Industrial CT (Computed Tomography) multi-dimensional size measurement method for complex workpiece

Abstract

The invention discloses an industrial CT (Computed Tomography) multi-dimensional dimension measurement method for a complex workpiece, which comprises the following steps of: automatically calculating a motion parameter according to a CT detection section, executing a posture adjustment command by a multi-dimensional platform according to the motion parameter, and adjusting the workpiece to a posture required by CT scanning, so that the positioning precision and the position scanning efficiency of industrial CT scanning are improved. Then vectorization and feature extraction are carried out on an image reconstructed by CT scanning data, finally matching with a CAD model is carried out, and error analysis and calculation are carried out on the image and the CAD model. According to the method, the space coordinate conversion parameters of the complex workpiece can be directly calculated, the consistency of workpiece detection is ensured, noise interference is reduced, the error analysis accuracy is improved, and the problems that in industrial CT detection, the scanning coordinate calculation of the complex workpiece is complex, the scanning positioning efficiency is low, and the scanning error analysis precision is poor are solved.

Description

Technical Field

[0001] The present invention relates to the field of industrial CT measurement technology, and more specifically, to an industrial CT multi-dimensional size measurement method for complex workpieces. Background Art

[0002] Industrial CT detection is based on the attenuation and absorption characteristics of radiation in the object being detected. The absorption ability of a substance to radiation is related to the properties of the substance. Therefore, by using the attenuation law and distribution of X-rays or gamma rays with a certain energy and intensity emitted by radionuclides or other radiation sources in the object being detected, it is possible to obtain detailed information inside the object through the detector display, and finally display it in the form of an image using computer information processing and image reconstruction technology. In the industrial CT detection technology of complex workpieces, multiple sections need to be detected, so multiple clamping or multi-axis motion devices are required to adjust the spatial posture of the workpiece. During the detection, the operator is often required to manually adjust the detection posture of the workpiece and perform multiple test adjustments on the area to be inspected in order to basically find the structural defects of the workpiece. The detection process is cumbersome and time-consuming, with low detection efficiency, and the detection results may be distorted and unreliable. In addition, the complexity of the workpiece leads to poor industrial CT detection accuracy, so the detection results affect the judgment of the dimensional accuracy of complex workpieces.

[0003] In CN112903730A, a multi-dimensional posture adjustment device is disclosed, which includes a tilting unit, a rotating unit, a translation unit and a clamping unit; the tilting unit includes a mounting frame, a first shaft and a first motor, a support block is fixedly provided on the first shaft and is laterally rotatably connected to the mounting frame, and the first motor is connected to the first shaft to drive its rotation; the rotating unit includes a connecting block, a second shaft and a second motor, the connecting block is movably connected to the support block, the second shaft is vertically arranged and its top end is fixedly connected to the connecting block, the second motor is connected to the bottom end of the second shaft to drive its rotation, and the second motor is installed on the first shaft; the translation unit is connected to the mounting frame to drive its lateral movement; the clamping unit is installed on the top of the connecting block and is used to clamp the workpiece. The patent can adjust the section to be measured of the workpiece to the required position through the interaction of the rotating unit, the tilting unit and the translation unit, conveniently realize the switching of multiple detection sections of the workpiece, avoid repeated clamping of the workpiece and thus improve the detection efficiency, but does not disclose how to quickly adjust the posture for scanning. In addition, in CN 112669460B, the CT image data of the workpiece to be tested is used to reconstruct a three-dimensional mesh image, and the image is registered with the CAD triangular mesh image, so that the deviation of the workpiece to be tested is quickly obtained. However, due to the interference of image noise in the process of reconstructing the three-dimensional mesh, the vertex position of the three-dimensional mesh contains noise errors, which leads to a large error in the workpiece deviation measured when the slice image is compared with the CAD, especially for parts with higher precision, the test error is even greater. Summary of the invention

[0004] The main technical problem to be solved by the present invention is to provide a multi-dimensional size measurement method for complex workpieces in industrial CT in view of the shortcomings of the prior art in industrial CT detection of complex workpieces, such as complex scanning coordinate calculation, low scanning positioning efficiency, and poor scanning error analysis accuracy.

