A product internal flow channel profile extraction method based on industrial CT

Abstract

The application provides a product internal flow channel profile extraction method based on industrial CT. The method comprises: obtaining an industrial CT three-dimensional image of a product to be detected; slicing the industrial CT three-dimensional image to obtain a plurality of two-dimensional slices; obtaining a plurality of flow channel contours in the plurality of two-dimensional slices; splicing the plurality of flow channel contours to form a three-dimensional model; and extracting the flow channel profile based on the three-dimensional model. The method directly extracts the flow channel structure by using a segmentation technique in three-dimensional CT volume data, reconstructs the flow channel structure into a three-dimensional point cloud model, and thus intuitively and quickly analyzes parameters such as the wall thickness, size, shape and directionality of the flow channel. The method solves the problem that the existing industrial CT technology cannot directly evaluate the blockage, size and integrity of the flow channel through volume data.

Description

Technical Field

[0001] This application relates to the field of nondestructive testing technology, and in particular to a method for extracting the internal flow channel profile of a product based on industrial CT. Background Technology

[0002] Industrial CT (Computed Tomography) is a non-destructive testing technology that uses X-ray beams to penetrate the workpiece from multiple circumferentially distributed angles. Detectors collect and record the attenuated X-ray information after it passes through the workpiece, and a computer uses image reconstruction algorithms to display the workpiece's structure as a three-dimensional image. The direct result is information about the workpiece's internal and external three-dimensional structure, defects, etc., providing complete three-dimensional volumetric data. Because industrial CT offers numerous advantages such as intuitive, clear, and accurate results, non-destructive testing, no limitations on the workpiece's material or shape, direct acquisition of three-dimensional volumetric data, high longitudinal resolution, and high testing efficiency, it is one of the world's most advanced testing equipment and is widely used in additive manufacturing, composite materials, and other application fields.

[0003] When performing complex structural analysis using industrial CT, it is usually necessary to perform rendering analysis on different internal tissues, structures, and flow channel directions, analyze structural dimensions and flow channel profiles, and clarify information such as the location and geometric dimensions of the structure to provide data for product manufacturing compliance.

[0004] Existing technologies use CT slice images to observe the flow channel surface structure layer by layer, checking for blockages, channel size, and channel integrity, and indirectly analyzing the flow channel geometry. However, these technologies suffer from problems such as unintuitive detection results and long processing times. Summary of the Invention

[0005] This application provides a method for extracting the internal flow channel profile of a product based on industrial CT, to at least solve problem A in the related art. The technical solution of this application is as follows:

[0006] In a first aspect, embodiments of this application provide a method for extracting the internal flow channel profile of a product based on industrial CT, including:

[0007] Acquire industrial CT 3D images of the product to be inspected;

[0008] The industrial CT 3D image is sliced ​​to obtain multiple 2D slices;

[0009] Obtain multiple flow channel contours from the multiple two-dimensional slices;

[0010] The multiple flow channel outlines are pieced together to form a three-dimensional model;

[0011] Based on the three-dimensional model, the flow channel profile is extracted.

[0012] In some embodiments, slicing the industrial CT three-dimensional image includes:

[0013] Preprocess the industrial CT 3D image to determine the shape features of the product to be inspected in the industrial CT 3D image;

[0014] Based on the shape features, the cutting direction is determined;

[0015] Based on the cutting direction, the industrial CT three-dimensional image is sliced.

[0016] In some embodiments, obtaining the multiple flow channel contours in the plurality of two-dimensional slices includes:

[0017] Determine the analysis region from which the flow channel information of the multiple two-dimensional slices is to be extracted;

[0018] Based on image recognition algorithms, the first region where the flow channel is located is determined within the analysis region;

[0019] Based on the image search algorithm, the search parameters are adjusted to obtain the flow channel contours within the first region corresponding to each of the multiple two-dimensional slices, thereby obtaining multiple flow channel contours in the multiple two-dimensional slices.

[0020] In some implementations, determining the analysis region from which the flow channel information to be extracted from the plurality of two-dimensional slices includes:

[0021] Based on the three-view method, the analysis area for extracting flow channel information from the multiple two-dimensional slices is determined.

