Impact-echo Signals Research Articles

Detection of Concrete Structural Defects Using Impact Echo Based on Deep Networks

Abstract Deep learning is widely used in image processing, which significantly improves the performance of image classification detection. Based on the current status of concrete structure defect detection technology, this experimental study on the detection of concrete structure defects using impact echo was conducted. Focusing on the unsteady features of the impact echo signal, we adopted wavelet transforms at different scales to extract the wavelet spectrum. At the same time, the convolution and subsample operation were combined to establish the recognition system of concrete structure defect detection based on the deep learning network. The research results show that this system can accurately recognize defects in the concrete structure and has high detection accuracy in the concrete structure assessment process.

Distinction between crack echoes and rebar echoes based on Morlet Wavelet Transform of impact echo signals

In an Impact-Echo (IE) test, the Fast Fourier transform (FFT) of the impacted surface responses reveals frequency peaks of major periodical events and can be used to determine depth information, such as the thickness of a target specimen and the depth of a delaminated crack. Since rebar interfaces also result in comparable spectral frequencies but with different depth characteristics, IE testers might have difficulty to determine whether a certain peak frequency is associated with a crack or a rebar. This paper aims to illustrate the use of the time-frequency analysis with Morlet Wavelet transform (MWT) to discriminate the crack response from the rebar response. In additional to the traditional FFT spectrum, the time-frequency technique provides more informative data to assist the analysis task.The proposed method for recognizing crack and rebar can be carried out first by analyzing the peak frequencies in the FFT spectrum. Next, the amplitude histogram at the selected frequency is extracted from the time-frequency spectrogram. Through evaluating the decay pattern of the amplitude curve, an index representing the “duration of amplitude-decay” is defined. Based on the comparison between results of the two studied interfaces, namely concrete-void and concrete-steel, it is preliminarily summarized that the reflected signals are generally less significant at the concrete-steel interface. A rebar leads to weaker reflective energy and thus shortens duration of amplitude-decay. Therefore, it is concluded that the proposed methodology can be applicable to distinguish the difference between the crack echoes and the rebar reflections based on the spectrogram obtained with the time-frequency analysis. Accordingly, this innovated technique provides analysts with an alternative scheme in the recognition/verification of cracks and rebars via the IE tests.

Time-Frequency Analysis of Impact Echo Signals of Grouting Defects in Tunnels

Abstract—Defects in the grouting layer are hidden problems of underground engineering quality, while it plays an important role in the stability of the overall structure of the tunnel segment, the earth pressure transmission and impermeability. There is no accurate means for the detection of the grouting layer so far. As a non-destructive testing method with single detection surface, the impact-echo method is widely used in the detection of cracks, delamination, voids, etc. in concrete structures. In this paper, the impact-echo method was used to detect the grouting defect in grouting-segment structure. Combined with the finite element and the test structure, the signal was analyzed in the time-frequency domain. The results show that the finite element results are in good agreement with the experimental results and the accuracy of frequency distribution characteristics results meets the engineering needs. The time-frequency analysis can provide a foundation for the qualitative judgment of defects.

HHT-Based CEEMD to Improve an Impact Echo Test

Abstract An impact echo (IE) test is a common, low-strain integrity test used to evaluate the thickness and inner condition of concrete plates. The vibration signal propagating along the thickness of a plate is of concern. However, the measured signal includes other waves, such as surface waves, reflective waves, noises from the environment, and so on. These unwanted signals affect the detection of plate integrity. The Hilbert–Huang transform (HHT), which is based on complementary ensemble empirical mode decomposition (CEEMD), has been found to distinguish and interpret IE signals effectively. This method breaks signals down into several meaningful ingredients called intrinsic mode functions (IMFs). CEEMD can also substantially reduce mode mixing and the final residue. The critical parameters of CEEMD are studied by coherence in the frequency domain, and their performance is demonstrated in this study. A Hilbert spectrum analysis is also proposed to distinguish various types of IE signals and enhanced to explain its properties. After obtaining the IMF of the echo wave, the corresponding frequency of the peak magnitude could be used to calculate the interface position. In addition, an approach is also proposed to calculate the depth interface using the IMF phase information, and the result shows that it can be evaluated successfully.