[0005] The purpose of the present invention is achieved through the following technical solutions:

[0006] A method for measuring multi-dimensional dimensions of a complex workpiece by industrial CT, comprising the following steps:

[0007] S1. Based on the multi-dimensional platform, the scanning plane is preset with three-point spatial coordinates, the posture adjustment parameters are calculated, and the complex workpiece is CT scanned to obtain industrial two-dimensional CT slice images;

[0008] S2. Accurately vectorize the industrial CT image based on the error compensation spatial moment algorithm and then extract features;

[0009] S21. Preprocessing the industrial CT image;

[0010] S22. Extract the image edge, search the edge point set to construct the contour list sequence, perform probabilistic circle detection on the non-empty list, and accurately vectorize the circle that meets the full circle constraint conditions; then insert the circle list;

[0011] S23. Use the set intersection method to perform straight line fitting on other contour chain lists to determine whether the short straight line segments are adjacent. If they are adjacent, merge them into long straight line segments;

[0012] S24. Use the perpendicular bisector method to find the arc and determine whether it forms an arc; perform precise vectorization of the arc contour points and insert them into the arc linked list; calculate the least squares error of the non-arc contour points to perform precise vectorization of the straight line and insert them into the straight line linked list;

[0013] S3. Edit the vectorized graphics and save them as DXF format files;

[0014] S4. Match the graphic primitive features of CT vectorization with the CAD design model, and calculate and analyze the error.

[0015] Furthermore, the coordinates of the three points M1, M2, and M3 on the scanning plane in step S1 are:

[0016] M1(X1, Y1, Z1)

[0017] M2(X2, Y2, Z2)

[0018] M3(X3, Y3, Z3)

[0019] The general equation is: Ax+By+Cz+D=0, where:

[0020] A=(y2-y1)×(z3-z2)-(z2-z1)×(y3-y2)

[0021] B = (z2-z1) × (x3-x2) - (z3-z2) × (x2-x1)

[0022] C=(x2-x1)×(y3-y2)-(y2-y1)×(x3-x2)

[0023] D=x1×((z2-z1)×(y3-y2)-(y2-y1)×(z3-z2))+y1×((z3-z2)×(x2-x1)-(z2-z1)×(x3-x2))+z1×((y2-y1)×(x3-x2)-(x2-x1)×(y3-y2)).

[0024] Furthermore, the posture adjustment in step S1 includes rotating the detection surface around the Z axis to be parallel to the X axis and rotating the detection surface around the X axis to be parallel to the XY plane.

[0025] Furthermore, the detection plane is rotated around the Z axis to be parallel to the X axis. When the detection plane is rotated around the Z axis to be parallel to the X axis, the angle is θ′. After the rotation, the coordinates of M1′, M2′, and M3′ are:

[0026] M1′(X1′, Y1′, Z1)

[0027] M2′(X2′, Y2′, Z2)

[0028] M3′(X3′, Y3′, Z3)

[0029] Where:

[0030]

[0031] According to the general plane equation: Ax+By+Cz+D=0, when the plane is parallel to the X-axis, A=0

[0032]

[0033] Get the rotation angle θ' value around the X axis.

[0034] Furthermore, the detection plane is rotated around the X-axis to be parallel to the XY plane. Assuming that the angle when the detection plane is rotated around the X-axis to be parallel to the XY plane is θ", the coordinates of M1", M2", and M3" after the rotation are:

[0035] M1″(X1′, Y1″, Z1′)

[0036] M2″(X2′, Y2″, Z2′)

[0037] M3″(X3′, Y3″, Z3′)

[0038] Where:

[0039]

[0040] According to the general plane equation: Ax+By+Cz+D=0, when the plane is parallel to the XY plane, A=0, B=0

[0041] A=(Y2”-Y1”)×(Z3’-Z2’)-(Z2’-Z1’)×(Y3”-Y2”)=0

[0042] B = (Z2'-Z1') × (X3'-X2') - (Z3'-Z2') × (X2'-X1') = 0

[0043] Get the value of the rotation angle θ" around the X axis.

[0044] Furthermore, the preprocessing in step S21 includes image enhancement and removal of image artifacts and noise.

[0045] Furthermore, the editing process in step S3 includes connecting similar line segments and deleting redundant line segments and isolated points.