[0022] In some implementations, determining the first region where the flow channel is located within the analysis region based on the image recognition algorithm includes:

[0023] Based on the grayscale features of the image within the analysis area, the first region where the flow channel is located is determined.

[0024] In some implementations, the step of adjusting search parameters based on an image search algorithm to obtain flow channel contours within a first region corresponding to each of the plurality of two-dimensional slices, thereby obtaining plurality of flow channel contours in the plurality of two-dimensional slices, includes:

[0025] For the first two-dimensional slice among the plurality of two-dimensional slices, determine the first search parameter and obtain the flow channel profile;

[0026] A first slice group with a preset number of slices is determined from the plurality of two-dimensional slices, and the flow channel contour corresponding to each two-dimensional slice in the first slice group is obtained based on the first search parameters and the image search algorithm.

[0027] Adjust the first search parameters, determine a preset number of second slice groups from the remaining two-dimensional slices after removing the first slice group from the plurality of two-dimensional slices, and obtain the flow channel contour corresponding to each two-dimensional slice in the second slice group based on the adjusted first search parameters and image search algorithm; until multiple flow channel contours in the plurality of two-dimensional slices are obtained.

[0028] In some embodiments, after stitching together the multiple flow channel contours to form a three-dimensional model, the process further includes:

[0029] Determine whether the flow channel model conforms to the flow channel characteristics;

[0030] If the flow channel model does not conform to the flow channel characteristics, repeat the step of obtaining multiple flow channel contours in the multiple two-dimensional slices until the flow channel model conforms to the flow channel characteristics.

[0031] In some implementations, extracting the flow channel profile based on the three-dimensional model includes:

[0032] Remove the redundant parts from the three-dimensional model and extract the flow channel surface.

[0033] In some implementations, the search parameters include inner contour weights, outer contour weights, regularization terms, length terms, time step, δ(x) parameter, Gaussian kernel parameter, number of iterations, and variable parameter step.

[0034] The technical solution provided in this application has at least the following beneficial effects:

[0035] By employing segmentation techniques in 3D CT volumetric data, the flow channel structure is directly extracted and reconstructed into a 3D point cloud model, enabling intuitive and rapid analysis of parameters such as channel wall thickness, size, shape, and orientation. This solves the problem that current industrial CT technologies cannot directly evaluate channel blockage, size, and integrity using volumetric data.

[0036] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0037] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application, and do not constitute an undue limitation of this application.

[0038] Figure 1 This is a flowchart illustrating a method for extracting the internal flow channel profile of a product based on industrial CT, according to an exemplary embodiment.

[0039] Figure 2 This is a flowchart illustrating a method for extracting the internal flow channel profile of a product based on industrial CT, according to another exemplary embodiment.

[0040] Figure 3 This is a flowchart illustrating a method for extracting the internal flow channel profile of a product based on industrial CT, according to yet another exemplary embodiment.

[0041] Figure 4 This is a flowchart illustrating a method for extracting the internal flow channel profile of a product based on industrial CT, as shown in a specific example 1.

[0042] Figure 5 This is an industrial CT three-dimensional image of the part product of Example 1 of the present invention.

[0043] Figure 6 This is a schematic diagram of the shape features of the part product of Example 1 of the present invention.

[0044] Figure 7 This is the interface for setting the cutting direction in Example 1 of the present invention.

[0045] Figure 8 This is a schematic diagram of the defined analysis area of ​​the part product in Example 1 of the present invention.

[0046] Figure 9 This is the first area selection and setting interface of Example 1 of the present invention.

[0047] Figure 10 This is a schematic diagram of the first region of the part product of Example 1 of the present invention.

[0048] Figure 11 This is a schematic diagram of the search parameter settings in Example 1 of the present invention.

[0049] Figure 12 This is a schematic diagram of the flow channel profile obtained in Example 1 of the present invention.

[0050] Figure 13 This is a schematic diagram of a three-dimensional model of Example 1 of the present invention.

