect depth of metal components based on ultrasonic echo resampling and time-frequency transformation is proposed. The ultrasonic echo signal is decomposed into a series of narrowband mode components by variational mode decomposition, and the useful mode components are clustered based on the correlation coefficient to obtain the preprocessed signal. The preprocessed signal is then processed by cubic spline interpolation to realize the data expansion of the sub-Nyquist sampling echo signal and obtain the reconstructed signal. Based on the synchro extracting transform, the timefrequency spectrum and amplitude distribution curve of the reconstructed signal are obtained. According to the principle of ultrasonic single transceiver, the high-precision depth measurement of the near-surface defect of metal components is finally realized. The experimental results show that the proposed method can accurately measure the near-surface defect depth of the metal component under the condition of sub-Nyquist sampling condition, and the measurement relative error is 2.161%, which is obviously less than that of the envelope method and the time-frequency transform method, whose relative error are 3.570% and 13.182%, respectively. Furthermore, the effects of the sub-Nyquist sampling rate, the signal noise and the defect location on the measurement accuracy of the near-surface defect depth are investigated. The results consistently demonstrate that the proposed method has better accuracy and robustness than the traditional methods for the near-surface defect depth measurement under different sampling rates, different noise and different defect depths.

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  • Received:
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  • Online: October 31,2024
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