Electron beam selective additive rotation body part automatic polishing method

Abstract

An electron beam selected area additive rotation body part automatic polishing method, comprising using three-dimensional scanning point cloud data as input, reducing data amount and removing noise points, then using ICP algorithm for point cloud matching, and matching the point cloud data to the template point cloud; extracting the region of interest required for path point calculation, using octree to obtain path points, and then using shared bus equation to remove abnormal points for fitting, finally obtaining path points; the obtained path points are segmented by convolution region, non-convolution feature is recognized, and path layers are equally spaced, to obtain the planned machining path and the matching parameter package; using positioning rotary tooling and force feedback module, real-time monitoring, feedback, adjustment and accurate execution of the preset contact force are realized, so that the polishing tool follows the surface profile change of the workpiece in real time, and the force and stroke of the polishing tool are displayed in real time, completing the conformal quantitative polishing of the part, and improving the problem that the existing additive manufacturing rudder surface product post-processing efficiency and precision are limited.

Description

Technical Field

[0001] This invention relates to an automatic grinding method for electron beam selective additive manufacturing of rotating parts, belonging to the field of additive manufacturing post-processing. Background Technology

[0002] Electron beam selective melting (EBSM) is an additive manufacturing process that uses an electron beam to scan and melt powder material, depositing it layer by layer to create three-dimensional metal parts. It is suitable for forming and manufacturing refractory high-performance metal materials such as titanium alloys and titanium-aluminum based alloys. Compared with laser selective melting additive manufacturing, EBSM has the following advantages: ① The vacuum environment reduces atmospheric pollution, making it particularly suitable for forming reactive metals such as titanium; ② Higher energy efficiency, suitable for manufacturing refractory metals and high-temperature alloys; ③ Higher scanning speed allows for innovative preheating and melting strategies, a characteristic crucial for forming brittle metal materials (such as TiAl intermetallic alloys); ④ Reduced residual stress, fewer post-processing steps, and no need for shape supports.

[0003] However, a significant limitation of electron beam selective melting additive manufacturing is the poor surface integrity and finish of the formed parts. Patent CN202211597855.8 proposes an in-situ surface treatment device and method for electron beam filament additive manufacturing. This method adjusts the relative position and angle of the printed part to the surface treatment electron beam gun by rotating and tilting a platform, enabling the surface treatment electron beam gun to treat both the inner and outer surfaces of the printed part in situ, thus completing in-situ surface treatment and heat treatment. Patent CN202310645436.5 discloses a printing method to improve the surface quality of electron beam additive manufacturing. This method includes: optimizing slicing parameters, designing a contour dashed line scanning strategy, adjusting the perimeter and contour parameters, using in-situ electron beam remelting to achieve smoothing and homogenization of the electron beam scanning traces, and improving the surface quality of the perpendicular workpiece side surface through slicing optimization and refined control of the contour melt channel size and morphology. Patent CN202010548795.5 relates to a method for suppressing powder splashing in electron beam 3D printing. The method involves preheating the powder in the forming area of ​​the powder bed with a second round of electron beam scanning, melting the powder in the preset area after the second round of electron beam scanning preheating, and then performing a third round of electron beam scanning preheating. During the 3D printing process, there is virtually no powder splashing, resulting in a 3D printed component with high density and low surface roughness. Patent CN202011355229.9 discloses a process method for improving the surface quality of electron beam additive manufacturing parts. This method involves precisely remelting the outer contour formed by electron beam melting of the added auxiliary material in the melting process of additive manufacturing using a laser, and then proceeding to the cooling process of additive manufacturing to obtain the required surface quality of the part. The surface roughness of the precisely remelted additive manufacturing part does not exceed Ra12.

[0004] Some of the methods mentioned above are designed for electron beam filament additive manufacturing, but they are poorly adapted to electron beam selective melting additive manufacturing. Furthermore, they all involve optimizing the parameters of the electron beam additive itself and do not involve post-processing. Traditional manual polishing methods are inefficient, difficult to control, and result in inconsistent product quality. Therefore, a flexible, high-precision, and convenient robotic polishing technique for electron beam selective melting additive manufacturing products urgently needs to be developed. Summary of the Invention

[0005] The technical problem solved by the present invention is to overcome the shortcomings of the prior art and provide an automatic grinding method for electron beam selective additive manufacturing of rotating parts, thereby improving the limited efficiency and accuracy of post-processing of existing additive manufacturing rudder surface products.

