Acoustic Emission Characterization And Pattern Recognition Of Fracture And Failure Process Of Asphalt Mixture

Cracking is one of the major distresses in asphalt pavements.Understanding the damage mechanism of asphalt mixtures is essential to make effective maintenance decisions and prolong the service life of asphalt pavements.As a kind of typical heterogeneous material,asphalt mixtures exhibit complicated mechanical performance and damage behavior under the action of vehicle load and environment.Acoustic emission?AE?technique can effectively detect minor damage and evaluate material mechanical properties.The objective of the paper was to diagnose the damage source,distinguish the damage features and characterize the damage behavior by investigating the relationship between the continuous mechanical process and the AE process of asphalt mixtures.Firstly,based on the wavelet transform?WT?and the fractal theory,the AE behaviors of asphalt mixtures at different damage stages were explored by evaluating the variation characteristics of AE parameters and waveforms.Secondly,the temporal-spatial variation of AE parameters was studied to observe the crack propagation path and to characterize the irreversibility of fatigue process of asphalt mixtures.Finally,the catastrophe theory and the pattern recognition technique were utilized to identify the critical fracture condition and analyze the AE characteristics of asphalt mixtures.The following major conclusions were achieved from this study.?1?The periodic changes of cumulative AE energy and AE count are associated with the mechanical behavior of asphalt mixtures.Their rapid increases corresponding to different loading levels sensitively reflect the development of fractures of the specimen under different loading rates.With the application of continuous wavelet transform?CWT?and discrete wavelet transform?DWT?,the variation of time-scale characteristics of AE signals could reflect the damage evolution of asphalt mixtures at different loading stages.According to the fractal results of various AE parameters,the fractal dimensions of AE energy are the same while that of AE count,hit and event are different,which reveals that AE energy presents a stable fractal response to the flexural failure process of asphalt mixtures under different loading rates.The mutational rise of the waveform fractal dimension from the minimum value is related to the formation of fracture zone of asphalt mixtures.?2?With the increase of rest time,the magnitude of AE energy decreases,and the feature of "blank area" gradually disappears at the stage of microcracks initiation and concentration,demonstrating that asphalt mixture has a better resistance to deformation.The AE amplitude b-value could be considered as a precursor to the rupture of asphalt mixtures.The spatial distribution of AE events from disorder to order reflects the influence of the microstructures of asphalt mixtures and loading mode on crack propagation.The change of Felicity ratio could be divided into three stages,corresponding to the deformation and compaction stage where 1?R_F,microcracks initiation and concentration stage where 0.4?R_F<1,and macrocracks extension stage where R_F<0.4.The Kaiser effect of AE process mainly occurs in deformation and compaction stage of asphalt mixtures.Once entering the stage of microcracks initiation and concentration,Kaiser effect gradually disappears and Felicity effect begins to play a role.The wavelet scalogram of AE waveform could identify the micro damage mechanism associated with the Kaiser effect and the Felicity effect.?3?The average frequency?AF?and rise time/amplitude?RA?of AE signals could effectively distinguish the main cracking mode of asphalt mixtures at different damage stages.During the initiation and extension of fatigue crack,the AF value decreases and RA value increases.With the propagation of main crack,AF value increase while the trend of RA value tends to be stable.The AE process of asphalt mixtures exhibits catastrophe characteristics.The cusp catastrophe model established based on cumulative AE energy could be applied to identify the critical fracture condition of fatigue crack that develops from microscopic to macroscopic.The self-organizing map?SOM?neural network established by AE energy,AF and RA could effectively distinguish the AE characteristics related to the damage behavior of asphalt mixtures at different stages.The classification results of AE characteristics would be more concentrated when the fatigue crack changes from micro to macro,revealing that the order degree of AE process improves.The study would hopefully give an insight into the AE behavior and its characteristics of asphalt mixtures under different loading conditions and provide a support for damage diagnosis and performance evaluation of asphalt pavements.