Discussion of the Definition for Acoustic Emission Event in the Time Series of Concrete Damage Process

2019 ◽  
Vol 55 (2) ◽  
pp. 129-135 ◽  
Author(s):  
Y. Wang ◽  
L. Ge ◽  
T. T. Zhang ◽  
L. Zhou
2013 ◽  
Vol 395-396 ◽  
pp. 515-519
Author(s):  
Zheng Zheng Xu ◽  
Yan Wang ◽  
Sheng Xing Wu ◽  
Yao Wang

Acoustic emission (AE) is capable of real time continuous monitoring and it's not sensitive to the geometry of components,so it's widely used in nondestructive testing of concrete. The AE b-value occupies an important position in the study of concrete damage evaluation as a parameter of AE technology. The basic theory of AE b-value and the related technical problems of AE b-value calculation was discussed. Then the research of AE b-value on concrete was reviewed. At last, the AE b-value in the damage process of cement mortar (CM) and polypropylene diber reinforced mortar (PFRM) under compression was studied and concluded that the trend of AE b-value of CM and PFRM was obviously different.The AE b-value is closely related to the formation and propagation of cracks in the damage process of concrete and it declines rapidly before final fracture occurs.


2020 ◽  
Vol 62 (5) ◽  
pp. 517-524
Author(s):  
Yan Wang ◽  
G. Jie ◽  
W. Na ◽  
Y. Chao ◽  
Z. Li ◽  
...  

Abstract This paper aims to improve the calculation efficiency and accuracy of concrete damage degree identification, and then to analyze the damage mechanism of concrete damage. First, the correlation analysis and principal component analysis of 15 characteristic parameters of acoustic emission signals accompanying concrete uniaxial compression and splitting damage process are performed through which the dimension is reduced into 5 non-correlated principal components. Then, based on the analysis of the relationship between each principal component and the damage and cracking mechanism of concrete, the damage degree of concrete is identified as an input variable of the BP neural network. The results show that the 5 principal components effectively eliminate redundant information and carry information on the failure mechanism of concrete damage and the damage process. Principal component analysis and the neural network are used to achieve the accurate recognition of acoustic emission parameters and the degree of concrete damage.


1989 ◽  
Vol 111 (3) ◽  
pp. 199-205 ◽  
Author(s):  
S. Y. Liang ◽  
D. A. Dornfeld

This paper discusses the monitoring of cutting tool wear based on time series analysis of acoustic emission signals. In cutting operations, acoustic emission provides useful information concerning the tool wear condition because of the fundamental differences between its source mechanisms in the rubbing friction on the wear land and the dislocation action in the shear zones. In this study, a signal processing scheme is developed which uses an autoregressive time-series to model the acoustic emission generated during cutting. The modeling scheme is implemented with a stochastic gradient algorithm to update the model parameters adoptively and is thus a suitable candidate for in-process sensing applications. This technique encodes the acoustic emission signal features into a time varying model parameter vector. Experiments indicate that the parameter vector ignores the change of cutting parameters, but shows a strong sensitivity to the progress of cutting tool wear. This result suggests that tool wear detection can be achieved by monitoring the evolution of the model parameter vector during machining processes.


2021 ◽  
pp. 147592172110188
Author(s):  
Zonglian Wang ◽  
Keqin Ding ◽  
Huilan Ren ◽  
Jianguo Ning

To gain an insight into the evolution of micro-cracks in concrete materials, a quantitative acoustic emission investigation on the damage process of concrete prisms subjected to three-point bending loading was performed. Each of the monitored acoustic emission signals was processed by a two-level wavelet packet decomposition into four different frequency bands (AA2, DA2, AD2, and DD2), and the energy coefficients R1, R2, R3, and R4 that parameterize their characteristic frequency bands were calculated. By analyzing variations in energy coefficients of the lowest frequency band (AA2), R1, and the energy coefficients of the highest frequency band (DD2), R4, the whole damage process was divided into three stages: crack initiation, crack growth, and crack coalescence. An inverse relationship between the frequency of the acoustic emission signal emitted by the propagating crack and the crack size in concrete materials was acquired based on the damage theory of brittle materials and the strain energy release theory. The statistical analysis results of the experimental data indicated that the average of R1 increased in turn, and the average of R4 correspondingly decreased in turn from Stage 1 to Stage 3. It revealed that the frequencies of acoustic emission signals decreased gradually with the evolution of the damage of concrete prisms, which is in a good agreement with the theoretical analysis result.


2021 ◽  
pp. 147592172110446
Author(s):  
Claudia Barile ◽  
Caterina Casavola ◽  
Giovanni Pappalettera ◽  
Vimalathithan Paramsamy Kannan

Signal-based acoustic emission data are analysed in this research work for identifying the damage modes in carbon fibre–reinforced plastic (CFRP) composites. The research work is divided into three parts: analysis of the shifting in the spectral density of acoustic waveforms, use of waveform entropy for selecting the best wavelet and implementation of wavelet packet transform (WPT) for identifying the damage process. The first two methodologies introduced in this research work are novel. Shifting in the spectral density is introduced in analogous to ‘flicker noise’ which is popular in the field of waveform processing. The entropy-based wavelet selection is refined by using quadratic Renyi’s entropy and comparing the spectral energy of the dominating frequency band of the acoustic waveforms. Based on the method, ‘dmey’ wavelet is selected for analysing the waveforms using WPT. The slope values of the shifting in spectral density coincide with the results obtained from WPT in characterising the damage modes. The methodologies introduced in this research work are promising. They serve the purpose of identifying the damage process effectively in the CFRP composites.


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