High-Resolution Ultrasonic Total Focusing Method Optimized by Deconvolution for Concrete Defect Evaluation

Abstract

Concrete structures are prone to internal defects during long-term service, which impairs their safety and durability. Although the ultrasonic total focusing method (TFM) is widely applied to concrete defect detection, its imaging is often affected by noise, signal aliasing, and localization errors.To improve the accuracy of defect detection in concrete structures, this study proposes a deconvolution-optimized ultrasonic TFM imaging method (DC-TFM), achieving high-resolution detection through multi-step signal processing. Firstly, Wiener deconvolution was adopted for preprocessing the original signals collected by the ultrasonic array. Using the measured system response as the convolution kernel, the signal pulse width was compressed to effectively suppress signal aliasing. Secondly, the propagation characteristics of surface waves were calculated and a window function was applied to eliminate the interference of direct surface waves on defect signals, enhancing the distinguishability of defect scattering signals. Finally, the processed signals were reconstructed for imaging based on the total focusing algorithm. The effectiveness of the proposed method in detecting typical concrete defects, such as double circular holes and inclined void, was systematically verified through numerical simulations and experiments. Analysis results showed that compared with the traditional TFM and the TFM corrected only by pulse peak delay (PPD), the proposed DC-TFM method significantly reduced localization errors, remarkably improved longitudinal resolution, and achieved clearer identification of defect boundaries, which exhibited higher shape restoration accuracy for dense defects and inclined defects. The imaging signal-to-noise ratio (SNR) increased up to 194%, and the maximum depth localization error was reduced by 92%.