Complex flow channel molded surface manufacturing conformity analysis and evaluation method based on industrial CT (Computed Tomography)

Abstract

The invention relates to an industrial CT (Computed Tomography)-based complex runner molded surface manufacturing conformity analysis and evaluation method, and belongs to the technical field of nondestructive testing. The method comprises the following steps: carrying out three-dimensional scanning on a to-be-measured runner profile to obtain three-dimensional volume data, and preprocessing the three-dimensional volume data; automatically segmenting the three-dimensional volume data, and forming a three-dimensional point cloud picture of the flow channel by adopting a three-dimensional stacking algorithm; noise points and interference points of a non-contour part in the three-dimensional point cloud picture of the flow channel are removed, and a three-dimensional contour image of the flow channel group is obtained; selecting a two-dimensional slice of a certain layer on the contour three-dimensional diagram to calculate the area of a runner group, and evaluating the position distribution uniformity; the wall thickness change and the wall surface irregularity of the runner are detected; selecting a certain morphological feature of the flow channel to carry out numerical calculation and flow channel on-off performance analysis; carrying out profile dynamic simulation and CAD registration; and for a runner fillet part with sub-pixels and rare pixels, converting the part in the CAD graph into a point cloud, carrying out registration on the point cloud and the extracted contour point cloud, and judging whether the point cloud of the scanned entity meets the design requirement or not according to the registration condition.

Description

Technical Field

[0001] The present invention belongs to the technical field of non-destructive testing, and relates to the evaluation and analysis of the morphology and structure of internal flow channels of workpieces. Specifically, it relates to a method for analyzing and evaluating the manufacturing compliance of complex flow channel profiles based on industrial CT. Background Art

[0002] As a key functional structure for transporting liquid cooling media and gaseous working media in aerospace power systems, the internal morphological characteristics and structural integrity of flow channels directly determine the thermal protection efficiency and aerodynamic performance of core components such as engine combustion chambers and turbine blades. In the high-pressure turbine guide vanes of aeroengines, millimeter-scale microchannels are responsible for transporting film cooling media at gas temperatures exceeding 1500°C; while the regenerative cooling flow channels in rocket engine thrust chambers need to withstand supercritical pressure conditions of the 300 MPa level. Such flow channels are generally formed by precision casting or additive manufacturing processes using nickel-based superalloys such as GH4169 and DD6. Their typical cross-sectional dimensions are of the order of 1 mm × 2 mm, with an aspect ratio of up to 10:1, and complex topological structures such as multi-chamber connectivity and spatial curvature changes are common.

[0003] Traditional flow channel detection mainly relies on industrial CT tomography and ultrasonic phased array technology. Although industrial CT can achieve three-dimensional reconstruction, it faces the problem of ray hardening artifacts caused by the high-density material of superalloys, and there are defects in the spatial resolution for sub-millimeter flow channels (typical resolution is about 50 μm). Ultrasonic testing is restricted by the probe size and near-surface blind zone, and it is difficult to accurately capture metallurgical defects at the corners of flow channels. More seriously, for turbine blades using directional crystal / single crystal casting processes, the grain boundary orientation has an anisotropic effect on the ultrasonic wave velocity, resulting in an increase in the error of defect quantitative analysis. Existing detection methods generally have a misjudgment rate of more than 20% in the verification of complex flow channel continuity, which has an unacceptable risk under the "zero defect" quality control system of aerospace power systems. Therefore, how to intuitively and accurately obtain the morphology, structure, and continuity of flow channels directly affects the detection and evaluation results. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a method for analyzing and evaluating the manufacturing compliance of complex flow channel profiles based on industrial CT, which combines industrial CT scanning technology, three-dimensional image processing technology, and data analysis technology to achieve an intuitive and accurate evaluation of the morphology, structure, and continuity of flow channels, timely discover and solve problems in the flow channel manufacturing process, thereby improving the quality and reliability of products.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for analyzing and evaluating the manufacturing compliance of complex flow channel profiles based on industrial CT, specifically including the following steps:

[0007] S1: Use an industrial CT scanner to perform three-dimensional scanning on the flow channel surface to be measured to obtain its three-dimensional volume data (i.e., three-dimensional CT image), and perform preprocessing such as noise removal and data filtering on the scanned three-dimensional volume data to ensure data quality and accuracy.

