Font Size: a A A

Research And Realization Of Visual Detection Method For Common Manufacturing Errors Of Complex Internal Cavity Parts

Posted on:2020-05-16Degree:MasterType:Thesis
Country:ChinaCandidate:J H WuFull Text:PDF
GTID:2381330599953360Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
Digital manufacturing error detection technology has been applied more and more widely.The main process of this method is to obtain the 3d measurement model of the parts to be tested by digital scanning method,and then compare it with the corresponding CAD standard model,so as to analyze and evaluate the manufacturing error.Because the 3d measurement model is only compared with the CAD standard model as a whole,the overall manufacturing error cannot reflect the size,shape and position error of the mechanical part to be tested.At the same time,general digital scanning means,such as CMM,laser scanning technology,can only get the surface model of the parts to be tested,if the mechanical parts have a complex cavity structure,the manufacturing error in the cavity structure can not be detected.In view of the above problems,this paper proposes a common manufacturing error detection method based on CT slices.Firstly,the 3d measurement model of the mechanical part scanned by industrial CT technology is registered with the CAD standard model.Because the industrial CT technology can measure the internal structure of the mechanical part,when the mechanical part under test has an internal cavity structure,the 3d measurement model can contain the surface model of the internal cavity structure at the same time.Then the 3d measurement model is segmented to obtain the measurement information of each surface in the mechanical parts.Finally,the common manufacturing errors of mechanical parts are analyzed.The method can also visualize the parts that are not within the tolerance range by comparing the set tolerance value with the calculated error value,and visually show the areas that do not meet the processing requirements,providing a reference for the judgment of product quality and the improvement of manufacturing process.The specific research content and work done are as follows:(1)IGES model was used as CAD standard model,and NURBS surfaces in it were point sampled to get the point convergence of IGES model.Then,it was registered with the 3d measurement model of mechanical parts scanned by industrial CT technology to prepare for the follow-up work.(2)In order to calculate the specific manufacturing error,it is necessary to carry out point cloud segmentation for the three-dimensional measurement model of mechanical parts,and obtain the measurement information of each surface in the mechanical parts.The Euclidean distance between each point in the 3d measurement model and the CAD standard model is calculated,and the relationship between the projection point of the point and each surface is determined,so as to determine the attribution surface of each point in the 3d measurement model and complete the point cloud segmentation of the 3d measurement model.(3)Point cloud segmentation is completed,the surface points obtained by fitting the segmentation are gathered together,and the specific information of each surface is obtained.Different error analysis methods are used for different manufacturing errors.In this paper,length and dimension error,planeness error,cylindricity error,face-to-face parallelism error and face-to-face perpendicularity error are calculated and analyzed.At the same time,the tolerance value is introduced to compare the input tolerance value with the calculated error value,and the processing area where the error value is not within the tolerance band is visualized.(4)The above research content set into a software application system,developed a can detect the common manufacturing errors of mechanical parts application,and then carry out example verification and demonstration,to prove the effectiveness of the method.
Keywords/Search Tags:Manufacturing Error, Cavity Structure, Digital Detection, Point Cloud Segmentation, Visualization
PDF Full Text Request
Related items