Method for improving cohesiveness between soft core support and ceramic core layer prepared through conformal printing

Abstract

The invention discloses a method for improving cohesiveness between a soft core support and a ceramic core layer prepared through conformal printing, and belongs to the field of additive manufacturing. The method comprises the steps of obtaining the actual posture of a ceramic core, accurately matching the position of the ceramic core, adjusting the positions of the ceramic core and a soft core support, planning a printing track and determining an optimal printing gap. The actual space pose point cloud set of the ceramic core is obtained through point laser measurement, and compared with traditional three-coordinate and blue light measurement methods and the like, repeated clamping errors and clamp errors are reduced; and meanwhile, measured data can be directly used for milling, so that the milling quality can be improved. And through operation of the method, the cohesiveness of the soft core support and the ceramic core can be improved without heating the ceramic core, the clamping error and the like can be reduced, and the whole preparation process is more convenient and efficient.

Description

Technical Field

[0001] This invention belongs to the field of additive manufacturing, specifically relating to a method for improving the adhesion between soft core support and ceramic core layer prepared by conformal printing. Background Technology

[0002] In the precision casting process of hollow turbine blades, variable-thickness soft core supports are fabricated at different locations on the surface of the ceramic core. The ceramic core and soft core supports are then placed in a mold. The spatial relationship of the ceramic core is adjusted by the contact between the soft core supports of different thicknesses and the mold surface, thereby controlling the turbine blade wall thickness. The fabrication of soft core supports typically employs a combined process of conformal printing and milling: first, a soft core support blank of uniform thickness is generated on the surface of the ceramic core through conformal printing; then, variable thickness design is achieved through milling. (Milling removes excess material to achieve variable thickness soft core supports at different locations). However, this process faces two major bottlenecks: 1. Insufficient adhesion: During milling, the cutting force can easily cause the soft core support to detach from the ceramic core surface. Traditional solutions (such as attaching heating pads to the ceramic core surface or heating with a hot air gun) are difficult to apply due to the complexity of the ceramic core structure and the special characteristics of conformal printing. There is an urgent need to develop a high-adhesion preparation method under heating conditions.

[0003] 2. Positional errors lead to uncontrolled gaps: Manufacturing errors in the ceramic core cause deviations between its actual position and the theoretical model, making it difficult to precisely control the gap between the printhead and the ceramic core surface. Although existing composite processing platforms integrate point laser detection, it is only used for dimensional calibration and does not address the impact of positional deviations on gaps; while conformal printing path planning methods optimize focusing efficiency but do not address improving adhesion.

[0004] Based on this, the adhesion of printing gap control is proposed, that is, controlling the distance between the raw material extrusion plane of the printing nozzle and the surface of the ceramic core. However, the ceramic core has manufacturing errors, which cause a deviation between the actual spatial pose of the ceramic core during the printing process and the theoretical spatial pose in the path planning software, resulting in inaccurate positioning and difficulty in achieving the set parameters for the printing gap.

[0005] Therefore, there is an urgent need for a method that can compensate for the ceramic core's orientation error and precisely control the printing gap in order to solve the adhesion defects of the non-heating process. Summary of the Invention

[0006] The technical problem to be solved: To overcome the shortcomings of existing technologies, this invention provides a method for improving the adhesion between soft core supports and ceramic core layers in conformal printing. The method involves the following steps: obtaining the actual "posture" of the ceramic core, precisely matching the position of the ceramic core, adjusting the positions of the ceramic core and the soft core support, planning the printing trajectory, and determining the optimal printing gap. This method improves the adhesion between the soft core support and the ceramic core without requiring heating of the ceramic core, and also reduces clamping errors, making the entire fabrication process more convenient and efficient.