[0046] Furthermore, in step S4, the idea of ​​the minimum bounding box is used to introduce the centroid, and a group of primitive features are selected in a human-computer interactive manner to achieve registration between models.

[0047] Furthermore, in step S4, the functions of fitting a short straight line to a long straight line and a short straight line to an arc are added as the basis for registration.

[0048] Furthermore, step S4 specifically includes:

[0049] S41. CAD design model element information of CT vectorized graphic element pairing;

[0050] S42. discretizing the vectorized primitives of the CT image;

[0051] S43. Calculate the normal error to the CAD model.

[0052] Compared with the prior art, the beneficial effects are:

[0053] The present invention can automatically calculate motion parameters according to the CT detection section, and the multi-dimensional platform executes the posture adjustment command according to the motion parameters to adjust the workpiece to the posture required by the CT scan, thereby improving the positioning accuracy and position scanning efficiency of industrial CT scanning. At the same time, the present invention reduces noise interference and improves the accuracy of error analysis by vectorizing the image reconstructed from the CT scan data, including linear vectorization and circular vectorization. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 Schematic diagram of a multi-dimensional platform.

[0055] Figure 2 A vectorized flowchart.

[0056] Figure 3 For precise vectorization renderings.

[0057] Figure 4 This is the effect diagram of the registration between the vectorized model and the CAD model.

[0058] Figure 5 This is the error effect diagram between the vectorized model and the CAD model. DETAILED DESCRIPTION

[0059] The present invention will be further explained and illustrated below in conjunction with the embodiments, but the specific embodiments do not limit the present invention in any form.

[0060] Example 1

[0061] This embodiment provides a method for measuring multi-dimensional dimensions of a complex workpiece using industrial CT, the steps comprising:

[0062] S1. Figure 1 , based on a multi-dimensional platform, the scanning plane is preset with three-point spatial coordinates, the posture adjustment parameters are calculated, and CT scanning is performed on complex workpieces to obtain industrial two-dimensional CT slice images;

[0063] S2. Accurately vectorize industrial CT images based on error-compensated spatial moment algorithm, such as Figure 2 , and then extract features;

[0064] S21. Preprocessing of industrial CT images, including image enhancement, removal of image artifacts and noise;

[0065] S22. Extract the image edge, search the edge point set to construct the contour list sequence, perform probabilistic circle detection on the non-empty list, and accurately vectorize the circle that meets the full circle constraint conditions; then insert the circle list;

[0066] S23. Use the set intersection method to perform straight line fitting on other contour chain lists to determine whether the short straight line segments are adjacent. If they are adjacent, merge them into long straight line segments;

[0067] S24. Use the perpendicular bisector method to find the arc and determine whether it forms an arc; perform precise vectorization of the arc contour points and insert them into the arc linked list; calculate the least squares error of the non-arc contour points to perform precise vectorization of the straight line and insert them into the straight line linked list;

[0068] S3. Graphics editing processing for vectorization, such as Figure 3 , including connecting similar line segments, deleting redundant line segments and isolated points, and saving vector graphics as DXF format files.

[0069] S4. Select the primitive features to match with the model, and calculate and analyze the error.

[0070] Example 2

[0071] This embodiment provides a calculation method for adjusting the posture parameters of a multi-dimensional platform, with the long side of the multi-dimensional platform as the X-axis, the short side as the Y-axis, the vertical direction as the Z-axis, and the center of the multi-dimensional platform as the zero point. The calculation steps include:

[0072] S11. Set the coordinates of the three points M1, M2, and M3 in the detection surface to:

[0073] M1(X1, Y1, Z1)

[0074] M2(X2, Y2, Z2)

[0075] M3(X3, Y3, Z3)

[0076] And calculate the detection surface function, the plane equation determinant is as follows

[0077] x-x1 y-y1 z-z1

[0078] x2-x1 y2-y1 z2-z1=0

[0079] x3-x2 y3-y2 z3-z2

[0080] have:

[0081] (x-x1)×(y2-y1)×(z3-z2)+(y-y1)×(z2-z1)×(x3-x2)+(z-z1)×(x2-x1)×(y3-y2)- (z-z1)×(y2-y1)×(x3-x2)-(z2-z1)×(y3-y2)×(x-x1)-(z3-z2)×(y-y1)×(x2-x1)=0

