Damage Detection in Multiple RC Structures Based on Embedded Ultrasonic Sensors and Wavelet Transform

Abstract

This paper summarizes the results of research aimed at assessing cracks in reinforced concrete structures using embedded ultrasonic sensors. The diffuse ultrasonic waves were considered to evaluate the health status of the tested structures. There are different algorithms used to detect cracks in the structure, but most studies have been performed on benchmark reinforced concrete (RC) structures and in laboratory conditions. Since there were difficulties with the validity of damage detection in real structures in the presence of environmental changes and noises, the application of advanced signal processing methods was necessary. Therefore, the wavelet transform was applied to process ultrasonic signals acquired from multiple civil structures. It is shown that the ultrasonic sensors with an applied wavelet transform algorithm on collected signals can successfully detect cracks in the laboratory as well as in a real environment. Experimental results showed a perfect match for detecting damage and quasi-static load in the presence of environmental changes. The results were confirmed with other techniques. In addition, designing an extra filter for removing noises can be avoided by using the applied algorithms. The obtained results confirmed that diffuse ultrasonic sensor methodology with the proposed algorithm is useful and effective in monitoring real RC structures, and it is better than traditional techniques.

EEMD and Multiscale PCA-Based Signal Denoising Method and Its Application to Seismic P-Phase Arrival Picking

“…A fixed threshold T = σ • 2 log(N) (σ denotes data variance) was used in this study. (6) For the remaining IMFs, denoised componentsĉ i (t) can be obtained by repeating steps (3)(4)(5), and the final denoised signalx(t) is obtained by stacking the denoised componentsĉ i (t), as follows:…”

“…Consequently, to improve signal detection, classification, and phase arrival picking, it is necessary to remove unwanted noise. Currently, signal denoising is widely used in the fields of medical signals [ 1 ], speech signals [ 2 ], mechanical diagnosis [ 3 ], structural health monitoring [ 4 , 5 , 6 ], and seismic monitoring networks [ 7 , 8 , 9 ]; however, this study focused specifically on microseismic (MS) signal denoising.…”

“…Subsequently, SVD was combined with the Hankel matrix to denoise a signal [ 23 ], where the Hankel matrix can expand a signal into a high-dimensional matrix and is very beneficial for feature extraction. Recently, coda wave interferometry (CWI) has been successfully applied to monitor stress distribution and damage detection in engineering [ 4 , 5 , 6 ], where wavelet transformation [ 5 ], normal band-pass filter, narrow band-pass filter, and double-notch filter [ 6 ] were used to extract useful signal features. These techniques provided a good research direction for noise reduction and damage detection.…”

Signal-Level Fusion Approach for Embedded Ultrasonic Sensors in Damage Detection of Real RC Structures

“…The CWT function was used since CWT is an effective signal processing approach, used to detect changes/cracks in many applications due to its very high sensitivity to even tiny disturbances in the time-domain signal. CWT-based methods are used for the detection and localization of damages in many applications [37][38][39]. A CWT-based change matrix is developed to evaluate the changes in the structure and propagation of crack.…”

Analysis of Sensitivity of Distance between Embedded Ultrasonic Sensors and Signal Processing on Damage Detectability in Concrete Structures

“…The cross-correlation function was used for damage detection in a steel beam under varying temperatures [28]. In [29], the authors applied the wavelet transform to detect damage in the structures. The short-time Fourier transform (STFT) has been used to detect local damage in a bearing [30].…”