Monitoring the internal quality of ornamental stone using impact-echo testing

The decay and durability of stone materials is a natural response to the progressive adjustment to different environmental and harsh conditions. Usually stone building elements with no apparent sign of decay are affected by the loss of cohesion. Non-invasive, early and low-cost identification of the internal damage of stone materials would be a great step forward.This paper presents an impact-echo (IE) method to analyse the internal quality of ornamental stone. The proposed method attempts to estimate the P-wave velocity in the material applying a frequency estimator that best explains the energy distribution of the possible modes of vibration from the captured IE signals. The velocity estimation will be analysed along a set of freeze-thawing cycles in order to establish a correlation with the internal damage caused in the material confirmed by its porosity. This value has been measured after several freezing-thawing cycles at each stone specimen.Experimental results show that the proposed method can be considered as a valid and effective tool for determining the internal damage of ornamental stone materials. Besides, the proposed method could be easily adapted to analyse specimens of different sizes, shapes and types of rocks.

Analysis method of impact echo based on variational mode decomposition

The Impact Echo (IE) method is a widely used method for the detection of concrete structures. The signal has non-stationary characteristics. Empirical mode decomposition (EMD) is one of the typical ways of dealing with non-stationary signals. Due to EMD having mode overlap and a breakpoint effect, Variational Mode Decomposition (VMD) has been proposed to overcome these problems. In this study, VMD is introduced into the analysis of the concrete component detection signals, and the impact echo analysis method based on VMD and marginal spectrum is established. The proposed method to solve the marginal spectrum is used in order to analyze the numerical simulation model’s IE signal. This method is able to correctly obtain the main frequency. When compared with the traditional Fourier spectrum, the marginal spectrum that is based on the VMD method shows that the band width that is present in the main frequency is narrow. Even in the presence of a highly noisy background, the method is able to correctly obtain the main frequency. At last, through the detection signal analysis of the non-defective concrete specimen and the concrete specimen with the circular hole, the results show that the proposed method can distinguish the signal in the different defective states of the concrete structures, which has obvious advantages compared with the Fourier spectrum.

Research on signal processing of segment-grout defect in tunnel based on impact-echo method

In shield tunneling construction, grout of precast concrete segments is widely applied to various geological conditions. However, the connection performance between the grout and segments after the grout cannot be determined by destructive means, such as coring. The impact-echo method is used extensively in nondestructive testing of civil engineering structures. Nevertheless, there are inadequate researches on determining defects in segment-grout structure. In this paper, the segment-grout structure was simulated experimentally and artificial defects were introduced in the grout. The Short-time Fourier Transform (STFT) and Wavelet Transform (WT) of signals obtained by the impact-echo method were carried out to analyze the time-frequency domain features of the impact-echo signals with and without defects in the grout. On this basis, defects in the grout layer were determined. Finally, energies of wavelet packet were calculated and characteristic relative energy indexes of wavelet packet at different positions were detained. It’s found that the values at positions without defects are relatively low. It’s demonstrated that the signal analysis of impact-echo method has to combine time-frequency domain information and energy distribution for detection of defects in the grout layer. Wavelet transform and energy analysis methods are effective means to detect defects in the grout layer.

Wall-climbing robot for non-destructive evaluation using impact-echo and metric learning SVM

The impact-echo (IE) acoustic inspection method is a non-destructive evaluation technique, which has been widely applied to detect the defects, structural deterioration level, and thickness of plate-like concrete structures. This paper presents a novel climbing robot, namely Rise-Rover, to perform automated IE signal collection from concrete structures with IE signal analyzing based on machine learning techniques. Rise-Rover is our new generation robot, and it has a novel and enhanced absorption system to support heavy load, and crawler-like suction cups to maintain high mobility performance while crossing small grooves. Moreover, the design enables a seamless transition between ground and wall. This paper applies the fast Fourier transform and wavelet transform for feature detection from collected IE signals. A distance metric learning based support vector machine approach is newly proposed to automatically classify the IE signals. With the visual-inertial odometry of the robot, the detected flaws of inspection area on the concrete plates are visualized in 2D/3D. Field tests on a concrete bridge deck demonstrate the efficiency of the proposed robot system in automatic health condition assessment for concrete structures.

Finland: Huntsman – TiO2

The paper presents the nature of elastic wave transition obtained in the time domain and the wave propagation velocity for the impact-echo method employed on the surface of concrete cubes 0.15 × 0.15 × 0.15 m3 subjected to heating in the temperature range of 200–1000 °C. The relations between the characteristics of the obtained impact-echo signal and the mechanical properties of concrete subjected to high temperature were presented as regression curves. The paper proposes certain formulas to be employed while assessing fire-damaged concrete element. The results obtained on fire damaged concrete slab 1.2 × 1.0 × 0.3 m3 indicate a strong relation between the impact-echo parameters and the mechanical properties of concrete.