[0007] The technical solution of this invention is: a method for improving the adhesion between soft core support and ceramic core layer prepared by conformal printing, comprising the following steps: Step 1: Obtain the actual spatial pose point cloud of the ceramic core through point laser measurement: The laser is positioned at a constant distance from the ceramic core surface in the theoretical model to generate the sampling trajectory. A point laser is used to strike the surface of the ceramic core to calculate the actual distance from the point to the surface, thus obtaining the actual spatial pose data of the ceramic core. Import the collected point cloud data into the model design software to generate a set of actual spatial pose points for the ceramic core. Step 2: Register the ceramic core pose using the weighted ICP algorithm on the obtained actual spatial pose point cloud of the ceramic core: Set the weights for the leading edge, trailing edge, leaf base, and leaf underside; Weighted ICP calculations were performed on the actual spatial pose point cloud of the ceramic core and the point cloud of the theoretical ceramic core model to solve for the rotation matrix R and the translation matrix T. The covariance matrix is ​​calculated by using SVD decomposition. The iteration continues until the average surface deviation is less than the set deviation threshold or the set number of iterations is reached, thus obtaining the average deviation that satisfies the minimum Euclidean distance. Step 3: Correct the spatial pose of the ceramic core and the soft core support according to the rotation matrix R and the translation matrix T; Step 4: Generate the soft core support printing trajectory: The data for the slicing were based on the contact surface between the bottom surface of the soft core support and the curved surface of the ceramic core. Set the print gap height, and generate the first layer of slice data by offsetting the print gap height along the surface normal direction; The soft core support blank slice data is generated by continuously offsetting the layer height, and the printing trajectory is generated by combining the filling algorithm. Step 5: Perform conformal printing based on the printing trajectory to obtain a soft core support; and control the printing gap height by using the target adhesive force.

[0008] A further technical solution of the present invention is: the data processing in step one includes: Calculate the actual Z-axis height Z from the probe of the point laser measurement to the surface of the ceramic core. 测 With theoretical height Z 理 The deviation ΔZ, ΔZ=Z 理 -Z 测 ; Based on the deviation ΔZ and the Z-axis coordinate value Z in the point laser measurement CNC program code, the Z1 value of the actual measuring point in the point laser detection coordinate system is calculated by Z1=Z+ΔZ. The coordinates {X,Y,Z1} in the point laser detection coordinate system are obtained by splicing the XY values ​​in the CNC program code. The coordinates {X,Y,Z1} in the point laser detection coordinate system are converted into the actual coordinates {x,y,z1} in the planned measurement coordinate system through inverse post-processing, as shown in the following expression:

[0009] Where B represents the angle between the printing device and the center of rotation of its turntable.

[0010] A further technical solution of the present invention is that the constant distance is a preset fixed distance between the point laser and the surface of the ceramic core in the theoretical model, and the sampling trajectory covers all areas of the ceramic core to be printed soft core support.

[0011] A further technical solution of the present invention is: the weighted ICP algorithm specifically includes: Define Q, the actual spatial pose point cloud set of the ceramic core, as the target point cloud, and theoretically design P, the nearest projection point set corresponding to the ceramic core surface, as the initial point cloud. The objective function D is minimized through iterative calculation, as shown in the following expression:

[0012] In the formula, D represents the average deviation of the Euclidean distance of the overall point cloud, R represents the rotation matrix, and S represents the translation matrix. n Indicates the total number of iterations. , , i Indicates the index of the point cloud's focal point; Indicates the first i The weight of each point.

[0013] A further technical solution of the present invention is: the iterative calculation includes: Set the initial rotation matrix R k=0 For an identity matrix, the translation matrix S k=0 It is a zero vector; Calculate the coordinates of the projection points of the ceramic core spatial transformation And determine its nearest projection point on the theoretically designed ceramic core surface. ;in, k Indicates the number of iterations. N This represents the total number of points in the point cloud set; The initial point cloud P and the target point cloud Q are mean-centered to obtain the centered point cloud:

[0014]

[0015] Subtract the mean of each point in the initial point cloud P and the target point cloud Q to obtain the decentralized points:

[0016]

[0017] After decentralizing each point in the initial point cloud P and the target point cloud Q, two new point cloud datasets are obtained. and ,calculate and The covariance matrix H:

[0018] SVD decomposition of the covariance matrix H yields Where U and V are orthogonal matrices, and Λ is a diagonal matrix; Calculate the rotation matrix R and the translation matrix T:

[0019]

[0020] Calculate the point cloud of the ceramic core to be registered and projection point set Average surface deviation with weight constraints between :

[0021] In the formula, This represents the average profile deviation between the actual tested ceramic core profile and the theoretical model, constrained by the wall thickness tolerance. Or, if the set number of iterations is met, the loop exits. The preset iteration deviation threshold is used; otherwise, the next iteration will start from step two.

