利用短时傅里叶变换 (STFT) 检测混凝土中钢筋的基于图像的分析方法

IF 2.2 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Shinyeon Kim;Minjeong Kim;Moon-Jung Kwak;Heejin Hwang;Seunghyun Song;Youngjun Joo
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引用次数: 0

摘要

钢筋结构的适当位置对建筑物的稳定性至关重要。然而,由于缺乏训练有素的劳动力以及缺乏管理和监督,混凝土结构的不良施工和坍塌事故日益增多。在这封信中,我们利用超声波信号进行无损检测(NDT),以确定混凝土块中是否存在钢筋。实验在有钢筋和无钢筋的两个不同位置进行。随后,对每个位置的数据进行短时傅立叶变换(STFT),并绘制出图像以识别特征。据观察,频带随钢筋的存在而变化。因此,我们可以根据钢筋的存在从 STFT 图像中提取可区分的特征。为了验证所获特征的有效性,我们使用 Python 代码进行了图像分类,结果表明准确率很高。因此,STFT 图像能够确定混凝土结构中是否存在钢筋。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image-Based Analysis Method for Detecting a Rebar in Concrete Using Short-Time Fourier Transform (STFT)
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.
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来源期刊
IEEE Sensors Letters
IEEE Sensors Letters Engineering-Electrical and Electronic Engineering
CiteScore
3.50
自引率
7.10%
发文量
194
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