3D Image Processing And Analysis Of The Structure Of Composite Materials

Traditional materials have been difficult to meet the demands for high productquality because of the rapid development of science and technology. Compositematerials have been widely used in the industry, because they can bring together in asingle material the benefits of various components. Since composite materials becamethe basic materials of aerospace engineering, their structure and quality have attractedpeople’s attention. Nondestructive testing and evaluation has been widely used in theinspection of composite materials in order to guarantee safety during their manufactureand operation. Micro-CT has been proved to be an effective method for analyzing theinternal structure of composite materials in recent researches.As an important part of composite materials, metal matrix composites havebecome a material of broad technological and commercial significance. The distributionof reinforced phases and pores play an important role in the metal matrix composites.Thus it is essential to assess those defects using nondestructive methods. In this thesis,capability of Micro-CT in analyzing the pores and clustering of reinforced phases inmagnesium matrix composites fabricated by stirring casting was investigated.In order to optimize the quality of tomographic images, experiments wereperformed to get better technological parameters of the Micro-CT equipment.Detectability of the Micro-CT equipment under these paraneters was assessed by spatialand density resolution method. The analytical results have shown that the Micro-CTcould distinguish two tiny structures (the size of them should bigger than36μm) whosedensity difference was bigger than0.5%under these paraneters. The density differencebetween magnesium matrix and SiC particulate is77%, so it can be easy to discernbetween the two which are the components of SiC particle reinforced Mg matrixcomposite using micro-CT. With these parameters, the tomographic images of the SiCparticle reinforced Mg matrix composites with different concentrations of SiC wereobtained.A scheme based on the image edge extraction and wavelet transformationalgorithm for the noise removal in tomographic images was presented. Theenhancement methods for the tomographic images were studied by means of imagestacking. The quality of most tomographic images was improved by using thesemethods. The processed tomographic images of the magnesium matrix composite weregot and compared with results of the EDS analysis. The results showed that thegrayscale of the tomographic image has a closely relationship with the composition ofthe material. An automatic segmentation method was presented and translated into programwith Matlab language. The classification of the image pixels was realized using thisprogram.3D images were generated by volumes rendering in which individual poresand clustering were clearly resolved, along with portions of the magnesium matrixstructure. For quantitative analysis of pores and clustering of the reinforced phases inmagnesium matrix composites, some criterions were presented. These criterions canprovide an effect method for the preparation and analysis of composite materials.