Enhancing ultrasonic time-of-flight diffraction measurement through an adaptive deconvolution method

Deconvolution is generally applied to improve the temporal resolution of ultrasonic signals. However, using this process in the time-of-flight diffraction (TOFD) measurement of small and shallow defects is challenging because TOFD signals are dispersive in space-frequency distribution. Particularly, determining the reference signal for deconvolution remains a critical barrier. To this end, an adaptive deconvolution method is proposed in this study. Using wavelet transform, we firstly decompose the TOFD signals into sub-band signals to standardise the space-frequency distribution. Then, sub-band signals with strong coherences are adaptively selected on the basis of coherence coefficient metric. Upon the opted sub-band signals, a lateral wave can be readily used as the reference signal, and TOFD signals can be reconstructed with established Wiener filtering and spectral extrapolation methods. The feasibility of the proposed method is validated with the TOFD measurement of a small side-drilled hole near the surface. Results show that the proposed method effectively separates overlapping TOFD signals and improves the axial resolution of a TOFD image.