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Acoustic Emission Technology To Identify The Failure Behavior Of Reinforced Concrete

Posted on:2022-10-14Degree:MasterType:Thesis
Country:ChinaCandidate:F N ZhaoFull Text:PDF
GTID:2492306509460814Subject:Highway environmental engineering
Abstract/Summary:PDF Full Text Request
Based on the characteristics that acoustic emission technology is suitable for nondestructive testing of materials,it has been widely used in material damage assessment and real-time structural health monitoring in recent years.Since the transient stress wave is released when the material is damaged internally,the acoustic emission signal is generated.Therefore,the acoustic emission non-destructive testing technology has great advantages in identifying the failure mechanism of reinforced concrete materials at the meso level.Based on the distribution of characteristic parameters such as acoustic emission energy,peak frequency and amplitude,this paper identifies the damage process and damage mode of reinforced concrete materials under bending stress.According to the load curve,acoustic emission energy and b value,three stages of crack development of reinforced concrete materials under bending stress are identified: the initial initiation stage,the crack propagation stage,and the damage failure stage.Based on cluster analysis,three damage modes of reinforced concrete materials were identified according to the distribution law of acoustic emission peak frequency-amplitude:damage to the mortar matrix,coarse aggregate,and damage to the interface transition zone between the steel bar and the mortar matrix,and reinforcement damage.The relationship between the frequency domain characteristics of the acoustic emission waveform and the stress state of reinforced concrete is established.A method for identifying the failure mechanism of reinforced concrete based on acoustic emission characteristic parameters and waveform frequency domain characteristics is obtained.
Keywords/Search Tags:reinforced concrete, acoustic emission, pattern recognition, cluster analysis, signal processing
PDF Full Text Request
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