[0051] Figure 14 (a) and (b) are schematic diagrams of the flow channel profile of Example 1 of the present invention. Detailed Implementation

[0052] To enable those skilled in the art to better understand the technical solutions of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0053] It should be noted that the terms "first," "second," etc., used in this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0054] Figure 1 This is a flowchart illustrating a method for extracting the internal flow channel profile of a product based on industrial CT, according to an embodiment of this application. Figure 1 As shown, the method for extracting the internal flow channel profile of a product based on industrial CT may include the following steps.

[0055] Step S101: Obtain an industrial CT 3D image of the product to be inspected.

[0056] In this embodiment, CT volume data of the product under test is acquired through industrial CT inspection equipment. This CT volume data is an industrial CT three-dimensional image.

[0057] Step S102: Slice the industrial CT three-dimensional image to obtain multiple two-dimensional slices.

[0058] To analyze the internal structure of the product under test, it is necessary to slice the acquired industrial CT 3D image to obtain a 2D slice image, which facilitates the analysis of the internal structure of the product under test.

[0059] The industrial CT 3D image can be sliced ​​using the software built into the industrial CT inspection equipment to obtain multiple 2D slices.

[0060] Step S103: Obtain multiple flow channel contours from the multiple two-dimensional slices.

[0061] To extract the flow channel profile inside the product, it is necessary to identify the flow channel contours in multiple two-dimensional slice images.

[0062] Step S104: Assemble the multiple flow channel contours to form a three-dimensional model.

[0063] This can be understood as performing 3D reconstruction after obtaining multiple flow channel contours from multiple 2D slices. Alternatively, after identifying the flow channel contours from multiple 2D slices, the multiple flow channel contours can be stitched together according to the slice order of the original industrial CT 3D image to obtain the flow channel profile.

[0064] The 3D model here is a 3D point cloud model.

[0065] Step S105: Extract the flow channel profile based on the three-dimensional model.

[0066] Based on the obtained 3D model spliced ​​from the flow channel contour, the flow channel surface is extracted.

[0067] After extracting the flow channel profile, flow channel information can be directly extracted from the original CT body data, including parameters such as the flow channel wall thickness, size, shape, and orientation, so as to facilitate observation of the flow channel shape, measurement and analysis of the flow channel size characteristics, and detection of flow channel defects.

[0068] In practice, after confirming the 3D model, CT volume data can be loaded to generate an STL file.

[0069] This application's embodiment of the product internal flow channel shape extraction method based on industrial CT utilizes segmentation technology to directly extract the flow channel structure from the acquired industrial CT 3D image and reconstruct it into a 3D model, thereby enabling intuitive and rapid analysis of multiple flow channel parameters. In other words, by segmenting and reconstructing the region of interest using segmentation technology, specific information about the product's internal flow channels can be extracted without damaging the product under test. This facilitates manufacturing conformity checks on the product's internal flow channels, and the operation is simple, fast, and computationally inefficient. Based on existing industrial CT images, the flow channel shape can be reconstructed with high precision, clearly observing the flow channel shape and dimensional characteristics, and identifying the location and morphology of defects. Existing technologies can only measure flow channel dimensions layer by layer based on CT image content; therefore, this technology is of great significance for improving the accuracy and efficiency of product internal structure detection.

[0070] In some embodiments, the industrial CT 3D image is sliced, such as... Figure 2 As shown, it includes the following steps:

[0071] Step S201: Preprocess the industrial CT three-dimensional image to determine the shape features of the product to be detected in the industrial CT three-dimensional image.

[0072] This can be understood as follows: before slicing, the cutting direction needs to be determined. To determine the cutting direction, the overall shape characteristics of the product to be inspected need to be obtained first. Only by understanding the shape characteristics of the product to be inspected can the appropriate cutting direction be determined.

[0073] By preprocessing the industrial CT image to be inspected, the boundary area of ​​the product to be inspected can be located, and the shape features of the product to be inspected can be obtained so as to observe the shape features and determine the cutting direction.

[0074] Step S202: Determine the cutting direction based on the shape features.

[0075] Based on the shape characteristics of the product, find a suitable cutting direction (x, y, z) to ensure that the two-dimensional slice has a clear outline and that the internal and external features of the product are easy to distinguish.

[0076] Optionally, the industrial CT 3D image can be sliced ​​in 2D along a specific axis to ensure that the slices of the product have clear outlines and internal and external features.

