A Study on the Applicability of the Impact-Echo Test Using Semi-Supervised Learning Based on Dynamic Preconditions

Abstract

The Impact-Echo (IE) test is an effective method for determining the presence, depth, and area of cracks in concrete as well as the dimensions of the sound concrete without defects. In addition, shallow delamination can be measured by confirming a flexural mode in the low-frequency region. Owing to the advancement of non-contact sensors and automated measurement equipment, the IE test can be measured at multiple points in a short period. To analyze and distinguish a large volume of data, applying supervised learning (SL) associated with various contemporary algorithms is necessary. However, SL has limitations due to the difficulty in accurate labeling for increased volumes of test data, and reflection of new specimen characteristics, and it is necessary to apply semi-supervised learning (SSL) to overcome them. This study analyzes the accuracy and evaluates the applicability of a model trained with SSL rather than SL using the data from the air-coupled IE test based on dynamic preconditions. For the detection of delamination defects, the dynamic behavior-based flexural mode was identified, and 21 features were extracted in the time and frequency domains. Three principal components (PCs) such as the real moment, real RMS, and imaginary moment were derived through principal component analysis (PCA). PCs were identical in slab, pavement, and deck. In the case of SSL considering a dynamic behavior, the accuracy increased by 7–8% compared with SL, and it could categorize good, fair, and poor status to a higher level for actual structures. The applicability of SSL to the IE test was confirmed, and because the crack progress varies under field conditions, other parameters must be considered in the future to reflect this.

Non-Destructive Testing Methods for In Situ Crack Measurements and Morphology Analysis with a Focus on a Novel Approach to the Use of the Acoustic Emission Method

“…The energy (amplitude) of the recorded signal increases later, and the obtained values are significantly lower in the damaged area because the zone of energy transfer is smaller (Figure 21) [71]. Work is currently underway to automate the measurement and increase the area that can be analyzed using this method and semi-supervised learning [72].…”

Reinforced concrete surface cracks length detection and length estimation by using digital image processing approach

“…Ultrasonic Pulse Velocity (UPV) is another employed technique to estimate the position of crack or deepness and characterization the quality of RC structures, based on the direct relationship between the wave propagation velocity with the RC material uniformity condition [3]. The use of proven technique such as the impact-echo (IE) method to accurately identifying, localizing and characterizing internal defects in RC structures due to various cracks damages has been conducted by various works [4, 5,6]. However, employing these effective NDT becomes necessary only when the visual inspection by human's naked eye of RC structures indicates potential damage, thereby warranting additional monitoring using NDT mentioned previously to monitor its damage progression [7].…”