CN116787777A - Method and system for co-segmentation of body and surface for manufacturing mixed increase and decrease materials - Google Patents

Abstract

The invention provides a method and a system for co-segmentation of a body and a table for manufacturing mixed increase and decrease materials, which are characterized in that a beam search tree is established, corresponding nodes and ancestor nodes thereof are determined according to the beam search tree, and blocks represented by all the nodes are combined to obtain a final model segmentation scheme. And the method is widely applicable to various three-dimensional models.

Description

Method and system for co-segmentation of body and surface for manufacturing mixed increase and decrease materials

Technical Field

The invention belongs to the technical field of additive and subtractive mixed manufacturing, and relates to a method and a system for co-segmentation of a body and a surface for mixed additive and subtractive manufacturing.

Background

The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.

Additive, subtractive hybrid manufacturing (ASHM) techniques combine the capabilities of additive manufacturing and subtractive manufacturing, take advantage of 3D printing in manufacturing complex geometries and improving material utilization, and numerically controlled processing in high machining accuracy and high quality surface treatments. The ASHM will eliminate stair-step defects caused by layered manufacturing, achieving higher product accuracy and excellent surface finish compared to 3D printing. ASHM is more flexible in manufacturing complex structures with aggressive geometries than numerical control machining. More and more people believe that in the near future, ASHM will show its great potential in workshops and become an important component of industrial, aerospace and consumer products.

However, hybrid manufacturing must take into account both additive and subtractive manufacturing computational geometries, which is far from fully automated, particularly for generally complex geometries. Hybrid fabrication is mainly achieved by a print head that builds up a 3D volume by depositing material layer by layer (each layer being a planar slab of the object) and a numerically controlled processing tool that engraves the material on the 3D surface according to a prescribed spatial profile. The specific manufacturing process for the ASHM consists of a set of "AM-then-SM" manufacturing stages. At each stage, solid shaping of the three-dimensional model is first achieved by Additive Manufacturing (AM), and then the three-dimensional model surface is finished by Subtractive Manufacturing (SM). Due to the geometry of the three-dimensional model and the freedom of movement of the print head and the numerically controlled tooling, it is often not possible to complete hybrid fabrication in a single "AM-then-SM" stage.

Sequence planning is the task of determining alternating sequences { A1, S1, A2, S2,..an, sn } where a and S represent additive and subtractive steps, respectively. The most critical point in sequence planning is to explore the minimum number of "AM-then-SM" switches. Each Ai or Si requires recalibration and some pre-treatment of the printhead or the cnc tool, which may greatly affect the overall efficiency of manufacturing. Furthermore, the location of process switching invariably produces undesirable finishing artifacts that affect surface quality and manufacturing accuracy. Thus, an ideal sequence plan requires as few process switches as possible in terms of process efficiency and product quality. The key challenge of hybrid manufacturing sequence planning is that after each "AM-then-SM" phase, the shape to be achieved can vary greatly, with consequent dynamic changes in tool accessibility, which greatly increases the difficulty of sequence planning. Each a or S manufacturing process cannot violate the printhead/tooling tool accessibility and manufacturing dependency constraints, where the printhead/tooling tool is not allowed to collide with the molded part of the mold and the machine itself. In addition, the model must be free of support structures during the additive stage. Since each time an "AM-then-SM" sequence makes a block of the model, the sequence planning problem can be equivalently translated into a three-dimensional model segmentation problem, namely: the three-dimensional model is partitioned into as few partitions as possible, each partition being fabricated by a single "AM-then-SM" sequence, provided that the fabrication constraints are met.

The inventors have appreciated that little research is currently done on this problem, and that existing methods have limited this problem to a specific shape (mainly columnar structures) and are not applicable to general models.

Disclosure of Invention

In order to solve the problems, the invention provides a method and a system for co-segmentation of a body and a surface for manufacturing mixed increase and decrease materials, which can divide the body and the surface into as few blocks as possible on the premise of meeting manufacturing constraints, and each block can be manufactured through an AM-then-SM sequence. And the method is widely applicable to various three-dimensional models.