Recognition of rebars and cracks based on impact-echo phase analysis

The impact-echo test is often used to detect defects or inclusions in concrete structures. Applying Fourier transform to the surface response of the target structure due to an impact, the depth of the interface can be determined through the impact-echo equation. Although the impact echo spectrum may reveal the existence of an interface in the structure, it cannot tell whether the interface results from a crack or rebar. Such information is crucial in the structural safety assessment and to determine interface depth because the impact-echo equations for cracks and rebar differ.This research proposes using the phase spectrum to differentiate crack echoes from rebar echoes. Both the amplitude and slope of the phase spectrum at the echo frequency are studied. Fourier analysis of the simplified signals shows that the phases of crack echoes are nearly 0, while those of rebar echoes are nearly π/2. Numerical and model tests were conducted to verify the results. As expected, the phases can be successfully divided into two groups. The phases of crack echoes are less than π/4 and cluster around 0, while the phases of rebar echoes exceed π/4 and cluster around π/2. Unfortunately, the slope of the phase spectrum at the echo frequency cannot serve as an index for the classification of inclusion type.Hence, it is suggested that both the magnitude and phase spectra be constructed in the Fourier analysis of the impact echo signals. Use the magnitude spectrum to determine the echo frequency and use the phase spectrum to determine the phase at the echo frequency. Then, use π/4 as a threshold to judge the type of inclusion. As such, one can obtain the correct type and depth of the inclusion.

On the evaluation of interface quality in concrete repair system by means of impact-echo signal analysis

According to Concrete Repair Manual as well as ACI 562-16 and European EN 1504-10 standards, a bond strength as a measure of adhesion is one the main feature of repair system necessary to be assessed. The most common laboratory and engineering method for bond strength evaluation is pull-off test. This is however a semi-destructive method that needs a repair in a place of measurement. Recently, the great interest in nondestructive techniques (NDT) development is noted. Impact-echo (IE) is considered as one of the most promising methods for this purpose.In this paper, the study on the usability the IE test based on frequency spectrum analysis for bond strength evaluation is analyzed. Both Finite Element Method (FEM) simulation and experimental tests were performed in order to obtain potential relations between IE frequency spectrum and parameters characterizing concrete substrate quality that may affect the final bond strength and the real value of pull-off bond strength measured on samples as well. It was concluded that the IE method can be a useful tool for interface quality and bond strength evaluations in concrete repair system. However, more complex signal analysis, e.g. wavelet analysis, should be considered in the future.

Multi-bandwidth wavelet transform of impact echo signals for delamination detection of thin concrete slabs

In this study, a multi-bandwidth wavelet transform of signals with mixed frequencies from multiple delamination mechanisms is proposed to achieve the time and frequency resolution required in delamination detection. It was applied to detect six embedded defects, simulating shallow and deep delamination, in a 60 in. × 36 in. × 7.25 in. reinforced concrete slab from impact echo signals recorded at 40 points using a portable seismic property analyzer. Test results indicated that the proposed transform successfully detected all the defects and was twice as accurate as Fourier transform for the identification of resonant frequencies. Out of the 40 measurement points, the false detection points were reduced from 22 with Fourier transform to 10 with the proposed transform.

Concrete Condition Assessment Using Impact-Echo Method and Extreme Learning Machines.

The impact-echo (IE) method is a popular non-destructive testing (NDT) technique widely used for measuring the thickness of plate-like structures and for detecting certain defects inside concrete elements or structures. However, the IE method is not effective for full condition assessment (i.e., defect detection, defect diagnosis, defect sizing and location), because the simple frequency spectrum analysis involved in the existing IE method is not sufficient to capture the IE signal patterns associated with different conditions. In this paper, we attempt to enhance the IE technique and enable it for full condition assessment of concrete elements by introducing advanced machine learning techniques for performing comprehensive analysis and pattern recognition of IE signals. Specifically, we use wavelet decomposition for extracting signatures or features out of the raw IE signals and apply extreme learning machine, one of the recently developed machine learning techniques, as classification models for full condition assessment. To validate the capabilities of the proposed method, we build a number of specimens with various types, sizes, and locations of defects and perform IE testing on these specimens in a lab environment. Based on analysis of the collected IE signals using the proposed machine learning based IE method, we demonstrate that the proposed method is effective in performing full condition assessment of concrete elements or structures.

Semi-supervised Bayesian classification of materials with impact-echo signals.

