CN102915384A - Characteristic manufacturing behavior sequence construction method based on product geometric body - Google Patents
Characteristic manufacturing behavior sequence construction method based on product geometric body Download PDFInfo
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Abstract
The invention relates to a characteristic manufacturing behavior sequence construction method based on a product geometric body, which mainly comprises the following steps of: analyzing a manufacturing face adjacency graph of a product; extracting at least one sub characteristic step by step to form a static characteristic model of manufacturing behavior; analyzing each processing feeding direction of the product by taking the Boolean operation and a body modeling theory of the adjacency graph as basis; and concluding and optimizing the sub characteristics in the static characteristic model to form geometric body process sequence models which can be available for analysis until all processing feeding directions are analyzed, namely, determining a characteristic manufacturing behavior sequence which can be used for guiding product processing by matching the processing feeding directions with the corresponding process sequence models.
Description
Technical field
The present invention relates to a kind of feature model behavior sequence constructing technology, espespecially a kind of feature model behavior sequence construction method of how much bodies of product-based.
Background technology
The product model data refer to be the comprehensively set of all data elements of product of definition of the application in covering the whole life cycle of product, it is included as carries out design and analysis, manufacturing, test, check and product support and comprehensive data such as the parts of definition or member required how much, topology, tolerance, relation, attribute and performance, in addition, also may comprise some and process relevant data.Product model is for assigning production task, directly quality control, testing and carry out the product support function comprehensive information can be provided.
The early stage CAD of employing makes up product model more, but, development along with feature identification technique, progressively be converted into the product model of identifying based on feature by the CAD product model, and in numerous characteristic recognition methods, characteristic recognition method based on the attribute adjacent map is the most frequently used method, at the beginning of 21 century, the researcher is just arranged with the Constitution Elements of the relation between the limit as figure, realized take the characteristic recognition method of digraph as the basis, there is again afterwards the researcher further to introduce on its basis the judgement of the convex or concave attribute of edge, pointed out that rational data structure and modeling method can improve the performance of whole system.But in the attribute adjacent map that forms based on directed edge, a considerable amount of assemblage characteristics can not be by clear and definite identification, and only for axial workpiece preferably recognition effect is arranged, simultaneously, because the data structure of neither one standard is as support, the expression of feature recognition result is also relatively unordered.
And, at present the study general of feature identification all is extracted as the master with the static state of feature, form machinable sequence not accurate enough.
Therefore, how to propose the feature model behavior sequence construction method of geometry bodies in order a kind of and accurately product-based, just become present industry problem anxious to be overcome.
Summary of the invention
In view of the shortcoming of above-mentioned prior art, the object of the invention is to provide the feature model behavior sequence construction method of geometry bodies in order a kind of and accurately product-based.
For achieving the above object, the feature model behavior sequence construction method of how much bodies of product-based provided by the present invention comprises: 1) the undirected adjacent map of the machined surface of analytic product (Manufacturing Face Adjacency Graph, MFAG figure), extract one by one at least one subcharacter of product, to form the static nature model of manufacturing behavior; And 2) one by one analytic product each processing direction of feed, subcharacter in the static nature model is concluded optimization, formation can be for the process sequence model of how much bodies analyzing, until each processing direction of feed is all analyzed complete, namely cooperate its corresponding process sequence model to be defined as the feature model behavior sequence by this processing direction of feed respectively, and finish this construction method.
Wherein, this subcharacter comprises MFAG to be processed figure and to the processing datum of MFAG figure that should be to be processed, and MFAG figure to be processed carries out the MFAG figure that boolean's additive operation obtains by the MFAG figure with the MFAG figure before the product processing and how much bodies; Processing datum is to carry out boolean by the MFAG figure before MFAG figure to be processed is processed with product to intersect the geometric surface that computing obtains.
In addition, the quantity of this processing direction of feed is 6, is respectively X-axis forward, X-axis negative sense, Y-axis forward, Y-axis negative sense, Z axis forward and Z axis negative sense.