[0022] A further technical solution of the present invention is: the weight Set a weight allocation strategy that satisfies the wall thickness tolerance constraint, as shown in the following expression:

[0023] In the formula, The cloud wall thickness at various points on the blade cross-section. for The minimum value in; K The ratio of wall thickness tolerance in different regions of the leaf blade is given. A ratio relationship is established based on the wall thickness tolerance of different parts, with the ratios of wall thickness tolerance at the leading and trailing edges to that at the leaf blade being denoted as follows:

[0024] In the formula, For the tolerance of the leading edge wall thickness; The tolerance for leaf wall thickness.

[0025] A further technical solution of the present invention is: the printing gap height in step five is 0.05–0.25 mm, the adhesion force is ≥4.72 N, and it can resist the milling cutting force of 3.17 N.

[0026] A further technical solution of the present invention is: the printing parameters in step five include: temperature 70℃, air pressure 0.016MPa, layer height 0.4mm; printing speed 1000mm / min, and filling algorithm is "zigzag".

[0027] A further technical solution of the present invention is: adhesion verification includes: When the printing gap is <0.05mm or >0.25mm, the adhesion force is >3.17N, which cannot resist milling force; The soft core support portion of the unregistered trajectory printing detached, but did not detach after registration.

[0028] A system for improving the adhesion between soft core supports and ceramic core layers in conformal printing includes: The point laser measurement module is used to acquire the actual spatial pose point set of the ceramic core; The weighted ICP registration module is communicatively connected to the point laser measurement module and is used to perform weighted ICP calculations on the actual spatial pose point cloud of the ceramic core and the theoretical point cloud of the ceramic core model. The trajectory generation module is communicatively connected to the weighted ICP registration module and is used to generate multi-layer printing trajectories; The conformal printing execution module, including the printhead and motion control system, performs conformal printing on the ceramic core surface according to the printing trajectory; it dynamically maintains the printing gap height to ensure that the adhesion meets the requirements; An integrated control unit coordinates the operation of each module and monitors the printing gap accuracy in real time.

[0029] Beneficial effects The beneficial effects of this invention are as follows: This invention obtains the actual spatial pose point set of the ceramic core through point laser measurement, which reduces repeated clamping errors and fixture errors compared with traditional three-coordinate and blue light measurement methods; at the same time, the measurement data can be directly used for milling, which helps to improve the milling quality.

[0030] This invention uses a weighted ICP algorithm to register the ceramic core pose, accurately compensating for ceramic core manufacturing errors (especially in the high-curvature leading and trailing edge regions). Combined with optimal printing gap control (0.05–0.25 mm), the adhesion between the soft core support and the ceramic core layer is ≥4.72 N, which can effectively resist the milling cutting force of 3.17 N, preventing the soft core support from falling off during milling and solving the problem of insufficient adhesion in traditional non-heating processes.

[0031] This invention abandons the traditional method of improving adhesion by heating with heating pads or hot air guns. High adhesion can be achieved simply by controlling the printing gap, without the need for additional heating steps. This simplifies the soft core support preparation process, making the process more convenient and faster, and improving printing efficiency and overall preparation reliability.

[0032] This invention solves the problem of uncontrolled printing gap caused by ceramic core posture deviation by correcting the spatial orientation of the ceramic core and the soft core support and planning a suitable printing trajectory. It ensures that the printing gap meets the set parameters and guarantees the molding quality of the soft core support and its matching degree with the ceramic core. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of a method for improving the adhesion between a soft core support and a ceramic core prepared by conformal printing, as described in an embodiment of the present invention. Figure 2 This is a schematic diagram of point laser sampling on the surface of a ceramic core in an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the process of importing the collected data points into UG using a point laser in an embodiment of the present invention. Figure 4 This is a schematic diagram of the parameters set in the weighted ICP registration in an embodiment of the present invention; Figure 5 This is a schematic diagram of the rotation matrix R and translation matrix T obtained after registration in an embodiment of the present invention; Figure 6 The registered point cloud and the registered point cloud after registration are completed in the embodiments of the present invention. Figure 2 Import point cloud diagram into the database; Figure 7 This is a schematic diagram of the spatial pose of the ceramic core and the soft core support after correction based on the registration results in an embodiment of the present invention; Figure 8 This is a schematic diagram illustrating the setting of the printing gap height in an embodiment of the present invention; Figure 9 This refers to the soft core support printing trajectory generated in the embodiments of the present invention; Figure 10 This is a schematic diagram of the printing of the soft core support during the experimental process in an embodiment of the present invention; Figure 11 This is a schematic diagram of the milling of the soft core support blank in an embodiment of the present invention. Detailed Implementation

[0034] The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the invention, and should not be construed as limiting the invention.

