Demonstrates enhanced imaging clarity in identifying grouting defects, indicating improved safety in construction.
The safety of prefabricated buildings is highly dependent on the fullness of sleeve grouting. However, as a typical heterogeneous media, concrete has multiple scattering effects caused by its internal coarse aggregate, which can lead to severe structural noise, making it difficult to obtain high signal‐to‐noise ratio images using the traditional total focus method (TFM). To address this problem, this study proposes a high‐precision imaging method based on elastic reverse time migration (ERTM). This method combines the finite difference time domain method to construct a non‐uniform wave field model, uses a stress‐trace scalarization strategy to isolate pure P‐waves, employs cross‐correlation imaging conditions to effectively utilize scattered wave field information, and introduces Laplace filtering and Hilbert transform to eliminate low‐frequency artifacts. Experimental results revealed that: (1) In the simulation environment, the ERTM algorithm exhibited excellent scattering noise suppression capabilities. Under the full grouting condition, the imaging clarity reached 82.1%, which was 15.6% higher than the TFM algorithm (66.5%). Under the grouting defect condition, the clarity was further improved to 85.3%, and the empty sleeve model showed the highest clarity (88.5%) due to the total reflection characteristics of the steel‐air interface. (2) In the outdoor experiment, despite the interference from the field environment, the overall clarity of the ERTM algorithm under the grouting full and 1/4 defect conditions still reached 79.5% and 82.8% respectively, which was 14.3% and 15.3% better than the TFM algorithm. Moreover, the resolution accuracy of local defect areas was as high as 87.5%. The research has confirmed that the ERTM algorithm can effectively overcome wavefront distortion in heterogeneous media and significantly improve the robustness of identifying small grouting defects under complex working conditions.
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Lu et al. (2026) studied this question.
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