Quality Prediction of Complex Castings in Sand Casting Driven by Heterogeneous Data from Multiple Sources
Sand casting complex castings will appear cold insulation,porosity,sand holes,shrinkage holes and other defects,it is necessary to predict the quality of castings.Among them,the factors affecting casting quality include process parameter data and product three-dimensional structure,but the three-dimensional structure of castings is complicated,there are difficulties in characterization,and the relationship between morphology and casting forming quality can not be determined.Aiming at the above goals and problems,this paper carried out a research on quality prediction of complex sand casting driven by heterogeneous data from multiple sources.Firstly,the structured process parameter data and product 3D structure of sand mixing molding,melting and casting were collected.Secondly,the deep convolutional autoencoder is constructed to realize the feature extraction of complex casting 3D structure and obtain the feature data.Finally,a quality prediction model of complex sand casting driven by process and three-dimensional heterogeneous data was built to accurately predict the casting defects.
NETL
NSTL
万方数据