[0035] Existing technologies suffer from manufacturing errors in ceramic cores, leading to discrepancies between the actual spatial pose of the ceramic core during printing and the theoretical spatial pose in the path planning software. This results in inaccurate positioning and difficulty in achieving the set printing gap parameters. This invention utilizes point laser measurement integrated into the experimental equipment platform to obtain the actual spatial pose of the ceramic core. Compared to traditional methods using coordinate measuring machines (CMMs) or blue light, this reduces repeated clamping errors and fixture errors. Furthermore, the generated data can be used in milling processes to improve milling quality. The specific technical solution is as follows: In one embodiment, refer to Figure 1 As shown, a method for improving the adhesion between a soft core support and a ceramic core in conformal printing is proposed. This method primarily improves the adhesion between the soft core support blank and the ceramic core surface; secondly, it improves the positioning accuracy of the soft core support and the control of the printing gap. The method for improving the adhesion of the soft core support used in this embodiment includes the following steps: Step 1: First, a sampling trajectory is generated by setting a constant distance between the point laser and the ceramic core surface in the theoretical model. Second, the actual distance from the point to the surface is calculated by hitting the ceramic core surface with the point laser to obtain the actual spatial pose of the ceramic core. Finally, the collected points are imported into UG software to obtain the actual spatial pose point set of the ceramic core. Based on the ceramic core measurement plan, a point laser measuring head is used to detect the ceramic core surface and obtain the actual Z-axis height value from the measuring head to the ceramic core surface. The obtained Z-axis height value Z 测 The data obtained from point laser measurement only represents the actual Z-axis distance from the point laser probe to the ceramic core surface. Further data processing is needed to obtain the point laser detection point cloud. The processing steps are as follows: First, calculate the distance Z measured by the point laser. 测 With theoretical height Z 理 The deviation is obtained through equation (1). .

[0036] (1) Secondly, based on the obtained deviation value and the Z-axis coordinate value in the point laser measurement NC code (numerical control program code), the Z1 value of the actual measuring point in the point laser detection coordinate system is obtained through formula (2). This value is then combined with the XY value of each detection point in the NC code to obtain the coordinate value {X,Y,Z1} of the detection point in the detection coordinate system.

[0037] (2) Then, based on the obtained coordinate values ​​after a post-processing inverse operation (3), the actual {x,y,z1} values ​​in the planned measurement coordinate system can be obtained. (3) Where B represents the angle between the printing device and the center of rotation of its turntable.

[0038] Step 2: Select the actual spatial pose point cloud of the ceramic core imported in Step 1, set the weights of the leading edge, trailing edge, leaf base, and leaf back, and then select all imported point clouds and ceramic core for weighted ICP calculation to obtain a set of registration point clouds, and the rotation matrix R and translation matrix T of the actual spatial pose point cloud of the ceramic core and the registration point cloud. The optimal pose of the ceramic core is accurately calculated using the ICP (Iterative Closest Point) registration algorithm. Based on the translation matrix T and rotation matrix R obtained from the registration, the corresponding Euler angles and translation amounts are calculated. This allows the ceramic core and the soft core support model to be moved to eliminate manufacturing errors in the ceramic core profile. The specific steps are as follows: First, assume that the actual set of points for detecting errors in the ceramic core surface is Q, and the set of points corresponding to its nearest projection onto the theoretically designed ceramic core surface is P, where the two point clouds are Q=q1,...,q N ,P=p1,...,p N Q represents the target point cloud, P represents the initial point cloud, and N represents the total number of points in the point cloud set. The goal of optimal spatial pose registration of the actual detected ceramic core relative to the theoretically designed ceramic core model is to find a suitable spatial transformation amount that minimizes the deviation between the corresponding detection points and the projected points. If correct registration can be achieved, that is, for any pair of registration points… , , ,have: (4) Where R represents the rotation matrix and S represents the translation matrix; Ensure the average deviation of the Euclidean distance of the overall point cloud after registration To minimize this, the objective function is established as follows: (5) Where n is the total number of iterations; Indicates the first i The weight of each point; Secondly, the core issue in solving ICP is calculating the average deviation that satisfies the minimum Euclidean distance. This study uses the SVD algorithm to calculate R and S, and the steps are as follows: Step 1: Since the point laser generates a set of detection points for the ceramic core surface error by detecting the ceramic core, the initial error is relatively small. Therefore, the initial spatial rotation matrix R is set. k=0 For an identity matrix, the translation matrix T k=0 It is a zero vector; Step 2: The coordinates of the projection point after the kth ceramic core spatial transformation are k is the number of algorithm iterations: (6) Step 3: Calculate the coordinates of the projected points after the kth ceramic core spatial transformation. The nearest projection point corresponding to the theoretically designed ceramic core surface. .

