Characterization And Analysis Of Fatigue Micro-Damage Accumulation In Metal Material Based On Acoustic Emission

Micro-damage evolution process of metal materials under fatigue load involving multi-sclae damage initiation,propagation,coupling and other complex physical phenomena.This paper researched the characterization of fatigue damage based on one probabilistic entropy approach.The low carbon structural steel Q235 is widely used in the manufacture of building,bridge,ship and other engineering structures.During these structures servicing time,most of them will sustain to cyclic load.Thus fatigue analysis should be important aspects in the design and testing operations of these structures.Based on the interconnectedness of fatigue damage in Q235 steel under dynamic and static loads,the material intrinsic damage distinction induced by dynamic fatigue load could be measured through static load response indirectly,and finally with the help of probabilistic entropy approach,the material damage evolution status could be evaluated effectively.Specifically,based on acoustic emission technique possesses a high sensitivity to the material micro-damage events,we estimated material fatigue damage status by acquiring the AE signal of specimen after different fatigue loading cycles during the static loading process.In view of the collected massive acoustic emission signals,a multicomponent stochastic damage variate has been established to characterize the damage energy scale and the time sequence characteristics,and then through the analysis of the multicomponent stochastic variate to study low carbon steel in different micro damage evolution characteristics of fatigue condition.Finally,by calculating the probabilistic entropy of multicomponent stochastic damage variate with different fatigue loading cycles,a characterization of the material fatigue micro-damage evolution was given.Result through experiment and suppleruented by the material cross section of the scanning electron microscope observation was that,the probabilistic entropy curves of low carbon steel after different fatigue loading cycles were significant different,the effective micro-damage probabilistic entropy based on acoustic emission detection was expected to become an effective parameter for presenting the status of material fatigue damage,which laid the foundation for further quantitative analysis of Q235 steel material.The main works that had been finished in this paper are as follows:1.Implementing a composite pattern to fuse the dynamic fatigue loading process and quasi-static uniaxial tensile test,the internal inherent micro-damage of material after the process of dynamic fatigue loading can be determined indirectly.2.On the basis of traditional mechanical parameters and observed original acoustic emission signal,we compared the results of test and inspection preliminary,and relying on the Andrews Plot,an exploratory damage data clustering analysis approach,to put forward the follow-up analysis guidance;3.According to the multivariate statistical analysis method,a multicomponent stochastic damage variate based on the acoustic emission signal data Da matrix has been established to implement dynamic meso and micro description to the micro damage system;4.Combining with the observation analysis of SEM microscopic characteristics,the changes of material microstructure were reflected directly,and the fatigue damage and mechanism of materials were evaluated and described according to the method of probability entropy.According to the results based on the traditional fracture mechanics parameters and acoustic emission original signal,it's hard to contain the difference of damage and behavior response of material with different fatigue loading cycles under the same condition test process.But with the quantitative of probabilistic entropy value,the statistical method based on multicomponent stochastic damage variate represented different damage evolution trends of the different fatigue damage contained Q235 steel,and SEM observation had one fine correspondence.This indicates that the probabilistic entropy of damage based on acoustic emission detection is expected to be an effective parameter to characterize the fatigue damage status of materials,which laid a foundation for the prospective fatigue life prediction of metal materials.