[0006] The technical solution of this invention is: an automatic grinding method for electron beam selective additive manufacturing of rotating parts, comprising:

[0007] Using 3D scanned point cloud data as input, downsampling and filtering are used to reduce the amount of data and remove noise. Then, the ICP algorithm is used to match the point cloud data to the template point cloud. The region of interest required for path point calculation is obtained by using the section method and envelope block extraction. The path points are obtained by using an octree. Then, the shared bus equation is used to remove outliers and fit the data to finally obtain the path points.

[0008] The obtained path points are segmented into spiral regions, identified as non-spiral features, and layered with equal spacing between path layers to obtain the planned processing path and the corresponding parameter package.

[0009] Using a positioning rotary fixture and a force feedback module, the preset contact force is monitored, fed back, adjusted, and precisely executed in real time, enabling the grinding tool to follow the changes in the workpiece surface contour in real time. At the same time, the force and stroke of the grinding tool are displayed in real time, completing the conformal quantitative grinding of the parts.

[0010] Preferably, the downsampling subdivides the three-dimensional space of the rotating part into uniformly sized three-dimensional grid voxel units, with the voxel center or the point closest to the center of mass as the sampling retention point.

[0011] Preferably, when the shared bus equation is estimated using the RANSAC algorithm:

[0012] After randomly initializing the model assumptions, the deviation of each point in the dataset from the model is evaluated, and internal and external points are distinguished according to the preset tolerance threshold. Through repeated iterations, the largest consensus set is identified, and then the least squares method is applied to refine the model parameters to best fit this core point set.

[0013] Preferably, the spiral region segmentation is specifically as follows:

[0014] The workpiece is divided into sections with the smallest rotational overlap angle. The smallest repeating unit after division is the rotary grinding area unit. The rotary area unit is further divided according to the generatrix. When the curvature of the generatrix changes abruptly, the rotary grinding unit is divided into sections.

[0015] Preferably, during non-rotation feature recognition, the workpiece is rotated according to the minimum rotational overlap angle, and the local features that cannot be overlapped are identified as non-rotation features.

[0016] Preferably, when the path layers are equally spaced, the workpiece is divided based on a series of plane clusters, and the boundary line between the plane and the workpiece surface contour is defined as the set of path points for this layer.

[0017] Preferably, the positioning rotary fixture enables the workpiece to be positioned and rotated at the minimum rotational overlap angle, with a diameter ≥ 650 mm and a repeatability ≤ 0.005° / mm.

[0018] Preferably, the force feedback module includes a grinding force sensor, a micro-power actuator, and an integrated force control unit, wherein:

[0019] The grinding force sensor monitors, provides feedback, adjusts, and precisely executes the preset contact force in real time, ensuring the accuracy of the surface contact force of the grinding tool in any posture.

[0020] The micro-powered actuator tracks and compensates for changes in the workpiece surface contour in real time, ensuring stable tracking between the tool and the workpiece surface;

[0021] The integrated force control unit displays the force and stroke measured by the grinding force sensor in real time, and sends commands to the micro-power actuator to control the grinding tool and the automated operation of surrounding products.

[0022] Compared with the prior art, the present invention has the following advantages:

[0023] (1) The present invention solves the problem of surface defects in electron beam selected additive products through post-processing, which is conducive to the promotion of new forming manufacturing processes and large-scale production.

[0024] (2) This invention makes full use of the characteristics of rotary body parts, the grinding scheme is convenient and efficient, avoids repetitive programming work, improves grinding efficiency, better improves quality control, and ensures consistent product quality. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of workpiece swirling region segmentation and non-swirling feature recognition according to an embodiment of the present invention;

[0026] Figure 2 This is the complete point cloud after processing according to an embodiment of the present invention.

