Assessing the Influences of Noise Suppression Filters on Ultrasonic Concrete Images Generated by an Innovative CMU-SAFT Algorithm

Abstract

AbstractUltrasonic imaging is a useful nondestructive testing technology for visualizing internal structural defects in structures. Despite its utility, since synthetic aperture focusing technique (SAFT) algorithm demands using advanced equipment to superimpose the measurements, this paper introduces a novel approach named CMU-SAFT to broaden applicability of SAFT on conventional ultrasonic data obviating the necessity for matrix antenna array-equipped devices and preventing hyperbolic patterns. To validate the feasibility of the proposed algorithm, experimental tests were conducted on a laboratory-produced concrete specimen including delamination defects at varying depths. Since other reflectives causing distortion in the ultrasonic image can interfere with the signal, the study also evaluated the influences of different noise suppression filters along with their combinations (band pass, wavelet transform, Wiener, and Savitzky–Golay). CMU-SAFT images were constructed using eleven filter combinations, and their performances were quantitatively assessed using signal-to-noise ratio, signal-to-noise and distortion ratio, total harmonic distortion, root mean square, mean squared ratio, mean absolute error and cross-correlation. The most effective filters and performance indices aligning with CMU-SAFT images considering defect depth and scanning width were suggested. The findings of the study revealed the leading potential of CMU-SAFT algorithm to overcome the need for specialized equipment by utilizing recommended filters and indicators under specific conditions.