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Research On Ultrasonic Testing Methods Of Volume Fraction Of LPSO Phases Of Magnesium Alloy

Posted on:2022-03-16Degree:MasterType:Thesis
Country:ChinaCandidate:S YangFull Text:PDF
GTID:2481306608997819Subject:Mechanical engineering
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As a lightweight structural material,magnesium alloy has high specific strength,excellent damping and easy recycling,which has a wide range of application prospects in transportation,aerospace,electronic communications,medical equipment and the other fields,but the absolute strength of magnesium alloy is low.In recent years,long period stacking ordered(LPSO)phases have been formed by adding elements such as Zn,Cu or Ni to Mg-RE alloy,and adjusting the alloy composition,temperature and cooling conditions reasonably.The change of the volume fraction of LPSO strengthening phases greatly improves the mechanical properties of Mg alloy,such as tensile strength,compressive strength and ductility.Therefore,volume fraction detection of LPSO phases plays an important role in understanding the properties of the alloy.The ultrasonic detection technology has the advantages of high sensitivity and superior accuracy.Therefore,it is used for quantitative evaluation of the volume fraction of LPSO phases of magnesium alloy in this paper.Firstly,scanning electron microscope(SEM)image analysis method was studied to calculate the volume fraction of LPSO phases,which was used to verify the measurement error of the results of ultrasonic experimental method.By analyzing the application effect of common image segmentation methods in SEM images of magnesium alloys,and evaluating the quality of image segmentation,the algorithm with high segmentation accuracy was selected to segment the target features of the SEM image.Then,on the basis of successful image segmentation,the volume fraction of LPSO phases in magnesium alloy was obtained by calculating the ratio of pixel number in the target region to the pixel number in the whole image.Secondly,linear ultrasound was used to characterize the volume fraction of LPSO phases.The simulation models of different volume fractions of LPSO phases were constructed based on the finite element theory of ultrasonic simulation.The finite element simulation software was used to perform linear ultrasonic simulations,the attenuation coefficient was calculated,and the relationship between the coefficient and volume fraction of LPSO phases was established.At the same time,the specimens were tested by the pulse reflection method,and the ultrasonic attenuation coefficient was extracted by collecting and processing the received signals.Simulation and experimental results show that the attenuation coefficient decreases with the increase of LPSO phase content in magnesium alloy.Finally,in order to improve the detection accuracy,this thesis conducted research on the extraction of nonlinear effect and volume fraction characterization of LPSO phases based on nonlinear ultrasonic detection method.The finite element simulation software was used to perform nonlinear ultrasonic simulation in the simulation models with different LPSO phases content.The relationship between the volume fraction of LPSO phases and the relative nonlinear coefficient was studied.At the same time,a nonlinear ultrasonic detection system was built to test magnesium alloy specimens with different volume fractions of LPSO phases.Dual tree complex wavelet packet transform(DTCWPT)and empirical mode decomposition(EMD)were used to process the signal,and the relative nonlinear coefficient of DTCWPT-EMD method was calculated.The relationship between the coefficient and volume fraction of LPSO phases was established.The analysis shows that the relative nonlinear coefficient decreases with the increase of LPSO phase content,and the feature extraction method of DTCWPT-EMD is more accurate than linear and nonlinear ultrasonic detection methods,and the accuracy of characterization is effectively improved.
Keywords/Search Tags:Magnesium alloy, Volume fraction of LPSO phases, Finite element, Ultrasonic attenuation, Nonlinear coefficient, Dual tree complex wavelet packet transform, Empirical mode decomposition
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