[0039] Step 4: Perform mean centering on the initial point cloud P and the target point cloud Q obtained from the kth calculation to obtain the centered point elements: (7) Then, subtract the mean from each point in the initial point cloud P and the target point cloud Q to obtain the decentralized points: (8) After decentralizing each point in the initial point cloud P and the target point cloud Q, two new point cloud datasets are obtained. and ; Step 5: Calculate the new point cloud dataset and The covariance matrix H: (9) Step 6: Perform SVD decomposition on the covariance matrix H: (10) Where U and V are orthogonal matrices. It is a diagonal matrix; Step 7: Calculate the rotation matrix R and the translation matrix T (11) Step 8: Calculate the point cloud of the ceramic core to be registered. and projection point set Average surface deviation with weight constraints between : (12) In the formula, This represents the average profile deviation between the actual tested ceramic core profile and the theoretical model, reflecting the wall thickness tolerance constraint. When ( If the preset iteration deviation threshold is met or the preset number of iterations is satisfied, the loop exits; otherwise, the next iteration will begin from step two.

[0040] Specifically, the weight Set a weight allocation strategy that satisfies the wall thickness tolerance constraint, as shown in the following expression:

[0041] In the formula, The cloud wall thickness at various points on the blade cross-section. for The minimum value in; K The ratio of wall thickness tolerance in different regions of the leaf blade is given. A ratio relationship is established based on the wall thickness tolerance of different parts, with the ratios of wall thickness tolerance at the leading and trailing edges to that at the leaf blade being denoted as follows:

[0042] In the formula, For the tolerance of the leading edge wall thickness; The tolerance for leaf wall thickness.

[0043] Step 3: Perform rotation and translation operations on the ceramic core and soft core support according to the rotation matrix R and translation matrix T to obtain the actual spatial pose of the ceramic core and soft core support; Step four: First, by selecting the contact surface between the bottom surface of the soft core support and the ceramic core surface at the corresponding printing position point, the basic slice data for the trajectory planning of the soft core support is obtained. Second, the printing gap height of the soft core support is set, and it is offset once along the normal direction of the surface to obtain the first layer slice data of the printing trajectory. Then, the basic slice data is offset again according to the set layer height to obtain the entire soft core support blank slice data. Finally, the printing trajectory is obtained according to the filling algorithm set for each layer. Step 5: Experiments were conducted with different printing gap heights (printer nozzle diameter 0.5mm). The experiments showed that, with other settings unchanged: when the printing gap height was below 0.05mm, the adhesion was low, only 1.35N, which could not withstand the milling cutting force of 3.17N; when the printing gap height was above 0.25mm, the adhesion was low, only 2.92N, which could not withstand the milling cutting force of 3.172N. Therefore, it was concluded that setting the printing gap height between 0.05mm and 0.25mm can effectively improve adhesion, with the maximum adhesion at 0.15mm, reaching 4.72N. This invention also provides a system for improving the adhesion between soft core supports and ceramic core layers prepared by conformal printing, comprising: The point laser measurement module is used to acquire the actual spatial pose point set of the ceramic core; The weighted ICP registration module is communicatively connected to the point laser measurement module and is used to perform weighted ICP calculations on the actual spatial pose point cloud of the ceramic core and the theoretical point cloud of the ceramic core model. The trajectory generation module is communicatively connected to the weighted ICP registration module and is used to generate multi-layer printing trajectories; The conformal printing execution module, including the printhead and motion control system, performs conformal printing on the ceramic core surface according to the printing trajectory; it dynamically maintains the printing gap height to ensure that the adhesion meets the requirements; An integrated control unit coordinates the operation of each module and monitors the printing gap accuracy in real time.