According to some embodiments, the present invention employs the following technical solutions:

a body and surface co-segmentation method for manufacturing mixed increase and decrease materials comprises the following steps:

obtaining a three-dimensional model;

performing material reduction collision detection on the three-dimensional model, and establishing a graph to represent the reachability relationship among the nodes;

establishing a beam search tree, determining corresponding nodes and ancestor nodes thereof according to the beam search tree, combining blocks represented by all the nodes to obtain a final model segmentation scheme, and executing the following steps in each iteration process of searching:

searching the corresponding blocks of ancestor nodes, finding out the nodes of the constructed graph containing the blocks, deleting the nodes and the connected edges from the graph to form a new graph

Sampling a plurality of candidate additive directions, each direction being down to a model level slice, performing collision detection of the printhead, and creating a map

Integration ofAnd->Build up of a diagram->

Iterative merging graphObtaining corresponding blocks;

selecting a plurality of blocks with highest scores through an evaluation function, and adding the blocks into a beam search tree.

As an alternative implementation mode, the specific process of performing the material reduction collision detection on the three-dimensional model comprises the step of adopting centroid Voronoi mosaic to realize uniform sampling on the surface of the model, wherein each Voronoi cell is represented by a site thereof, the collision detection of a tool is performed on each site and other sites, and if a certain site is not reachable in any direction, the collision detection is called a non-reachable point.

As an alternative embodiment, the specific process of creating the graph includes creating the graphEach node represents a sampling point, each coded edge represents the accessibility relation between two nodes, and if an edge pointing from node A to B exists, the cutter is blocked by B in a certain direction and cannot reach the direction when the cutter needs to process A, and the direction is recorded by the codes of the edges.

As an alternative embodiment, the specific process of building the beam search tree includes calculating the segmentation result of the model using a top-down beam search algorithm, each node in the tree representing a model segment.

As an alternative embodiment, a new graph is formedThe specific process of (1) comprises at the initial time of each iteration of beam search, firstly finding the corresponding blocks of the ancestor nodes, and finding the map +.>By never crossing the graph->The deletion of these nodes and the edges connected to them creates a new graph +.>

As an alternative embodiment, a plurality of candidate additive directions are sampled, each direction down to a model horizontal slice, collision detection of the printheads is performed, and a map is createdThe specific procedure of (1) comprises the step of establishing a picture +.>Uniformly sample N on Gaussian sphere _Dir In each direction, firstly, horizontally slicing the model by using a constant step length, and enabling a solid area between every two adjacent slice layers to be called Slab;

establishing a graphEach Slab corresponds to a node in the graph, performs collision detection of the printheads, and creates an edge in the graph.

Further, if there is an edge pointing from node a to node B, it means that if the corresponding slave B is already formed, the print head collides with the corresponding slave B when printing the slave B corresponding to a;

if one Slab contains an area where the overhang angle is too large to require a support structure, the corresponding node is provided with a corresponding label.

As an alternative embodiment, integrationAnd->Build up of a diagram->Comprises +.>Copy it as another figure +.>Then is a picture->A label is given to each node in the list to indicate whether the node meets the accessibility constraint of the material addition and the material reduction and the support-free constraint in the current state;

the label is a through graphAnd (2) a picture->The many-to-one mapping between the sampling points and the Slab is calculated by determining the many-to-one spatial position mapping relationship between the sampling points and the Slab, if a certain sampling point is not reachable in the current state,then in the picture->And correspondingly setting the node label corresponding to the mapped Slab.

As an alternative embodiment, an iterative merge mapThe specific procedure for obtaining the corresponding block comprises for each graph established +.>And merging all leaf nodes with labels which are not corresponding to the set labels into new nodes with other labels, and iteratively merging the other nodes into the new nodes one by one through a greedy algorithm.

A body and surface co-segmentation system for mixed additive and subtractive manufacturing, comprising:

the input module is used for acquiring a three-dimensional model;

the material reduction collision detection module is used for carrying out material reduction collision detection on the three-dimensional model, and establishing a graph so as to represent the accessibility relation among the nodes;

the segmentation module is used for establishing a beam search tree, determining corresponding nodes and ancestor nodes thereof according to the beam search tree, and combining the blocks represented by all the nodes to obtain a final model segmentation scheme;

the segmentation module specifically comprises a segmentation module and a segmentation module,

for searching the corresponding blocks of ancestor nodes, finding the blocks including the nodes of the constructed graph, deleting the nodes and connected edges from the graph, forming a new graphIs a module of (a);

for sampling a plurality of candidate additive directions, each direction down to a model level slice, performing collision detection of the printhead, creating a mapIs a module of (a);

for integration ofAnd->Build up of a diagram->Is a module of (a);

for iterative merging of graphsObtaining corresponding partitioned modules;

and a module for selecting blocks with highest scores through the evaluation function and adding the blocks into the beam search tree.