[0082] X×(y2-y1)×(z3-z2)-x1×(y2-y1)×(z3-z2)+Y×(z2-z1)×(x3-x2)-y1×(z2-z1)×(x3-x2)+Z×(x2-x1)×(y3-y2)-z1×(x2-x1)×(y3-y2)- Z×(y2-y1)×(x3-x2)+z1×(y2-y1)×(x3-x2)-X×(z2-z1)×(y3-y2)+x1×(z2-z1)×(y3-y2)-Y×(z3-z2)×(x2-x1)+y1×(z3-z2)×(x2-x1)=0

[0083] X×((y2-y1)×(z3-z2)-(z2-z1)×(y3-y2))+Y×((z2-z1)×(x3-x2)-(z3-z2)×(x2-x1))+Z×((x2-x1)×(y3-y2)-(y2-y1)×(x3-x2))+x1 ×((z2-z1)×(y3-y2)-(y2-y1)×(z3-z2))+y1×((z3-z2)×(x2-x1)-(z2-z1)×(x3-x2))+z1×((y2-y1)×(x3-x2)-(x2-x1)×(y3-y2))=0

[0084] The general equation of the plane is Ax+By+Cz+D=0,

[0085] A=(y2-y1)×(z3-z2)-(z2-z1)×(y3-y2)

[0086] B = (z2-z1) × (x3-x2) - (z3-z2) × (x2-x1)

[0087] C=(x2-x1)×(y3-y2)-(y2-y1)×(x3-x2)

[0088] D=x1×((z2-z1)×(y3-y2)-(y2-y1)×(z3-z2))+y1×((z3-z2)×(x2-x1)-(z2-z1)×(x3-x2))+z1×((y2-y1)×(x3-x2)-(x2-x1)×(y3-y2)).

[0089] S12. The detection surface rotates around the Z axis to a position parallel to the X axis;

[0090] Assume that when the detection plane rotates around the Z axis to an angle parallel to the X axis, the angle is θ′. After the rotation, the coordinates of M1′, M2′, and M3′ are:

[0091] M1′(X1′, Y1′, Z1)

[0092] M2′(X2′, Y2′, Z2)

[0093] M3′(X3′, Y3′, Z3)

[0094] Where:

[0095]

[0096] According to the general plane equation: Ax+By+Cz+D=0, when the plane is parallel to the X-axis, A=0

[0097]

[0098] According to the above formula, the rotation angle θ' around the X-axis can be calculated.

[0099] S13. The detection surface rotates around the X axis until it is parallel to the XY plane.

[0100] Assume that when the detection plane rotates around the X-axis to be parallel to the XY plane, the angle is θ", and the coordinates of M1", M2", and M3" after the rotation are:

[0101] M1″(X1′, Y1″, Z1′)

[0102] M2″(X2′, Y2″, Z2′)

[0103] M3″(X3′, Y3″, Z3′)

[0104] Where:

[0105]

[0106] According to the general plane equation: Ax+By+Cz+D=0, when the plane is parallel to the XY plane, A=0, B=0

[0107] A=(Y2”-Y1”)×(Z3’-Z2’)-(Z2’-Z1’)×(Y3”-Y2”)=0

[0108] B = (Z2'-Z1') × (X3'-X2') - (Z3'-Z2') × (X2'-X1') = 0

[0109] Substituting the above coordinate formulas, the rotation angle θ" around the X-axis can be calculated.

[0110] Example 3

[0111] This embodiment provides a method for measuring multi-dimensional dimensions of a complex workpiece using industrial CT, the steps comprising:

[0112] S1. Figure 1, based on a multi-dimensional platform, the scanning plane is preset with three-point spatial coordinates, the posture adjustment parameters are calculated, and CT scanning is performed on complex workpieces to obtain industrial two-dimensional CT slice images;

[0113] S2. Accurately vectorize industrial CT images based on error-compensated spatial moment algorithm, such as Figure 2 , and then extract features;

[0114] S21. Preprocessing of industrial CT images, including image enhancement, removal of image artifacts and noise;

[0115] S22. Extract the image edge, search the edge point set to construct the contour list sequence, perform probabilistic circle detection on the non-empty list, and accurately vectorize the circle that meets the full circle constraint conditions; then insert the circle list;

[0116] S23. Use the set intersection method to perform straight line fitting on other contour chain lists to determine whether the short straight line segments are adjacent. If they are adjacent, merge them into long straight line segments;

[0117] S24. Use the perpendicular bisector method to find the arc and determine whether it forms an arc; perform precise vectorization of the arc contour points and insert them into the arc linked list; calculate the least squares error of the non-arc contour points to perform precise vectorization of the straight line and insert them into the straight line linked list;

[0118] S3. Editing the vectorized graphics, including connecting similar line segments, deleting redundant line segments and isolated points, and saving the vectorized graphics as a DXF format file.