[0044] In one embodiment, the laser measurement in step one only obtains an actual Z value. It is necessary to match the XY value in the generated measurement code with the new Z value to obtain the actual XYZ value of the ceramic core spatial pose point.

[0045] In one embodiment, when performing weighted ICP registration in step two, it is necessary to manually select the point cloud and ceramic core, and when generating the printing trajectory, it is necessary to operate in UG. Therefore, it is implemented through secondary development of UG, which complicates the Ministry of Construction's use of different software.

[0046] In one embodiment, the other printing parameters set in step five of the printing gap test experiment are: temperature 70℃, air pressure 0.016MPa, layer height 0.4mm, printing speed 1000mm / min, filling algorithm "zigzag", and the experimental equipment is a ceramic core soft core support additive and subtractive material integrated processing platform.

[0047] This invention addresses manufacturing errors in ceramic cores by iteratively calculating the shortest distance from a point to a surface using the ICP algorithm. It then solves for the rotation matrix R and translation matrix T between the theoretical and actual spatial poses. Based on these obtained rotation and translation matrices, the actual spatial pose of the ceramic core is derived, allowing for the setting of an appropriate printing gap to improve adhesion. Traditional methods for improving adhesion involve attaching heating pads to the ceramic core surface or using a hot air gun. This invention, by improving adhesion through the printing gap, eliminates the need for auxiliary heating, making the soft core support fabrication process more convenient and faster, and improving printing efficiency.

[0048] In one embodiment, refer to Figure 1 As shown, the path planning process for the free-form ceramic core with variable thickness soft core support in this embodiment includes the following steps: Step one: By setting a constant distance between the point laser and the ceramic core surface in the theoretical model, a sampling trajectory is generated. The sampling process is as follows: Figure 2 As shown, a point laser is used to strike the surface of the ceramic core to calculate the actual distance from the point to the surface, thereby obtaining the actual spatial pose of the ceramic core.

[0049] Step two: Import the coordinates of the collected points obtained through data processing into the UG software, such as... Figure 3 As shown, the actual spatial pose points of the ceramic core can be obtained; Step 3: Select the actual spatial pose point cluster of the ceramic core imported in Step 1, and set the weights for the leading edge, trailing edge, leaf base, and leaf back, as follows: Figure 4 As shown. Then, weighted ICP calculations were performed on all imported point clouds and ceramic cores to obtain a set of registration point clouds, and the rotation matrix R and translation matrix T of the actual spatial pose point cloud set of the ceramic core and the registration point cloud set, as shown. Figure 5-6 As shown; Step four: Based on the rotation matrix R and translation matrix T obtained in step three, perform rotation and translation operations on the ceramic core and soft core support to obtain their actual spatial poses, such as... Figure 7 As shown; Step four: First, by selecting the contact surface between the bottom surface of the soft core support and the ceramic core surface at the corresponding printing position, the basic slice data for trajectory planning of the soft core support is obtained. Second, the printing gap height of the soft core support is set, such as... Figure 8 As shown, the first layer of the printing trajectory slice data is obtained by offsetting it once along the normal direction of the curved surface. Then, the basic slice data is offset again according to the set layer height to obtain the entire soft core support blank slice data. Finally, the printing trajectory is obtained according to the filling algorithm set for each layer, as shown. Figure 9 As shown; Step 5: Following the steps in Step 4, conduct printing experiments with print gap heights of 0.05mm, 0.1mm, 0.15mm, 0.2mm, 0.25mm, and 0.3mm respectively to verify the results. Figure 10 As shown.