Compared with the prior art, the invention has the beneficial effects that:

the invention encodes the manufacturing constraint into a plurality of directed graphs, and simplifies the graphs through graph searching and specific judging standards, and finally can realize the co-segmentation of the model body and the table with the aim of least increasing and decreasing the process switching times, so that each block can be manufactured through one increasing and decreasing the process sequence on the premise of meeting the manufacturing constraint, and the method is widely applicable to various three-dimensional models.

In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.

FIG. 1 is a general flow chart of the present invention;

FIG. 2 is a flowchart of an algorithm of the present invention;

FIG. 3 is a diagram of the present inventionIs established in the process of the step (a);

FIG. 4 is a diagram of the present inventionIs established in the process of the step (a);

FIG. 5 is a diagram of the present inventionIs established in the process of the step (a);

FIG. 6 is a diagram of the present inventionIs a combined iteration diagram;

FIG. 7 is a graph of comparison results when different weights are set for each sub-evaluation function in the beam search evaluation function;

FIG. 8 is a partial result display diagram of the present invention.

Detailed Description

The invention will be further described with reference to the drawings and examples.

It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.

A method for co-dividing body and table for manufacturing mixed increase and decrease materials is characterized in that a model is divided into as few blocks as possible on the premise that manufacturing constraints are met, and each block can be manufactured through an AM-then-SM sequence. The invention is directly oriented to the manufacturing process, analyzes the three-dimensional model given by the user, and generates a model segmentation scheme for manufacturing the mixed increase and decrease materials.

According to some examples, as shown in fig. 1, 2, comprising the steps of:

step (1): acquiring stl or obj files corresponding to the three-dimensional model input by a user;

step (2): performing material reduction collision detection and establishing a graph

Step (3): establishing a beam search tree, and executing steps (4) - (8) in each iteration process of searching;

step (4): creating a graph

Step (5): sampling N _Dir Candidate additive directions, each direction establishing a graph

Step (6): integration ofAnd->Build up of a diagram->

Step (7): iterative merging graphObtaining corresponding blocks;

step (8): selecting a plurality of blocks with highest scores through an evaluation function, and adding the blocks into a beam search tree;

step (9): and obtaining a final model segmentation scheme according to the established beam search tree.

Specific details are set forth for each step:

in this embodiment, in step (1), the three-dimensional model is a closed model.

In this embodiment, the step (2) mainly includes the following steps:

step (2-1): uniform sampling is achieved with centroid Voronoi mosaics on the model surface, each Voronoi cell represented by its site. And then performing accessibility analysis of the machining tool: collision detection of the tool is performed for each sampling point (station) with other sampling points, and if a certain sampling point is not reachable in any direction, it is called "unreachable point".

Step (2-2): establishing a graphWhere each node represents a sample point and each band-encoded edge represents a reachability relationship between two nodes. If there is an edge pointing from node a to B, this indicates that the tool is not reachable by B in a direction that is recorded by the edge code, as in fig. 3 (a), when it is required to machine a.

In this embodiment, the step (3) mainly includes the following steps:

step (3-1): the segmentation results of the model are computed using a top-down beam search algorithm. The algorithm is actually a process of building a beam search tree, wherein each node in the tree represents a model block, and nodes which need to be added to the beam search tree are selected through the methods of steps (4) - (8) in each iteration of the beam search.

The step (4) mainly comprises the following steps:

step (4-1): at the initial time of each iteration of beam search, firstly finding the blocks corresponding to the ancestor nodes of the beam search, and finding the blocksIs a node of (a). By from->The deletion of these nodes and the edges connected to them creates a new graph +.>(as in fig. 3 (b)).

The step (5) mainly comprises the following steps:

step (5-1): each time a graph is built upUniformly sample N on Gaussian sphere _Dir And candidate additive directions. In each direction, the model is first sliced horizontally with a constant step, and the solid region between each two adjacent slice layers is called the "slot". Then build up a map->Each Slab corresponds to a node in the graph, performs collision detection of the printhead by invoking the method of the article "As-continuous-As-possible Extrusion-based Fabrication of Surface Models", and establishes an edge in the graph. If there is an edge pointing from node A to node B, it is indicated that if the Slab corresponding to B is already formed, the print head will collide with the Slab corresponding to B when printing the Slab corresponding to A. In addition, if one Slab includes an area where the overhang angle is too large to require a support structure, the corresponding node is set with a red label (as in fig. 4 (a)). In the collision detection process, we do not need to extract tetrahedrons of the three-dimensional model for calculation, but use closed curve calculation obtained by slicing, so that the calculation speed is greatly improved (as in (b) of fig. 4).