[0008] S2: Find the main direction of the preprocessed three-dimensional volume data, cut it at intervals of voxels perpendicular to the main direction to obtain all two-dimensional slice images of the entire volume data. Use a segmentation algorithm to segment the flow channel contour from all two-dimensional slice images and stack them into a three-dimensional point cloud map of the flow channel.

[0009] S3: Remove the noise points and interference points in the non-contour part of the three-dimensional point cloud map of the flow channel after segmentation to obtain a three-dimensional contour image of the flow channel group.

[0010] S4: Select a two-dimensional slice of a certain layer on the three-dimensional contour image of the flow channel group processed in step S3, and calculate the size of the flow channel group, including length, width, and area.

[0011] S5: Fit the center points of each small hole in the entire flow channel cross-section, perform an overall uniformity distribution evaluation analysis, and detect the change in the flow channel wall thickness and the irregularity of the flow channel wall surface.

[0012] S6: Select a certain morphological feature of the flow channel for numerical calculation and flow channel on-off analysis.

[0013] S7: Dynamic simulation of the flow channel surface and CAD registration.

[0014] S8: For the fillet part of the flow channel with sub-pixels and few pixels, convert this part in the CAD drawing into a point cloud and register it with the extracted contour point cloud, and judge whether the point cloud of the scanned entity meets the design requirements according to the registration situation.

[0015] Furthermore, step S2 specifically includes: using a variable parameter iterative RSF image segmentation (Region-Scalable Fitting Model with Variable Parameters, VP-RSF) model or other contour segmentation methods to perform contour segmentation on each slice image to obtain a segmented contour map (such as Figure 3 ), and using contour tracing subtraction operation to process all two-dimensional contour maps to remove the inner and outer contours to obtain a flow channel cross-section contour map that only retains the flow channel contour (such as Figure 4 ). Extract point clouds from the flow channel cross-section contour map to obtain flow channel cross-section contour point clouds, and then use algorithms such as three-dimensional stacking to perform three-dimensional stacking on all two-dimensional processed flow channel cross-section contour point clouds to obtain a three-dimensional point cloud map of the internal flow channel surface (such as Figure 5 ), which can accurately reflect the geometric shape of the flow channel surface.

[0016] Furthermore, as Figure 8 shown, step S3 specifically includes the following steps:

[0017] S31: Use a point cloud denoising method based on deep learning for denoising. Specifically, use a convolutional neural network (CNN) model to denoise the segmented three-dimensional point cloud map of the flow channel, thereby greatly reducing the interference of noise points and enhancing the accuracy of the data;

[0018] S32: Use a multi-dimensional deviation calculation method to remove interference, including but not limited to: comparing with the geometric shape of the design model, and performing deviation evaluation based on the channel resistance model of the flow channel structure, etc., to further improve the comprehensiveness and accuracy of the compliance evaluation.

[0019] Furthermore, step S4 specifically includes: accurately locating the center point of each flow channel hole on a certain layer of slice to obtain the center point coordinates xyz; among them, the center point positioning is to perform OBB on each small hole to find the center point;

[0020] OBB is an axis-aligned bounding box relative to the object (as Figure 6 shown), and implementing OBB usually involves the following steps:

[0021] 1) Calculate the convex hull;

[0022] 2) Use principal component analysis (PCA) to find the best rotation direction;

[0023] 3) Determine the boundaries of the bounding box according to these directions.

[0024] Furthermore, step S5 specifically includes the following steps:

[0025] S51: Fit a circle based on the center points of all flow channel holes on this layer to determine the position of the center of the circle, number the center points, calculate the distance from the center point of each small hole to the center of the circle respectively, and compare it with the radius of the circle. According to the situation where the measured center points are inside and outside the fitted circle, judge whether the flow channels are evenly distributed, perform uniformity evaluation, and judge whether the position of the center point meets the standard.

[0026] S52: Connect the center point of each small hole with the center of the circle, calculate the angle between the straight lines formed by the center points of two adjacent small holes and the center of the circle, traverse and calculate the angles between all small holes, and perform deviation analysis according to the angle change situation to judge whether the small holes are evenly distributed inside the workpiece.