[0050] Step six: Subsequently, using the same milling parameters, experiments were conducted to investigate whether the adhesion generated by different printing gaps could resist milling forces, such as... Figure 11 As shown in the figure. The experiment found that when the printing gap was set to 0.05mm, the printed soft core support could not effectively resist the milling force. Because the printing gap was too small, the extrusion volume was too small to effectively form an adhesive layer. When the printing gap was set to 0.3mm, the printed soft core support could not effectively resist the milling force either. Because the printing gap was too large, the resulting adhesive layer failed to make effective contact with the ceramic core surface, resulting in low adhesion.

[0051] A printing gap of 0.15mm was selected as the experimental parameter. The printing trajectory after ICP registration was compared with the unregistered printing trajectory. The experiment found that the soft core support printed on the ceramic core surface after registration could effectively resist the milling force. However, the soft core support printed by the unregistered printing trajectory was milled off in some places. This is because the unregistered printing trajectory cannot effectively guarantee a printing gap of 0.15mm. The actual printing gap may be less than 0.05mm or greater than 0.3mm.

[0052] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the present invention.

Claims

1. A method for improving the adhesion between a soft core support and a ceramic core layer prepared by conformal printing, characterized in that, Includes the following steps: Step 1: Obtain the actual spatial pose point cloud of the ceramic core through point laser measurement: The laser is positioned at a constant distance from the ceramic core surface in the theoretical model to generate the sampling trajectory. A point laser is used to strike the surface of the ceramic core to calculate the actual distance from the point to the surface, thus obtaining the actual spatial pose data of the ceramic core. Import the collected point cloud data into the model design software to generate a set of actual spatial pose points for the ceramic core. Step 2: Register the ceramic core pose using the weighted ICP algorithm on the obtained actual spatial pose point cloud of the ceramic core: Set the weights for the leading edge, trailing edge, leaf base, and leaf underside; Weighted ICP calculations were performed on the actual spatial pose point cloud of the ceramic core and the point cloud of the theoretical ceramic core model to solve for the rotation matrix R and the translation matrix T. The covariance matrix is ​​calculated by using SVD decomposition. The iteration continues until the average surface deviation is less than the set deviation threshold or the set number of iterations is reached, thus obtaining the average deviation that satisfies the minimum Euclidean distance. Step 3: Correct the spatial pose of the ceramic core and the soft core support according to the rotation matrix R and the translation matrix T; Step 4: Generate the soft core support printing trajectory: The data for the slicing were based on the contact surface between the bottom surface of the soft core support and the curved surface of the ceramic core. Set the print gap height, and generate the first layer of slice data by offsetting the print gap height along the surface normal direction; The soft core support blank slice data is generated by continuously offsetting the layer height, and the printing trajectory is generated by combining the filling algorithm. Step 5: Perform conformal printing based on the printing trajectory to obtain a soft core support; The printing gap height is controlled by the target adhesion force.

2. The method for improving the adhesion between the soft core support and the ceramic core layer prepared by conformal printing according to claim 1, characterized in that: The data processing in step one includes: Calculate the actual Z-axis height Z from the probe of the point laser measurement to the surface of the ceramic core. 测 With theoretical height Z 理 The deviation ΔZ, ΔZ=Z 理 -Z 测 ; Based on the deviation ΔZ and the Z-axis coordinate value Z in the point laser measurement CNC program code, the Z1 value of the actual measuring point in the point laser detection coordinate system is calculated by Z1=Z+ΔZ. The coordinates {X,Y,Z1} in the point laser detection coordinate system are obtained by splicing the XY values ​​in the CNC program code. The coordinates {X,Y,Z1} in the point laser detection coordinate system are converted into the actual coordinates {x,y,z1} in the planned measurement coordinate system through inverse post-processing, as shown in the following expression: Where B represents the angle between the printing device and the center of rotation of its turntable.

3. The method for improving the adhesion between the soft core support and the ceramic core layer prepared by conformal printing according to claim 2, characterized in that: The constant distance is a preset fixed distance between the point laser and the surface of the ceramic core in the theoretical model, and the sampling trajectory covers all areas of the ceramic core to be printed soft core support.