[0119] S4. Select the primitive features to match with the model, and calculate and analyze the error.

[0120] S41. Constructing a CAD design model based on the original workpiece data;

[0121] S42. Pair the CAD design model primitive information with the CT vectorized graphic primitives, introduce the centroid using the idea of ​​the minimum bounding box, and use human-computer interaction to select a set of primitive features to achieve alignment between models.

[0122] S42. Discretize the CT image vectorized primitives into 48 points;

[0123] S43. Calculate the normal error to the CAD model.

[0124] Example 4

[0125] This embodiment provides a method for measuring multi-dimensional dimensions of a complex workpiece using industrial CT, the steps comprising:

[0126] S1. Figure 1, based on a multi-dimensional platform, the scanning plane is preset with three-point spatial coordinates, the posture adjustment parameters are calculated, and CT scanning is performed on complex workpieces to obtain industrial two-dimensional CT slice images;

[0127] S2. Accurately vectorize industrial CT images based on error-compensated spatial moment algorithm, such as Figure 2 , and then extract features;

[0128] S21. Preprocessing of industrial CT images, including image enhancement, removal of image artifacts and noise;

[0129] S22. Extract the image edge, search the edge point set to construct the contour list sequence, perform probabilistic circle detection on the non-empty list, and accurately vectorize the circle that meets the full circle constraint conditions; then insert the circle list;

[0130] S23. Use the set intersection method to perform straight line fitting on other contour chain lists to determine whether the short straight line segments are adjacent. If they are adjacent, merge them into long straight line segments;

[0131] S24. Use the perpendicular bisector method to find the arc and determine whether it forms an arc; perform precise vectorization of the arc contour points and insert them into the arc linked list; calculate the least squares error of the non-arc contour points to perform precise vectorization of the straight line and insert them into the straight line linked list;

[0132] S3. Graphics editing processing for vectorization, such as Figure 3 , including connecting similar line segments, deleting redundant line segments and isolated points, and saving vector graphics as DXF format files.

[0133] S4. Figures 4-5 , select the primitive features to match with the model, such as Figures 4-5 , and the error is obtained by calculation and analysis.

[0134] S41. Constructing a CAD design model based on the original workpiece data;

[0135] S42. Pair the CAD design model element information with the CT vectorized graphic elements.

[0136] The centroid is introduced by adopting the idea of ​​minimum bounding box, and a set of primitive features are selected by human-computer interaction to realize the registration between models. In addition, the functions of fitting short straight lines to long straight lines and short straight lines to arcs are added as the basis for registration. Two line segments are defined as a long line segment and refitted into a long straight line, or two straight lines are defined as belonging to the same arc and refitted into a new arc.

[0137] S42. Discretize the CT image vectorized primitives into 48 points;

[0138] S43. Calculate the normal error to the CAD model.

[0139] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the embodiments here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A method for measuring the multi-dimensional size of a complex workpiece using industrial CT, characterized in that the steps include: S1. Based on the multi-dimensional platform, the scanning plane is preset with three-point spatial coordinates, the posture adjustment parameters are calculated, and the complex workpiece is CT scanned to obtain industrial two-dimensional CT slice images; S2. Accurately vectorize the industrial CT image based on the error compensation spatial moment algorithm and then extract features; S21. Preprocessing the industrial CT image; S22. Extract the image edge, search the edge point set to construct the contour list sequence, perform probabilistic circle detection on the non-empty list, and accurately vectorize the circle that meets the full circle constraint conditions; then insert the circle list; S23. Use the set intersection method to perform straight line fitting on other contour chain lists to determine whether the short straight line segments are adjacent. If they are adjacent, merge them into long straight line segments; S24. Use the perpendicular bisector method to find the arc and determine whether it forms an arc; perform precise vectorization of the contour points forming the arc and insert them into the arc linked list; Calculate the least squares error of non-arc contour points to accurately vectorize the straight line and insert it into the straight line list; S3. Edit the vectorized graphics and save them as DXF format files; S4. Match the graphic primitive features of CT vectorization with the CAD design model, and calculate and analyze the error.