[0027] Furthermore, as Figure 7 shown, step S6 specifically includes the following steps:

[0028] S61: Fit the shape of a single flow channel on a two-dimensional slice, and measure the length, width or diameter of the flow channel surface; for the case where the shape of a single flow channel is irregular, first locate the center point, draw an arbitrary straight line through the center point to intersect with the edge points of the flow channel, calculate the distance between the two intersection points on each straight line, find out the straight line where the two intersection points with the shortest distance are located, which is the straight line where the short axis is located, the distance between the two intersection points is the short side length, and the line segment perpendicular to this straight line and intersecting with the small hole is the long side, so that the length and width of the small hole can be measured;

[0029] S62: Extract the point cloud map of a single flow channel in three-dimensional space, and measure the flow direction angle of the flow channel group in three-dimensional space. Specifically, select a certain point on the flow channel surface, measure the curvature and normal direction of this point, obtain the curvature information of different points along the flow direction for each flow channel, conduct multi-point evaluation and analysis, and calculate the angle deviation in the flow channel;

[0030] S63: According to the obtained three-dimensional flow channel contour map, perform slice segmentation to obtain the two-dimensional contour map of each flow channel, measure the area enclosed by each flow channel contour, and automatically calculate the deviation for comparative evaluation and analysis;

[0031] S64: Accurately identify the chamfer part of the flow channel, and measure its exact radian and length; for the problem that there are few pixels in the chamfer part and it is difficult to identify, use the sub-pixel edge recognition method for positioning and analysis, and perform multiple curve fittings to obtain more accurate image information;

[0032] S65: Select a certain section in three-dimensional space and measure the angle formed between adjacent flow channels on this section.

[0033] Further, as Figure 9 shown, step S7 specifically includes the following steps:

[0034] S71: Through the obtained CAD model, convert the CAD into a point cloud model, where the CAD image information is read and the CAD images of the chamfer and each surface of the flow channel are separately extracted and converted into point cloud data. The local point cloud map after converting the standard CAD image is registered with the segmented point cloud using technologies such as ICP, and the overall manufacturing compliance and deviation of the flow channel are compared and analyzed; among them, the Iterative Closest Point (ICP) algorithm is a point cloud registration algorithm, belonging to fine registration.

[0035] S72: On the basis of comparing the point cloud model and the CAD model, evaluate the manufacturing accuracy of the flow channel by calculating the deviation (such as the maximum deviation, root mean square error, etc.), and further optimize the manufacturing process and design parameters.

[0036] The beneficial effects of the present invention are as follows: The method of the present invention combines industrial CT scanning technology, three-dimensional image processing technology, and data analysis technology, and can achieve intuitive and accurate evaluation of the morphology, structure, and on-off status of the flow channel. Through the application of the method of the present invention, problems in the manufacturing process of the flow channel can be discovered and solved in a timely manner, improving the quality and reliability of the product. At the same time, the method of the present invention can also provide strong support for the formulation of quality control and improvement suggestions.

[0037] Other advantages, objectives, and features of the present invention will be described to some extent in the subsequent specification, and to some extent, will be obvious to those skilled in the art based on the study of the following text, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the following specification. Brief Description of the Drawings

[0038] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be described in detail preferably in conjunction with the accompanying drawings, where:

[0039] Figure 1 is a flowchart of the method for analyzing and evaluating the compliance of the complex flow channel profile manufacturing based on industrial CT of the present invention;

[0040] Figure 2 is a three-dimensional scan diagram of the flow channel profile;

[0041] Figure 3 is a sectional view; where, (a) is a two-dimensional sectional view along the axial direction, and (b) is a contour diagram after the section is segmented;

[0042] Figure 4 is a sectional flow channel contour diagram after edge tracking subtraction operation;

[0043] Figure 5 is a three-dimensional point cloud diagram;

[0044] Figure 6 is a flowchart of the automatic measurement method for the geometric parameters of the flow channel based on OBB;

[0045] Figure 7 is a schematic diagram of the analysis process of the uniformity of the flow channel hole distribution;

[0046] Figure 8 is a flowchart of the three-dimensional flow channel extraction;

[0047] Figure 9 is a schematic diagram of the flow channel point cloud registration process. Detailed Embodiments