[0027] Explanation of reference numerals in the attached diagram: 1-Upper cylindrical surface outside the first region; 2-Upper curved surface outside the second region; 3-Lower curved surface outside the third region; 4-Lower cylindrical surface outside the fourth region; 5-Repeating boss in the fifth region; 6-Upper cylindrical surface inside the sixth region; 7-Upper curved surface inside the seventh region; 8-Lower curved surface inside the eighth region; 9-Lower cylindrical surface inside the ninth region; 10-First mounting platform; 11-Second mounting platform; 12-XY plane. Detailed Implementation

[0028] This invention proposes an automatic grinding method for electron beam additive rotating parts. The method is characterized by using three-dimensional scanning point cloud to acquire workpiece contour detection technology, planning the processing path and supporting parameter package, and cooperating with positioning rotary tooling and force feedback module to achieve conformal quantitative grinding of the workpiece.

[0029] The aforementioned 3D scanning point cloud acquisition workpiece contour detection technology uses 3D scanning point cloud data as input, employs downsampling and filtering to reduce data volume and remove noise, then uses the ICP algorithm for point cloud matching to match the point cloud data to the template point cloud, and uses the section method and envelope block extraction to extract the region of interest required for path point calculation, uses an octree to obtain path points, and then uses the shared bus equation to remove outliers and fit the data to finally obtain the path points.

[0030] The planned processing path includes swirling region segmentation, non-swirling feature recognition, and equal-spaced layering between path layers.

[0031] The aforementioned parameter package includes different partition parameter packages and non-rotation feature parameter packages within each rotary unit. Different grinding rotary units repeatedly execute the combination of partition parameter packages within each rotary unit.

[0032] The positioning and rotating fixture includes a clamping and locking device and an intermittent rotating device. The clamping and locking device is fixed on a support platform, which is connected to the intermittent rotating device via bearings. The intermittent rotating device is connected to the system via a data interface. The positioning and rotating fixture enables the workpiece to be positioned and rotated at the minimum rotational overlap angle, with a diameter ≥ 650 mm and a repeatability ≤ 0.005° / mm. In this embodiment, the workpiece is positioned and rotated at the minimum rotational overlap angle of 60°, with a diameter 700 mm and a repeatability 0.003° / mm.

[0033] The force feedback module includes a grinding force sensor, a micro-power actuator, and an integrated force control unit.

[0034] The downsampling method subdivides the three-dimensional space of the part into uniformly sized three-dimensional grid voxel units, and the center of mass of the voxel or the point closest to the center of mass is used as the sampling retention point.

[0035] The point cloud registration process involves transforming the converted workpiece point cloud to a standard coordinate system and unifying the sets of points obtained from different viewpoints into a fixed coordinate system to form a complete point cloud, as shown in the attached figure. Figure 2 As shown.

[0036] The shared bus equation is estimated using the RANSAC (Random Sample Consensus) algorithm. First, model assumptions are randomly initialized. Then, the deviation of each point in the dataset from the model is evaluated, and internal and external points are distinguished based on a preset tolerance threshold. Through repeated iterations, the largest consensus set is identified. Subsequently, the least squares method is applied to refine and adjust the model parameters to best fit this core point set. In this case, a straight line is selected as the fitting model. A random sampling strategy is used for data segmentation, and a reasonable error limit is set. This approach yields the mathematical expression of the bus and its corresponding interior point indices.

[0037] The described rotary region segmentation divides the workpiece into sections with the minimum rotational overlap angle (60° in this embodiment). The smallest repeating unit after segmentation is the rotary grinding region unit. Within each rotary region unit, further subdivisions are made according to the generatrix. When the curvature of the generatrix changes abruptly, subdivisions are performed within the rotary grinding unit, such as... Figure 1 As shown, the outer surface is divided into the first region 1 outer upper cylindrical surface, the second region 2 outer upper curved surface, the third region 3 outer lower curved surface, the fourth region 4 outer lower cylindrical surface, and the fifth region 5 repeating boss. The inner surface is divided into the sixth region 6 inner upper cylindrical surface, the seventh region 7 inner upper curved surface, the eighth region 8 inner lower curved surface, and the ninth region 9 inner lower cylindrical surface.

[0038] The non-rotational feature recognition identifies the local features that cannot be overlapped after rotating the workpiece by the minimum rotational overlap angle of 60° as the first mounting platform 10 and the second mounting platform 11.

[0039] The path layers are equally spaced, based on a series of parallel XY reference planes (such as...). Figure 1 The workpiece is divided into planar clusters (as shown in Figure 12). The boundary line between the plane and the surface contour of the workpiece is defined as the set of path points of this level. In this embodiment of the invention, the part height is 250mm and the Z-axis spacing of the planar clusters is 5mm.