In this embodiment, the step (6) mainly includes the following steps:

step (6-1): for each graphCopy it as another figure +.>Then is a picture->A label is assigned to each node of (a) to indicate whether the node satisfies additive and subtractive accessibility constraints and support-free constraints in the current state. The label is by the picture->And (2) a picture->The many-to-one mapping between the sampling points and the Slab is calculated by determining the many-to-one spatial position mapping relationship between the sampling points and the Slab (as in (a) and (b) of FIG. 5). If a certain sampling point is not reachable in the current state, then in the diagram +.>The node label corresponding to the Slab to which it maps is set to red. Similarly, if a Slab is in the figure +.>The corresponding node label in (1) is red, then it is in +.>The corresponding node label in (a) is also set to red (as in fig. 5 (c)).

The step (7) mainly comprises the following steps:

step (7-1): for each graph builtAll leaf nodes with labels which are not red are combined into a new blue node, and the rest nodes are combined into the new blue node one by one in an iterative mode through a greedy algorithm (breadth-first search). The merging criteria are: the merged node is a leaf node and its label is not red. When the picture is->When the merging cannot be continued, the combination of all Slab contained in the blue new node is a candidate block of the three-dimensional model (FIG. 6 shows the graph +.>One example of iterative merging).

The step (8) mainly comprises the following steps:

step (8-1): beam searching all graphs calculated for each iterationEach corresponding to a candidate partition. Each candidate block is scored by an evaluation function:

F(B)＝∑w _k f _k (B),k∈[1,2,…,6]wherein f _k (B) Representing sub-evaluation functions, six in total:

f _size (B)＝∑Length(s _B ),s _B ∈S _B ；

f _priority (B)＝∑Priority(s _B ),s _B ∈S _B ；

f _connect (B)＝Component(S _B )；

wherein S is _B Representing a set of all slabs in partition B; s is(s) _B A closed curve representing the bottom of the Slab; length(s) _B ) Representing the length of the curve; priority(s) _B ) Priority score representing all sampling points in the Slab (the higher the sampling points block more other sampling points the higher the score); component (S) _B ) Representing the number of connected components of the block B;representing the additive direction of the block x; p represents the set of all cutting planes on partition x; distance (p, v) represents the Euclidean Distance of the frangible point v on the segment and the cutting plane p; project (p) represents the projection area of the segment beyond the cutting plane p in the two-dimensional plane; area (Project (p)) represents the Area of the projection region.

Weights w of each sub-evaluation function _k Are all limited between 0 and 1 by normalization, and Σw _k =1. And then, the W candidate blocks with the highest scores are respectively represented by one node and added into a beam search tree. Fig. 7 shows the segmentation result of the model with the weights of the six sub-evaluation functions set to 1, respectively.

In this embodiment, the step (9) mainly includes the following steps:

step (9-1): and taking out the highest scoring node obtained in the last iteration of the beam search, and then sequentially taking out ancestor nodes of the highest scoring node. The segments represented by these nodes are then combined to yield the final three-dimensional model segmentation scheme, where each segment is fabricated using a single "AM-then-SM" sequence.

It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

While the foregoing description of the embodiments of the present invention has been presented in conjunction with the drawings, it should be understood that it is not intended to limit the scope of the invention, but rather, it is intended to cover all modifications or variations within the scope of the invention as defined by the claims of the present invention.

Claims (10)

1. A body and surface co-segmentation method for manufacturing mixed increase and decrease materials is characterized by comprising the following steps:

obtaining a three-dimensional model;

performing material reduction collision detection on the three-dimensional model, and establishing a graph to represent the reachability relationship among the nodes;

establishing a beam search tree, determining corresponding nodes and ancestor nodes thereof according to the beam search tree, combining blocks represented by all the nodes to obtain a final model segmentation scheme, and executing the following steps in each iteration process of searching:

searching the corresponding blocks of ancestor nodes, finding out the nodes of the constructed graph containing the blocks, deleting the nodes and the connected edges from the graph to form a new graph

Sampling a plurality of candidate additive directions, each direction being down to a model level slice, performing collision detection of the printhead, and creating a map

Integration ofAnd->Build up of a diagram->

Iterative merging graphObtaining corresponding blocks;

selecting a plurality of blocks with highest scores through an evaluation function, and adding the blocks into a beam search tree.

