Grouting, Rheology, and Soil MechanicsAI and Multimedia in EducationAdvanced Computing and Algorithms

Pengcheng Xia, Z. Pan, Ruoyu Chen

2026.1.2RESEARCH IN NONDESTRUCTIVE EVALUATION

DOI: 10.1080/09349847.2026.2614555

Abstract

ABSTRACT Grouted sleeves serve as critical load-transfer components in precast concrete structures, and their reliable connections are decisive for ensuring structural integrity. However, the inherent structural complexity of precast concrete leads to severe ultrasonic wave scattering and mode conversion during testing, significantly degrading the imaging accuracy of the Synthetic Aperture Focusing Technique (SAFT) due to signal contamination. To address this challenge, we propose a noise-suppression-enhanced SAFT algorithm that significantly improves detection performance by applying advanced filtering techniques to the raw signals.Through systematic evaluation of four filtering methods – elliptic bandpass filtering, wavelet transform filtering, Wiener filtering, and Butterworth bandpass filtering – an optimized hybrid filtering strategy combining time-frequency decomposition and adaptive noise cancellation was established. Experimental validation on precast concrete columns with embedded grouted sleeves demonstrated the superiority of our enhanced algorithm. Compared to conventional SAFT processing, it achieved a 48.6% higher signal-to-noise ratio (SNR), a 170% increase in contrast-to-noise ratio (CNR), and a 381.5% improvement in contrast ratio (CR). Quantitative comparison with physical measurements revealed a positional assessment error of less than 1.5 cm.This study marks the first successful application of noise-suppressed SAFT technology for grouted sleeve characterization, establishing a novel methodological framework for quality assurance in modular construction through enhanced nondestructive testing capabilities.

Citation format

XIA, Pengcheng; PAN, Z.; CHEN, Ruoyu. Research on imaging of precast concrete structure grouting sleeve based on noise suppression SAFT filtering algorithm. RESEARCH IN NONDESTRUCTIVE EVALUATION, 2026, 37(1): 17–42.