[0077] Step S203: Based on the cutting direction, slice the industrial CT three-dimensional image.

[0078] In this embodiment, the shape features of the product to be inspected are first identified, and the cutting direction is determined based on the shape features. The product is then cut in a suitable cutting direction to obtain a two-dimensional slice, so as to ensure that the two-dimensional slice has a clear outline and internal and external features.

[0079] In some embodiments, multiple flow channel profiles are obtained from multiple two-dimensional slices, such as... Figure 3 As shown, it includes the following steps:

[0080] Step S301: Determine the analysis area for extracting flow channel information from the plurality of two-dimensional slices.

[0081] To reduce the computer load and improve modeling speed, a small and precise area is selected for slice analysis. That is, the product part from which flow channel information is to be extracted is selected.

[0082] As one possible implementation, the analysis region for extracting flow channel information from the multiple two-dimensional slices is determined based on the three-view method. That is, the region to be analyzed in the industrial CT three-dimensional image is divided using the three-view method.

[0083] Using the three-view method is intuitive and simple.

[0084] Step S302: Based on the image recognition algorithm, determine the first region where the flow channel is located within the analysis region.

[0085] As one possible implementation, the first region where the flow channel is located is determined based on the grayscale features of the image within the analysis region.

[0086] The initial flow channel contour is set using an image recognition algorithm, and the area where the flow channel is located is roughly selected.

[0087] In this embodiment, the flow channel location is determined by using the image grayscale information of the two-dimensional slice image. The two-dimensional slice image is preliminarily processed according to the grayscale features to divide the initial range for the flow channel contour search. This can greatly improve the success rate of flow channel contour search, improve the accuracy of flow channel contour recognition, and reduce the search time, thereby improving the efficiency of flow channel three-dimensional model establishment.

[0088] Step S303: Based on the image search algorithm, adjust the search parameters to obtain the flow channel contours within the first region corresponding to each of the multiple two-dimensional slices, so as to obtain multiple flow channel contours in the multiple two-dimensional slices.

[0089] It should be noted that when using an image search algorithm to obtain the flow channel contour in each of multiple 2D slices, not all 2D slices are subjected to the same search parameters. This is because the shape of the entire product is irregular, and the shape and position of the flow channels differ for each 2D slice. Therefore, the search parameters need to be adjusted for different 2D slices to obtain the flow channel contour more accurately.

[0090] As one possible implementation, obtaining multiple flow channel profiles from the multiple two-dimensional slices includes:

[0091] For the first two-dimensional slice among the plurality of two-dimensional slices, determine the first search parameter and obtain the flow channel profile;

[0092] A first slice group with a preset number of slices is determined from the plurality of two-dimensional slices, and the flow channel contour corresponding to each two-dimensional slice in the first slice group is obtained based on the first search parameters and the image search algorithm.

[0093] Adjust the first search parameters, determine a preset number of second slice groups from the remaining two-dimensional slices after removing the first slice group from the plurality of two-dimensional slices, and obtain the flow channel contour corresponding to each two-dimensional slice in the second slice group based on the adjusted first search parameters and image search algorithm; until multiple flow channel contours in the plurality of two-dimensional slices are obtained.

[0094] In other words, firstly, for a single 2D slice, an image search algorithm is used to adjust the search parameters and select a clear flow channel contour within the first region of that 2D slice. Then, a suitable number of 2D slices are extracted, and the current search parameters are used to perform contour searches on other 2D slices. Next, for the next 2D slice, the applicability of the current search parameters is confirmed. If it is not applicable, the search parameters are adjusted to confirm new search parameters suitable for the current 2D slice. Then, a suitable number of 2D slices are extracted, and the new search parameters are used to perform flow channel contour searches. This process continues until the flow channel contours in all 2D slices are confirmed. That is, based on the search parameters of the current 2D slice, other 2D slices are selected for contour searches, and the search parameters are repeatedly adjusted to confirm the stability of the flow channel contour search results. Furthermore, the 2D slice data extracted each time can be the same or different. By continuously confirming the applicability of the current search parameters, the accuracy of the flow channel contour segmentation is ensured.