2. The method for measuring complex workpieces by industrial CT multi-dimensional size according to claim 1, characterized in that: The coordinates of the three points M1, M2, and M3 on the scanning plane in step S1 are: M1(X1, Y1, Z1) M2(X2, Y2, Z2) M3(X3, Y3, Z3) The general equation is: Ax+By+Cz+D=0, where: A=(y2-y1)×(z3-z2)-(z2-z1)×(y3-y2) B = (z2-z1) × (x3-x2) - (z3-z2) × (x2-x1) C=(x2-x1)×(y3-y2)-(y2-y1)×(x3-x2) D=x1×((z2-z1)×(y3-y2)-(y2-y1)×(z3-z2))+y1×((z3-z2)×(x2-x1)-(z2-z1)×(x3-x2))+z1×((y2-y1)×(x3-x2)-(x2-x1)×(y3-y2)).

3. The method for measuring complex workpieces by industrial CT multi-dimensional size according to claim 1, characterized in that: The posture adjustment in step S1 includes rotating the detection surface around the Z axis to be parallel to the X axis and rotating the detection surface around the X axis to be parallel to the XY plane.

4. The method for measuring complex workpieces by industrial CT multi-dimensional size according to claim 3, characterized in that: When the detection surface rotates around the Z axis to be parallel to the X axis, the detection plane is rotated around the Z axis to be parallel to the X axis, and the angle is θ′. After the rotation, the coordinates of M1′, M2′, and M3′ are: M1′(X1′, Y1′, Z1) M2′(X2′, Y2′, Z2) M3′(X3′, Y3′, Z3) Where: According to the general plane equation: Ax+By+Cz+D=0, when the plane is parallel to the X-axis, A=0 A=(Y2'-Y1')×(Z3-Z2)-(Z2-Z1)×(Y3'-Y2')=0 Get the rotation angle θ' value around the X axis.

5. The method for measuring complex workpieces by industrial CT multi-dimensional size according to claim 3, characterized in that: The detection plane rotates around the X-axis to be parallel to the XY plane. Assume that when the detection plane rotates around the X-axis to be parallel to the XY plane, the angle is θ", and the coordinates of M1", M2", and M3" after the rotation are: M1″(X1′, Y1″, Z1′) M2″(X2′, Y2″, Z2′) M3″(X3′, Y3″, Z3′) Where: According to the general plane equation: Ax+By+Cz+D=0, when the plane is parallel to the XY plane, A=0, B=0 A=(Y2”-Y1”)×(Z3’-Z2’)-(Z2’-Z1’)×(Y3”-Y2”)=0 B = (Z2'-Z1') × (X3'-X2') - (Z3'-Z2') × (X2'-X1') = 0 Get the value of the rotation angle θ" around the X axis.

6. The method for measuring complex workpieces by industrial CT multi-dimensional size according to claim 1, characterized in that: The preprocessing in step S21 includes image enhancement and removal of image artifacts and noise.

7. The method for measuring complex workpieces by industrial CT multi-dimensional size according to claim 1, characterized in that: The editing process in step S3 includes connecting similar line segments and deleting redundant line segments and isolated points.

8. The method for measuring multi-dimensional size of complex workpieces by industrial CT according to claim 1, characterized in that: In step S4, the idea of ​​the minimum bounding box is used to introduce the centroid, and a group of primitive features are selected in a human-computer interactive manner to achieve registration between models.

9. The method for measuring complex workpieces by industrial CT multi-dimensional size according to claim 1, characterized in that: In step S4, the functions of fitting a short straight line to a long straight line and a short straight line to an arc are added as the basis for registration.

10. The method for measuring complex workpieces by industrial CT multi-dimensional size according to claim 1, characterized in that: Step S4 includes: S41. CAD design model element information of CT vectorized graphic element pairing; S42. discretizing the vectorized primitives of the CT image; S43. Calculate the normal error to the CAD model.

Images