[0040] The aforementioned grinding force sensor monitors, provides feedback, adjusts, and precisely executes the preset contact force in real time, ensuring that the accuracy of the surface contact force is ≤1N under any posture of the tool (robot). In this embodiment of the invention, the accuracy of the surface contact force is 0.5N.

[0041] The aforementioned micro-power actuator compensates for changes in the workpiece surface contour in real time, ensuring stable tracking of the tool and the workpiece surface.

[0042] The integrated force control unit displays the force and stroke measured by the grinding force sensor in real time, and can send commands to the micro-power actuator to control the grinding tool and automate the operation of peripheral products.

[0043] The aforementioned conformal quantitative grinding has a grinding amount of 0.3mm.

[0044] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0045] The contents not described in detail in this specification are existing technologies known to those skilled in the art.

Claims

1. An automatic grinding method for electron beam selective additive manufacturing of rotating parts, characterized in that: include: Using 3D scanned point cloud data as input, downsampling and filtering are used to reduce the amount of data and remove noise. Then, the ICP algorithm is used to match the point cloud data to the template point cloud. The region of interest required for path point calculation is obtained by using the section method and envelope block extraction. The path points are obtained by using an octree. Then, the shared bus equation is used to remove outliers and fit the data to finally obtain the path points. The obtained path points are segmented into a rotary region, identified as non-rotary features, and layered into equal-spacing paths to obtain the planned processing path and its associated parameter package. The rotary region segmentation is as follows: the workpiece is segmented with the minimum rotational overlap angle. The smallest repeating unit after segmentation is the rotary grinding region unit. The rotary grinding region unit is further divided according to the generatrix. When the curvature of the generatrix changes abruptly, the rotary grinding region unit is divided into different areas. Using a positioning rotary fixture and a force feedback module, the preset contact force is monitored, fed back, adjusted, and precisely executed in real time, enabling the grinding tool to follow the changes in the workpiece surface contour in real time. At the same time, the force and stroke of the grinding tool are displayed in real time, completing the conformal quantitative grinding of the parts.

2. The automatic grinding method for electron beam selective additive manufacturing rotating parts according to claim 1, characterized in that: The downsampling process subdivides the three-dimensional space of the rotating part into uniformly sized three-dimensional grid voxel units, with the voxel's center or the point closest to the center being used as the sampling retention point.

3. The automatic grinding method for electron beam selective additive manufacturing rotating parts according to claim 1, characterized in that: When the shared bus equations are estimated using the RANSAC algorithm: After randomly initializing the model assumptions, the deviation of each point in the dataset from the model is evaluated, and internal and external points are distinguished according to the preset tolerance threshold. Through repeated iterations, the largest consensus set is identified, and then the least squares method is applied to refine the model parameters to best fit this core point set.

4. The automatic grinding method for electron beam selective additive manufacturing rotating parts according to claim 1, characterized in that: When identifying non-rotational features, the workpiece is rotated at the minimum rotational overlap angle, and the local features that cannot be overlapped are identified as non-rotational features.

5. The automatic grinding method for electron beam selective additive manufacturing rotating parts according to claim 1, characterized in that: When the path layers are equally spaced, the workpiece is divided based on a series of plane clusters, and the boundary line between the plane and the workpiece surface contour is defined as the set of path points for this level.

6. The automatic grinding method for electron beam selective additive manufacturing of rotating parts according to claim 1, characterized in that: The positioning rotary fixture enables the workpiece to be positioned and rotated with the minimum rotational overlap angle, with a diameter ≥650mm and a repeatability ≤0.005° / mm.

7. The automatic grinding method for electron beam selective additive manufacturing rotating parts according to claim 1, characterized in that: The force feedback module includes a grinding force sensor, a micro-power actuator, and an integrated force control unit, wherein: The grinding force sensor monitors, provides feedback, adjusts, and precisely executes the preset contact force in real time, ensuring the accuracy of the surface contact force of the grinding tool in any posture. The micro-powered actuator tracks and compensates for changes in the workpiece surface contour in real time, ensuring stable tracking between the tool and the workpiece surface; The integrated force control unit displays the force and stroke measured by the grinding force sensor in real time, and sends commands to the micro-power actuator to control the grinding tool and the automated operation of surrounding products.

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