[0095] It should be noted that the search parameters may include, but are not limited to, inner contour weights, outer contour weights, regularization terms, length terms, time step, δ(x) parameter, Gaussian kernel parameter, number of iterations, and variable parameter step.

[0096] In this embodiment, by analyzing the region determination, initial contour setting, and flow channel contour search steps, the selection of slice regions of industrial CT 3D images, the determination of flow channel location range, and the selection of flow channel contour search parameters are realized. This effectively reduces the amount of computation, improves the processing speed, and improves the accuracy of flow channel contour recognition, thereby improving the efficiency of flow channel 3D model establishment.

[0097] In some cases, such as when there are irregular features caused by image recognition errors, the obtained 3D model may have some deviation. In this case, it is necessary to judge the obtained 3D model. If the judgment result is that the current obtained 3D model is inaccurate, it is necessary to adjust the parameters of each step in obtaining the flow channel contour and re-obtain the flow channel contour. Therefore, in some embodiments, after stitching together the multiple flow channel contours to form a 3D model in step S104, the method further includes:

[0098] Determine whether the flow channel model conforms to the flow channel characteristics;

[0099] If the flow channel model does not conform to the flow channel characteristics, repeat the step of obtaining multiple flow channel contours in the multiple two-dimensional slices until the flow channel model conforms to the flow channel characteristics.

[0100] In this embodiment, the accuracy of the three-dimensional model is determined directly by observing whether the obtained three-dimensional model conforms to the characteristics of the flow channel.

[0101] By judging the accuracy of the obtained 3D model, we can ensure that the flow channel surface can be correctly extracted in the end.

[0102] Because in step S302, when determining the first region where the flow channel is located, the first region includes not only the area of ​​all flow channels but also a portion of the area outside the product. The portion outside the flow channel needs to be removed. Therefore, in step S105, based on the three-dimensional model, extracting the flow channel profile further includes: removing the redundant parts of the three-dimensional model to extract the flow channel profile.

[0103] In practice, the redundant parts of the 3D model in the STL file, except for the flow channel structure, are removed, and the flow channel model is retained, resulting in the final extracted flow channel profile.

[0104] The following example illustrates the method for extracting the internal flow channel profile of a product based on industrial CT, using a component with a flow channel structure as an example.

[0105] Figure 4This is a flowchart illustrating a method for extracting the internal flow channel profile of a product based on industrial CT, according to a specific embodiment of this application. Figure 4 As shown, the flow channel profile extraction method may include the following steps:

[0106] Step S401: Obtain an industrial CT 3D image of the part, such as... Figure 5 As shown.

[0107] Step S402: Preprocess the industrial CT 3D image to obtain the shape features of the part, such as... Figure 6 As shown.

[0108] Step S403: Based on the shape feature, select the transverse cutting method along the Z-axis to slice the industrial CT three-dimensional image and obtain multiple two-dimensional slices.

[0109] In specific implementation, such as Figure 7 Select Z-axis cross section in the interface shown.

[0110] Step S404: Based on the three-view method, determine the analysis area where the flow channel information to be extracted from the multiple two-dimensional slices. This analysis area is shown in... Figure 8 The region that 'a' points to.

[0111] Step S405: Based on the grayscale features of the image within the analysis area, determine the first region where the flow channel is located.

[0112] For example, if the desired flow channel profile is a black area within a 2D slice, then lower the upper limit of grayscale to around 47. Figure 9 The interface shown allows you to select the first region, which determines the first region where the flow channel is located. Figure 10 As shown.

[0113] It should be noted that, Figure 10 The first area shown includes the location of all flow channels. Similarly, the selected area also includes the exterior of the product, which requires further processing after modeling.

[0114] Step S406: For one of the multiple two-dimensional slices, select appropriate search parameters to obtain a suitable flow channel profile.

[0115] Adopting such Figure 11 The search parameters shown yield a suitable flow channel profile, as follows: Figure 12 As shown.

[0116] Step S407: Every preset number of two-dimensional slices, confirm the applicability of the current search parameters until multiple flow channel profiles corresponding to all two-dimensional slices are obtained.