[0048] The following specific examples illustrate the implementation manners of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the drawings provided in the following embodiments only schematically illustrate the basic concept of the present invention. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0049] Among them, the drawings are only for illustrative purposes, showing only schematic diagrams rather than actual diagrams, and should not be construed as a limitation to the present invention; in order to better illustrate the embodiments of the present invention, some components in the drawings will be omitted, enlarged or reduced, which does not represent the size of the actual product; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0050] In the drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc. indicating the orientation or positional relationship, they are based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms describing the positional relationship in the drawings are only for illustrative purposes and should not be construed as a limitation to the present invention. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0051] Please refer to Figures 1 to 9, an embodiment of the present invention provides a method for manufacturing compliance analysis and evaluation of complex flow channel profiles based on industrial CT, specifically for manufacturing compliance evaluation of the cooling flow channels in a certain aero-engine. First, use an industrial CT scanning device to scan the engine component and reconstruct a three-dimensional CT image. Then, use methods such as querying contours to segment the three-dimensional CT image and extract the contour map of the cooling flow channel. Next, perform denoising processing on the segmented three-dimensional contour image to improve the accuracy of subsequent analysis. Select a two-dimensional slice of a certain layer, accurately locate the center points of the flow channel holes, and measure the area of a single flow channel and the shape of a single flow channel (length and width or diameter, R chamfer, inner and outer wall thicknesses) on any two-dimensional section. Fit a circle based on the center points of all flow channels in this layer to determine whether the flow channels are evenly distributed. Fit the shape of a single flow channel and measure geometric parameters such as length and width or diameter. Finally, perform slice segmentation processing on the obtained three-dimensional flow channel contour map, measure the areas enclosed by each flow channel contour, and automatically calculate the deviation for comparative evaluation and analysis. At the same time, accurately identify and measure the chamfer part of the flow channel, and measure the flow direction angle and curvature information of the flow channel group in three-dimensional space. By comparing the differences between the actual flow channel shape and the designed shape, evaluate the manufacturing compliance of the cooling flow channel and put forward corresponding quality control and improvement suggestions.

[0052] As a preferred embodiment, for a curved flow channel, calculate the curvature of the flow direction of the flow channel according to the degree of curvature. Through the selection and curvature measurement of different points on the inner wall of the flow channel, compare with the standard value for analysis and give the compliance analysis result.

[0053] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the purpose and scope of the present technical solution, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A method for analyzing and evaluating the manufacturing conformity of complex flow channel profiles based on industrial CT, characterized in that: The method specifically comprises the following steps: S1: Use an industrial CT scanner to perform three-dimensional scanning on the flow channel surface to obtain its three-dimensional volume data, and perform noise removal and data filtering preprocessing to ensure data quality and accuracy; S2: Find the main direction of the preprocessed 3D volume data, cut it perpendicular to the main direction and at intervals of voxels to obtain all 2D slice images of the entire volume data; segment the flow channel contours using a segmentation algorithm for all 2D slice images, and stack them into a 3D point cloud image of the flow channel; S3: removing noise points and interference points in the non-contour part of the segmented three-dimensional point cloud image of the flow channel to obtain a three-dimensional contour image of the flow channel group; S4: selecting a two-dimensional slice of a certain layer on the three-dimensional contour image of the flow channel group processed in step S3, and calculating the size of the flow channel group, including length, width and area; S5: Fit the center point of each small hole in the entire flow channel section, conduct overall uniformity distribution evaluation and analysis, and detect the change of flow channel wall thickness and irregularity of the flow channel wall; S6: Select a certain morphological feature of the flow channel for numerical calculation and flow channel continuity analysis; S7: Dynamic simulation of flow channel profile and CAD registration; S8: For the sub-pixel and sparsely pixelated fillet parts of the flow channel, convert the part in the CAD drawing into a point cloud and align it with the extracted contour point cloud. According to the alignment, determine whether the point cloud of the scanned entity meets the design requirements.

2. The method for analyzing and evaluating the manufacturing conformity of complex flow channel profiles based on industrial CT according to claim 1 is characterized in that: Step S2 specifically includes: using the VP-RSF model or other contour segmentation methods to perform contour segmentation on each slice image to obtain a segmented contour map, and using contour tracking subtraction operations to process all two-dimensional contour maps to remove internal and external contours to obtain a flow channel cross-sectional contour map that only retains the flow channel contour; performing point cloud extraction on the flow channel cross-sectional contour map to obtain a flow channel cross-sectional contour point cloud, and then using a three-dimensional stacking algorithm to perform three-dimensional stacking on all two-dimensionally processed flow channel cross-sectional contour point clouds to obtain a flow channel three-dimensional point cloud map of the internal flow channel surface; wherein VP-RSF represents variable parameter iterative RSF image segmentation.

