Image-Based Analysis Method for Detecting a Rebar in Concrete Using Short-Time Fourier Transform (STFT)

Abstract

The appropriate location of reinforced structures is critical for building stability. However, due to the shortage of well-trained labor and lack of management and supervision, poor construction and collapse accidents in the concrete structure are increasing. In this letter, we conduct nondestructive testing (NDT) with ultrasonic signals to determine the presence of a rebar within the concrete block. The experiments are performed at two distinct locations with and without a rebar. Subsequently, the short-time Fourier transform (STFT) is performed on the data from each location, and the resulting images are plotted to identify features. It is observed that the frequency bands vary depending on the presence of a rebar. It allows us to extract distinguishable features in STFT images based on the presence of the rebar. To validate the effectiveness of obtained features, image classification using Python codes is conducted, demonstrating high accuracy. Therefore, STFT images enable the determination of the presence of the rebar within the concrete structure.