[0117] As an example, the applicability of the current search parameters is confirmed every 10 two-dimensional slices.

[0118] Step S408: Assemble the multiple flow channel contours to form a three-dimensional model.

[0119] Step S409: Confirm the accuracy of the generated 3D model.

[0120] The generated 3D model, such as Figure 13 As shown, it includes the flow channel structure and some other structures of the product.

[0121] Step S410: Remove the redundant parts of the 3D model, retain the flow channel model, and extract the flow channel profile.

[0122] In practice, after removing the redundant parts of the 3D model in the STL file, the resulting flow channel model is as follows: Figure 14 As shown, Figure 14 (a) and (b) are schematic diagrams of the flow channel profile in two directions, respectively.

[0123] It should also be noted that the exemplary embodiments mentioned in this invention describe methods or systems based on a series of steps or apparatus. However, this invention is not limited to the order of the steps described above; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0124] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only.

[0125] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for extracting the internal flow channel profile of a product based on industrial CT, characterized in that, include: Acquire industrial CT 3D images of the product to be inspected; The industrial CT 3D image is sliced ​​to obtain multiple 2D slices; Obtaining multiple flow channel contours from the plurality of two-dimensional slices includes: determining an analysis region from which flow channel information is to be extracted from the plurality of two-dimensional slices; determining a first region where the flow channel is located within the analysis region based on an image recognition algorithm; and adjusting search parameters based on an image search algorithm to obtain flow channel contours within the first region corresponding to each of the plurality of two-dimensional slices, thereby obtaining multiple flow channel contours from the plurality of two-dimensional slices; wherein, adjusting search parameters based on an image search algorithm to obtain flow channel contours within the first region corresponding to each of the plurality of two-dimensional slices, thereby obtaining multiple flow channel contours from the plurality of two-dimensional slices, includes: determining a first search parameter for a first two-dimensional slice in the plurality of two-dimensional slices and obtaining the flow channel contour; determining a preset number of first slice groups from the plurality of two-dimensional slices, and obtaining the flow channel contour corresponding to each two-dimensional slice in the first slice group based on the first search parameter and the image search algorithm; adjusting the first search parameter, determining a preset number of second slice groups from the remaining two-dimensional slices after removing the first slice group from the plurality of two-dimensional slices, and obtaining the flow channel contour corresponding to each two-dimensional slice in the second slice group based on the adjusted first search parameter and the image search algorithm; until multiple flow channel contours from the plurality of two-dimensional slices are obtained; The multiple flow channel outlines are pieced together to form a three-dimensional model; Based on the three-dimensional model, the flow channel profile is extracted.

2. The method according to claim 1, characterized in that, Slicing the industrial CT 3D image includes: Preprocess the industrial CT 3D image to determine the shape features of the product to be inspected in the industrial CT 3D image; Based on the shape features, the cutting direction is determined; Based on the cutting direction, the industrial CT three-dimensional image is sliced.

3. The method according to claim 1, characterized in that, The analysis region for determining the flow channel information to be extracted from the plurality of two-dimensional slices includes: Based on the three-view method, the analysis area for extracting flow channel information from the multiple two-dimensional slices is determined.

4. The method according to claim 1, characterized in that, The method of determining the first region where the flow channel is located within the analysis region based on the image recognition algorithm includes: Based on the grayscale features of the image within the analysis area, the first region where the flow channel is located is determined.

5. The method according to claim 1, characterized in that, After stitching together the multiple flow channel contours to form a three-dimensional model, the process further includes: Determine whether the three-dimensional model conforms to the characteristics of the flow channel; If the three-dimensional model does not conform to the flow channel characteristics, repeat the step of obtaining multiple flow channel contours in the multiple two-dimensional slices until the flow channel model conforms to the flow channel characteristics.

6. The method according to claim 1, characterized in that, The step of extracting the flow channel profile based on the three-dimensional model includes: Remove the redundant parts from the three-dimensional model and extract the flow channel surface.

7. The method according to claim 1, characterized in that, The search parameters include inner contour weight, outer contour weight, regularization term system, length term system, time step, δ(x) parameter, Gaussian kernel parameter, number of iterations, and variable parameter step.

Images