3. The method for analyzing and evaluating the manufacturing conformity of complex flow channel profiles based on industrial CT according to claim 1 is characterized in that: Step S3 specifically includes the following steps: S31: using a deep learning-based point cloud denoising method to perform denoising, specifically using a convolutional neural network model to denoise the segmented flow channel 3D point cloud image; S32: Use multi-dimensional deviation calculation method to remove interference, including: geometric shape comparison with the design model, and deviation evaluation based on the channel resistance model of the flow channel structure.

4. The method for analyzing and evaluating manufacturing conformity of complex flow channel profiles based on industrial CT according to claim 1, characterized in that: Step S4 specifically includes: accurately locating the center point of each flow channel hole on a certain layer of slices to obtain the center point coordinates xyz; wherein, the center point positioning is to find the center point of each small hole by OBB, wherein OBB is a bounding box aligned relative to the object direction.

5. The method for analyzing and evaluating manufacturing conformity of complex flow channel profiles based on industrial CT according to claim 1, characterized in that: Step S5 specifically includes the following steps: S51: fitting a circle based on the center points of all the flow channel holes in the layer, determining the position of the circle center, numbering the center points, respectively calculating the distance from the center point of each small hole to the circle center, and comparing it with the circle radius, judging whether the flow channel is evenly distributed according to the distribution of the measured center points inside and outside the fitting circle, performing uniformity evaluation, and judging whether the center point position meets the standard; S52: Connect the center point of each small hole with the center of the circle, calculate the angle between the straight lines formed by the center points of two adjacent small holes and the center of the circle, traverse and calculate the angles between all small holes, perform deviation analysis based on the angle changes, and determine whether the small holes are evenly distributed in the workpiece.

6. The method for analyzing and evaluating manufacturing conformity of complex flow channel profiles based on industrial CT according to claim 1, characterized in that: Step S6 specifically includes the following steps: S61: Fitting the shape of a single flow channel on a two-dimensional slice, measuring the length, width or diameter of the flow channel surface; for the case where the shape of a single flow channel is irregular, first locate the center point, make an arbitrary straight line through the center point and intersect the edge point of the flow channel, calculate the distance between the two intersection points on each straight line, find the straight line where the two intersection points with the shortest distance are located, which is the straight line where the minor axis is located, and the distance between the two intersection points is the short side length, and the line segment perpendicular to the straight line and intersecting with the small hole is the long side, that is, the length and width of the small hole can be measured; S62: extracting a point cloud image of a single flow channel in the three-dimensional space, measuring the flow direction angle of the flow channel group in the three-dimensional space, specifically selecting a point on the flow channel surface, measuring the curvature and normal direction of the point, obtaining curvature information of different points along the flow direction of each flow channel, performing multi-point evaluation and analysis, and calculating the angle deviation in the flow channel; S63: Slice and segment the obtained three-dimensional flow channel profile to obtain a two-dimensional flow channel profile, measure the area enclosed by each flow channel profile, and automatically calculate the deviation for comparative evaluation and analysis; S64: Accurately identify the chamfered part of the flow channel and measure its precise curvature and length. In view of the problem that the chamfered part has few pixels and is difficult to identify, a sub-pixel edge recognition method is used for positioning analysis, and multiple curve fitting is performed to obtain accurate image information; S65: Select a certain section in three-dimensional space and measure the angle between adjacent flow channels on the section.

7. The method for analyzing and evaluating manufacturing conformity of complex flow channel profiles based on industrial CT according to claim 1, characterized in that: Step S7 specifically includes the following steps: S71: converting the CAD model obtained into a point cloud model, wherein the CAD image information is read and the CAD images extracted from the chamfer and each surface of the flow channel are converted into point cloud data, and the local point cloud image converted from the standard CAD image is registered with the segmented point cloud using the ICP technology, and the overall manufacturing compliance and deviation of the flow channel are compared and analyzed; wherein ICP means iterative closest point; S72: Based on the comparison between the point cloud model and the CAD model, the manufacturing accuracy of the flow channel is evaluated by calculating the deviation, and the manufacturing process and design parameters are further optimized.

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