%0 Journal Article %T 基于图像处理的碳纤维增强树脂基复合材料固化压力-缺陷-力学性能建模与评估<br>Modeling and evaluation of curing pressure-defects-mechanical properties of carbon fiber reinforced resin composites based on image processing %A 李树健 %A 湛利华 %A 周源琦 %A 蒲永伟 %J 复合材料学报 %D 2018 %R 10.13801/j.cnki.fhclxb.20180317.001 %X 利用热压罐成型工艺制备了不同固化压力条件下的碳纤维增强树脂基复合材料层合板，分析了超声相控阵C扫描图像与微观缺陷的对应关系，研究了固化压力、孔隙缺陷及力学性能之间的关联规律。结果表明：利用超声C扫描图像差异能够表征孔隙等缺陷含量，在本实验条件下，固化压力由0 MPa提高到0.6 MPa，复合材料孔隙率降低96.7%，拉伸强度（TS）和层间剪切强度（ILSS）分别提高56.1%和68.8%。在此基础上，对不同固化压力条件下制备的复合材料层合板的超声相控阵C扫描图像进行图像处理并定义成型质量指数，实现了基于C扫描图像对孔隙缺陷的定量表征。最后，通过对孔隙缺陷检测、力学性能测试及图像定量化评价结果进行数学拟合，建立了基于图像处理的固化压力-缺陷-力学性能之间的数学关联模型（CPDMP模型），并给出了成型质量指数阈值为81%，及可接受的孔隙率应不高于1.1%，相应的固化压力应不低于0.35 MPa。 The carbon fiber composite laminates were manufactured in different curing pressures by autoclave process. The relationship between the ultrasonic phased array C scanning image and the defects of microstructure was analyzed, and the correlations among curing pressure, voids and mechanical properties were studied. The results indicate that ultrasonic C scanning image can be used to characterize the content of voids. In this experiment condition, the curing pressure increases from 0 MPa to 0.6 MPa, the porosity decreases by 96.7%, and the tensile strength(TS) and interlaminar shear strength(ILSS) increase by 56.1% and 68.8%, respectively. On this basis, the C scanning images of composite laminate in different curing pressures were processed, and the forming quality index was defined. Thus, the quantitative characterization of voids based on C scanning images was realized. Finally, through mathematical fitting of the results of voids detection, mechanical properties test and image quantitative evaluation, a mathematical model(CPDMP model) among curing pressure-defects-mechanical properties based on image processing was established. In addition, the forming quality index threshold of 81%, the acceptable porosity of more than 1.1% and the corresponding curing pressure of more than 0.35 MPa were presented. 国家重点基础研究发展计划（2014CB046502）；湖南科技大学博士科研启动资金（E51782） %K 复合材料 %K 缺陷 %K 力学性能 %K 图像处理 %K 固化< %K br> %K composite material %K defects %K mechanical properties %K image processing %K curing %U http://fhclxb.buaa.edu.cn/CN/abstract/abstract14297.shtml