Damage Identification And Characterization In Steel-concrete Composite Beams Using Acoustic Emission

Steel-concrete composite beams,typically consist of concrete slab,steel beam and shear connectors,are increasingly being employed in medium-span bridges because of the high stiffness and ductility,low structure height and high load-carrying capacity.However,damages are likely to occur at interfacial defection between concrete and steel beam,shear connectors,and concrete in the hogging region,results in loss of structural stiffness and durability,affects the overall safety of the structures.Acoustic emission(AE)technique was used to damage detection and characterization for steel-concrete composite beams in this thesis.Empirical wavelet transform and Akiake information criteria was used to precisely pick arrival time,and Genetic Algorithm was further proposed for source location accurately.Based on the moment tensor analysis and parameter analysis,the mechanism of steel-concrete composite beams was characterized quantitatively.The main contents are listed as follows:(1)Steel-concrete composite beams push-out test were monitored by acoustic emission testing.The variation characteristics of AE ringing counts,energy,and peak frequency at each loading stage were discussed.Results showed cumulative ringing count and cumulative energy and the ratio of the AE peak frequency in the high frequency band can qualitatively distinguished stages of damage initialization,propagating,and failure.Furthermore,two failure modes of steel-concrete composite beams push-out test,shear connectors failure and concrete punching failure,can be qualitatively distinguished by AE ringing counts,energy,and peak frequency parameters.To further damage characterization,Akiake information criteria and Genetic Algorithm was used for different damage source location.pencil lead break test data were used to source location comparison among threshold-Geiger method,Akiake information criteria-Geiger method,Akiake information criteria-Simplex method,and proposed method.The location accuracy and robust of proposed method were found superior to other methods.Then the damage sources in the push-out test like bond-slip,shear failure of studs and concrete cracks were located through proposed method.(2)Steel-concrete composite beams bending test under hogging moment were monitored by acoustic emission testing.Empirical wavelet transform was used as a filter to determine dominate frequency component to reduce the attenuation,scattering,absorption and dispersion phenomenon of AE waves propagated in the large size concrete slab.With the help of empirical wavelet transform,Akiake information criteria and Genetic Algorithm achieved higher crack location accuracy,which was proved through pencil lead break test data.(3)Based on the higher precise damage sources localization,concrete cracks were classified into three types of crack mode and crack motion orientations were identified by moment tensor analysis,where P-wave first motion was picked from dominate frequency component of empirical wavelet transform.Another crack classification results of the parameter analysis were demonstrated a good agreement with moment tensor analysis.As a result,dominant motions of micro-cracks were found to be tensile crack,which is the dominant mechanism of concrete cracks in the hogging moment and interface debonding.