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Academic Journal of Engineering and Technology Science, 2020, 3(3); doi: 10.25236/AJETS.2020.030313.

Concrete Acoustic Emission Signal Recognition Based on Concrete Acoustic Emission Energy


Zhen Yin*, Lei Qin

Corresponding Author:
Zhen Yin

Department of Civil and Architecture Engineering, University of Jinan, Jinan 250022, China
*Corresponding author e-mail: 1609813335@qq.com


Acoustic emission energy is one of the important characteristic parameters in AE signals. AE energy can reflect the deformation mechanism of materials, AE energy history analysis method can evaluate the activity and development trend of AE sources, AE energy distribution analysis method can be used to evaluate the intensity of AE sources, and AE energy history analysis method and AE energy history analysis method can be used to evaluate the intensity of AE sources The acoustic emission energy distribution analysis method combines the energy, cumulative energy and the change of applied external load with the arrival time, which is used to reflect the basic characteristics of different stages of the acoustic emission signal generated by concrete after external load, so as to realize the recognition of the acoustic emission signal of concrete.


Concrete damage evolution, acoustic emission signal recognition, Damage characterization of concrete, acoustic emission energy

Cite This Paper

Zhen Yin, Lei Qin. Concrete Acoustic Emission Signal Recognition Based on Concrete Acoustic Emission Energy. Academic Journal of Engineering and Technology Science (2020) Vol. 3 Issue 3: 104-112. https://doi.org/10.25236/AJETS.2020.030313.


[1] D.K.Yu (2016). Damage evolution analysis of reinforced concrete beams based on acoustic emission and BP neural network. (Doctoral dissertation).
[2] R.F.Yang and T.H.Ma (2006). A study on the application of acoustic emission technology. Journal of Zhongbei University: Natural Science Edition,vol.16, no.5, p.83-88.
[3]J.Z.Shen and Z.J.Li (2006). Nondestructive testing technology and its application in civil engineering. Nondestructive testing, vol.13, no.11, p.497-500
[4] G.H.Li and M.A.Wu (2009). Modern nondestructive testing and evaluation. Chemical Industry Press J.S, vol.16, no.7, p.239-245.
[5] Q.S.Wang and G.X.Wan (2010). Acoustic emission experiment of rock failure under combined dynamic and static loading. Explosion and impact, vol.30, no.3, p.247-253.
[6] W.Zhou and S.R sun (2013). Acoustic emission behavior of wind turbine blade composite under tensile damage. Journal of composite materials, vol.30 , no.2, p.240-246.
[7] W.Hao and Y.Yuan (2016). Effect of impact damage on the curved beam interlaminar strength of carbon/epoxy laminates. Journal of Adhesion Science & Technology, vol.30, no.11, p.1189-1200.
[8] Wang Meibo (2008). Research on the method of fault signal analysis of rolling bearing based on acoustic method. (Doctoral dissertation).
[9] S.B.Sun and Y.Guo (2017). Double impact feature extraction of fatigue peeling failure of outer ring of rolling bearing based on acoustic emission signal. Vibration and impact, vol.36, no.4, p.1-6.
[10] D.L.Zhang and R.Mo (2015). Tool Wear Recognition Based on chaos time series analysis and support vector machine. Computer integrated manufacturing system , vol.21, no.8, p.2138-2146
[11] M. S. H. Bhuiyan, I. A. Choudhury and M. Dahari(2014). Monitoring the tool wear, surface roughness and chip formation occurrences using multiple sensors in turning. Journal of Manufacturing Systems, vol.33, no.4, p.476-487.
[12] M.Wang, N.J Yang and X.G.Wang (2011). Research status and development trend of acoustic emission detection technology. National Academic Conference on vibration theory and application, vol.35, no.14, p.200-205.
[13] K.Dan (2013). Research on crack damage identification of fan blade material based on Acoustic Emission Technology. (Doctoral dissertation).
[14] F.Qiu, and M.Y Zhang (2015). Identification and location of acoustic emission source of tank floor corrosion. Journal paper, vol.37, no.2, p.14-19
[15] S.M Zhang, R.Yu and D.K.he (2016). Acoustic emission signal recognition method of boiler leakage based on AR and HMM. Journal of Yunnan University: Natural Science Edition, vol.38, no.3, p.383-391
[16] J. Yang (2016). Study on delamination failure mechanism of layered composite materials in humid and hot environment based on acoustic emission technology. (Doctoral dissertation).
[17] S.Yu, L.J Shen, Y.Li (2017). Acquisition and characteristic analysis of the surface of Pinus yunnanensis acoustic emission signalJournal of Northwest Forestry University, vol.32, no.2, p.247-251.