4. The method for improving the adhesion between the soft core support and the ceramic core layer prepared by conformal printing according to claim 3, characterized in that: The weighted ICP algorithm specifically includes: Define Q, the actual spatial pose point cloud set of the ceramic core, as the target point cloud, and theoretically design P, the nearest projection point set corresponding to the ceramic core surface, as the initial point cloud. The objective function D is minimized through iterative calculation, as shown in the following expression: In the formula, D represents the average deviation of the Euclidean distance of the overall point cloud, R represents the rotation matrix, and S represents the translation matrix. n Indicates the total number of iterations. , , i Indicates the index of the point cloud's focal point; Indicates the first i The weight of each point.

5. The method for improving the adhesion between the soft core support and the ceramic core layer prepared by conformal printing according to claim 4, characterized in that: The iterative calculation includes: Set the initial rotation matrix R k=0 For an identity matrix, the translation matrix S k=0 It is a zero vector; Calculate the coordinates of the projection points of the ceramic core spatial transformation And determine its nearest projection point on the theoretically designed ceramic core surface. ;in, k Indicates the number of iterations. N This represents the total number of points in the point cloud set; The initial point cloud P and the target point cloud Q are mean-centered to obtain the centered point cloud: Subtract the mean of each point in the initial point cloud P and the target point cloud Q to obtain the decentralized points: After decentralizing each point in the initial point cloud P and the target point cloud Q, two new point cloud datasets are obtained. and ,calculate and The covariance matrix H: SVD decomposition of the covariance matrix H yields Where U and V are orthogonal matrices, and Λ is a diagonal matrix; Calculate the rotation matrix R and the translation matrix T: Calculate the point cloud of the ceramic core to be registered and projection point set Average surface deviation with weight constraints between : In the formula, This represents the average profile deviation between the actual tested ceramic core profile and the theoretical model, constrained by the wall thickness tolerance. Or, if the set number of iterations is met, the loop exits. The preset iteration deviation threshold is used; otherwise, the next iteration will start from step two.

6. The method for improving the adhesion between the soft core support and the ceramic core layer prepared by conformal printing according to claim 5, characterized in that: The weight Set a weight allocation strategy that satisfies the wall thickness tolerance constraint, as shown in the following expression: In the formula, The cloud wall thickness at various points on the blade cross-section. for The minimum value in; K The ratio of wall thickness tolerance in different regions of the leaf blade is given. A ratio relationship is established based on the wall thickness tolerance of different parts, with the ratios of wall thickness tolerance at the leading and trailing edges to that at the leaf blade being denoted as follows: In the formula, For the tolerance of the leading edge wall thickness; The tolerance for leaf wall thickness.

7. The method for improving the adhesion between the soft core support and the ceramic core layer prepared by conformal printing according to claim 6, characterized in that: In step five, the printing gap height is 0.05–0.25 mm, the adhesion force is ≥4.72 N, and it can resist a milling cutting force of 3.17 N.

8. The method for improving the adhesion between the soft core support and the ceramic core layer prepared by conformal printing according to claim 7, characterized in that: The printing parameters in step five include: temperature 70℃, air pressure 0.016MPa, layer height 0.4mm; printing speed 1000mm / min, and filling algorithm in a zigzag pattern.

9. The method for improving the adhesion between the soft core support and the ceramic core layer prepared by conformal printing according to claim 8, characterized in that: Adhesion verification includes: When the printing gap is <0.05mm or >0.25mm, the adhesion force is >3.17N, which cannot resist milling force; The soft core support portion of the unregistered trajectory printing detached, but did not detach after registration.

10. A system for improving the adhesion between a soft core support and a ceramic core layer prepared by conformal printing, used to implement the method for improving the adhesion between a soft core support and a ceramic core layer prepared by conformal printing as described in any one of claims 1-9; characterized in that, include: The point laser measurement module is used to acquire the actual spatial pose point set of the ceramic core; The weighted ICP registration module is communicatively connected to the point laser measurement module and is used to perform weighted ICP calculations on the actual spatial pose point cloud of the ceramic core and the theoretical point cloud of the ceramic core model. The trajectory generation module is communicatively connected to the weighted ICP registration module and is used to generate multi-layer printing trajectories; The conformal printing execution module, including the printhead and motion control system, performs conformal printing on the ceramic core surface according to the printing trajectory; it dynamically maintains the printing gap height to ensure that the adhesion meets the requirements; An integrated control unit coordinates the operation of each module and monitors the printing gap accuracy in real time.

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