2. The method for performing body and surface co-segmentation for mixed material increasing and decreasing manufacturing according to claim 1, wherein the specific process of performing material decreasing collision detection on the three-dimensional model comprises the step of adopting centroid Voronoi mosaic on the surface of the model to realize uniform sampling, wherein each Voronoi cell is represented by a site thereof, and collision detection is performed on a tool of each site and other sites, and if a certain site is not reachable in any direction, the method is called as a non-reachable point.

3. The method for co-dividing a body and a surface for manufacturing mixed increasing and decreasing materials according to claim 1, wherein the specific process of creating the graph comprises creating the graphEach node represents a sampling point, each coded edge represents the accessibility relation between two nodes, and if an edge pointing from node A to B exists, the cutter is blocked by B in a certain direction and cannot reach the direction when the cutter needs to process A, and the direction is recorded by the codes of the edges.

4. The method of claim 1, wherein the step of creating a beam search tree comprises computing model segmentation results using a top-down beam search algorithm, each node in the tree representing a model segment.

5. The method for co-dividing a body and a surface for manufacturing mixed increasing and decreasing materials according to claim 1, wherein a new graph is formedThe specific process of (1) comprises at the initial time of each iteration of beam search, firstly finding the corresponding blocks of the ancestor nodes, and finding the map +.>By never crossing the graph->The deletion of these nodes and the edges connected to them creates a new graph +.>

6. Such as weightThe method of co-dividing a body and a surface for mixed additive manufacturing according to claim 1, wherein a plurality of candidate additive directions are sampled, a model horizontal slice is taken in each direction, collision detection of a print head is performed, and a map is createdThe specific procedure of (1) comprises the step of establishing a picture +.>Uniformly sample N on Gaussian sphere _Dir In each direction, firstly, horizontally slicing the model by using a constant step length, and enabling a solid area between every two adjacent slice layers to be called Slab;

establishing a graphEach Slab corresponds to a node in the graph, performs collision detection of the printheads, and creates an edge in the graph.

7. The method of co-dividing a body and a table for mixed additive and subtractive manufacturing of claim 6, wherein if there is an edge from node a to node B, it indicates that if the corresponding slave B is already formed, the print head collides with the corresponding slave B when printing the slave B;

if one Slab contains an area where the overhang angle is too large to require a support structure, the corresponding node is provided with a corresponding label.

8. The method for co-dividing a body and a surface for manufacturing mixed materials according to claim 1, wherein the method is integratedAnd->Build up of a diagram->Comprises +.>Copy it as another graphThen is a picture->A label is given to each node in the list to indicate whether the node meets the accessibility constraint of the material addition and the material reduction and the support-free constraint in the current state;

the label is a through graphAnd (2) a picture->The mapping between the sampling points and the Slab is calculated by determining the mapping relation of the sampling points and the Slab in many-to-one space, if a sampling point is not reachable in the current state, the mapping is shown in the figure->And correspondingly setting the node label corresponding to the mapped Slab.

9. The method for co-segmentation of a body and a surface for manufacturing mixed increase and decrease materials according to claim 1, wherein the iterative combined graph is characterized in thatThe specific procedure for obtaining the corresponding block comprises for each graph established +.>And merging all leaf nodes with labels which are not corresponding to the set labels into new nodes with other labels, and iteratively merging the other nodes into the new nodes one by one through a greedy algorithm.

10. A body and surface co-segmentation system for manufacturing mixed increase and decrease materials is characterized by comprising:

the input module is used for acquiring a three-dimensional model;

the material reduction collision detection module is used for carrying out material reduction collision detection on the three-dimensional model, and establishing a graph so as to represent the accessibility relation among the nodes;

the segmentation module is used for establishing a beam search tree, determining corresponding nodes and ancestor nodes thereof according to the beam search tree, and combining the blocks represented by all the nodes to obtain a final model segmentation scheme;

the segmentation module specifically comprises a segmentation module and a segmentation module,

for searching the corresponding blocks of ancestor nodes, finding the blocks including the nodes of the constructed graph, deleting the nodes and connected edges from the graph, forming a new graphIs a module of (a);

for sampling a plurality of candidate additive directions, each direction down to a model level slice, performing collision detection of the printhead, creating a mapIs a module of (a);

for integration ofAnd->Build up of a diagram->Is a module of (a);

for iterative merging of graphsObtaining corresponding partitioned modules;

and a module for selecting blocks with highest scores through the evaluation function and adding the blocks into the beam search tree.