Abstract:

This article proposes a sparse denoising method for ultrasonic signals based on the dual memory-enhanced deep unfolding network (DME-DUN), which aims to accurately reconstruct high-frequency ultrasonic signals in flip chip detection. To address information loss during the iterative process in deep unfolding networks, two memory enhancement mechanisms are designed, i.e., adjacent-stage and cross-stage. For adjacent-stage, the high-throughput information from the previous stage is introduced into the current stage, thus facilitating the transmission of information between adjacent stages. Additionally, the cross-stage memory enhancement mechanism is applied to promote information fusion between separated stages. This mechanism is based on Richardson extrapolation and calculates the output error between every two adjacent stages to update the sparse coefficient. Extensive experiments verify that the proposed method effectively captures weak echo features while removing noise.

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