The detection and identification of internal defects in a material require the use of some technology that translates the hidden interior damages into observable signals with different signature-defect correspondences. We apply impact-echo techniques for this purpose. The materials are classified according to their defective status (homogeneous, one defect or multiple defects) and kind of defect (hole or crack, passing through or not). Every specimen is impacted by a hammer, and the spectrum of the propagated wave is recorded. This spectrum is the input data to a Bayesian classifier that is based on the modeling of the conditional probabilities with a mixture of Gaussians. The parameters of the Gaussian mixtures and the class probabilities are estimated using an extended expectation-maximization algorithm. The advantage of our proposal is that it is flexible, since it obtains good results for a wide range of models even under little supervision; e.g., it obtains a harmonic average of precision and recall value of 92.38% given only a 10% supervision ratio. We test the method with real specimens made of aluminum alloy. The results show that the algorithm works very well. This technique could be applied in many industrial problems, such as the optimization of the marble cutting process.

Nondestructive Test Method for Cement Grouting in Corrugated Pipe Based on Systemic De-Convolution Technique

In order to determine the cement grouting compactness, a new method is proposed for echo signals processing. A model containing four different defects is constructed and simulated using finite element method (FEM). The collected impact-echo signals are processed by systemic de-convolution. It is found that the surface depth of the defect is directly related to the beginning time of the head wave after de-convolution. Using this method, the defect position and dimension can be obtained.

Application of Information Entropy in the Cement Grouting Test Using Impact Acoustics

The unqualified corrugated pipe grouting quality in bridges will lead to serious safety accidents. The sound field propagation in corrugated pipe structure was simulated and analyzed using finite element method, a much complex wave propagation characteristic is demonstrated, and the scattering signals caused by grouting defect are hardly distinguished. The collected impact-echo signals were processed by signal processing of information entropy technology. It is found the defect size is directly related to the information entropy. Several simulated models are constructed and measured, and the bigger size defect is, the lower entropy value is.

The Corrosion Status of Reinforced Concrete Structure Monitoring by Impact-Echo Method

The paper deals with the study of dominant frequencies of an Impact-Echo method response signal obtained from a reinforced concrete beam with a steel rod diameter of 8 mm. Tension pulse was produced in axis of the rod at one end and detected in axis at opposite end of rod. Dominant frequencies of the response signal will be the main criterions for the reinforced concrete rebar corrosion progress. The article presents the results of measurements obtained after 12 months controlled degradation in aqueous NaCl solution. The results were compared with measurements of electrical resistance of reinforcing steel by using the Thomson double bridge.

Using of Impact-Echo Methods to Assessment of Reinforced Concrete Structures Corrosion

The paper deals with the study of dominant frequencies of an Impact-Echo method response signal obtained from a reinforced concrete beam with a steel rod diameter of 8 mm. Tension pulse was produced in axis of the rod at one end and detected in axis at opposite end of rod. Dominant frequencies of the response signal will be the main criterions for the reinforced concrete rebar corrosion progress. The article presents the results of measurements obtained after 12 months controlled degradation in aqueous NaCl solution. The results were compared with measurements of electrical resistance of reinforcing steel by using the Thomson double bridge.

S7-13 Detecting Voids in Tendon Ducts of Post-Tensioned Bridge Girders

The tendon ducts in post-tensioned bridge girders must be grouted fully so as to prevent water and oil stain from entering the ducts, which will decrease the durability and load-carrying capacity of post-tensioned bridges badly. This paper describes the motivations for and recent history of Impact-Echo (IE) scanning applications to internal grout condition evaluation of tendon ducts in post-tensioned girders. The tendon ducts’ internal injection quality of a railway bridge in Yichang city was evaluated using IE technology. During the in-situ testing, the IE signals were collected firstly, then the transformation from the time to the frequency domain was carried out using the principles of the fast Fourier transform, data interpretation was much simpler and quicker in the frequency domain. The grout condition of tendon ducts could be determined according to the frequency analysis, poorly grouted sections can be differentiated from the well-grouted sections within the tendon ducts. Results show that the IE method can be employed to detect voids in the grouted tendon ducts of many types of post-tensioned structures.

Multisensor data fusion for impact-echo testing of concrete structures

Based on the investigation of spatial variations of impact-echo signals for different source and receiver locations, a simple multisensor data fusion strategy is proposed to increase the accuracy of nondestructive evaluation of concrete structures using the impact-echo test. The data fusion strategy fuses the ratios between spectral amplitudes of the delamination and concrete bottom echo signals (D/B ratios) from multiple source–receiver arrays. The fused D/B ratios demonstrate different characteristics for test locations above the delamination, above the sound concrete, and across the delamination boundary. These characteristics can be used to accurately locate the delamination and its boundaries without increasing testing time. The applicability of the multisensor data fusion for impact-echo testing is validated using both numerical simulation and experimental testings.