In more detail, above-mentioned steps 2) further comprise: 2-1) the MFAG figure before the processing of definition product is source figure, and gives record; 2-2) in 6 processing direction of feeds, select a processing direction of feed, and give record; 2-3) check this processing direction of feed, whether search is to existing processing datum on the geometric surface that should process direction of feed, if then by the boolean sum computing, this source figure and the MFAG figure of one of them subcharacter with this processing datum are merged, generate new MFAG figure, with as source figure, and record successively MFAG figure and formed this source figure of this subcharacter, and proceed to step 2-4), if not, then proceed to step 2-6); 2-4) continue search along this processing direction of feed, the processing datum that judges whether another subcharacter exists on the geometric surface that should process direction of feed, if, then proceed to step 2-5), if not, then by this processing direction of feed that records and successively the MFAG figure of the subcharacter through merge processing of record be defined as the process sequence model with formed source figure, and proceed to step 2-6); 2-5) by the boolean sum computing, the MFAG figure of this source figure and this subcharacter is merged, generates new MFAG and scheme, with as source figure, and the MFAG that records successively this subcharacter schemes and formed this source figure, and is back to step 2-4); 2-6) judge whether also to exist Unrecorded processing direction of feed, if then in Unrecorded processing direction of feed, select next processing direction of feed, and be back to step 2-3), if not, then proceed to step 2-7); And 2-7) is the feature model behavior sequence by respectively this process sequence model construction of determining successively, and finishes this construction method.
Below in conjunction with technique scheme, useful technique effect of the present invention is described.Than prior art, the present invention mainly is by the undirected adjacent map of the machined surface of analytic product, extract one by one at least one subcharacter of product, to form the static nature model of manufacturing behavior, then, Boolean calculation and Ontology Modeling with non-directed graph are theoretical as the basis, each processing direction of feed of analytic product, subcharacter in the static nature model is concluded optimization, formation can be for the process sequence model of how much bodies analyzing, until each processing direction of feed is all analyzed complete, but namely cooperate its corresponding process sequence model to be defined as the feature model behavior sequence of guide product processing by this processing direction of feed respectively, the present invention is by making up static nature model and this mode of being association of activity and inertia of process sequence model, with the orderly and feature model behavior sequence definition product.
Description of drawings
Fig. 1 is the operating process schematic diagram of feature model behavior sequence construction method of how much bodies of product-based of the present invention.
Fig. 2 is the schematic diagram of static nature model of the determined manufacturing behavior of feature model behavior sequence construction method of how much bodies of an embodiment how much bodies using product-based of the present invention.
Fig. 3 is the concrete operations schematic flow sheet of an embodiment of the step S20 of Fig. 1.
Fig. 4 uses the MFAG figure of the subcharacter that the feature model behavior sequence construction method of how much bodies of product-based of the present invention extracts for how much bodies of another embodiment.
Fig. 5 is the constructed feature model behavior sequence schematic diagram of feature model behavior sequence construction method that how much bodies among Fig. 4 are used how much bodies of product-based of the present invention.
Source figure when Fig. 6 is the X-axis forward for the processing direction of feed.
Source figure when Fig. 7 is the Z axis negative sense for the processing direction of feed.
Source figure when Fig. 8 is the Z axis forward for the processing direction of feed.
Fig. 9 is the feature model behavior sequence figure that process sequence model P1, P2, P3 make up.
[main element symbol description]
A, B1～B8, C source figure
The MFAG figure of F1～F9 subcharacter 1～subcharacter 9
M1～M14 geometric surface
P1, P2, P3 process sequence model
S10～S20, S200～S209 step
Embodiment
Below by specific instantiation explanation embodiments of the present invention, those of ordinary skill in the field can understand other advantages of the present invention and effect easily by content disclosed in the present specification.The present invention also can be implemented or be used by other different instantiations, and the every details in this instructions also can be based on different viewpoints and application, carries out various modifications and change under the spirit of the present invention not deviating from.
See also Fig. 1, it is the operating process schematic diagram of the feature model behavior sequence construction method of how much bodies of demonstration product-based of the present invention.Below namely cooperate Fig. 2 to 5 to describe the concrete operation step of feature model behavior sequence construction method of how much bodies of product-based of the present invention in detail.
As shown in Figure 1, execution in step S10 at first, the undirected adjacent map of the machined surface of analytic product (Manufacturing Face Adjacency Graph, MFAG figure), extract one by one at least one subcharacter of product, to form the static nature model of manufacturing behavior, wherein, this subcharacter comprises MFAG figure to be processed and to the processing datum of MFAG figure that should be to be processed.And this MFAG figure to be processed is by the MFAG figure after the figure of the MFAG before the product processing and the processing (namely as shown in Figure 2 how much bodies) being carried out the MFAG figure that boolean's additive operation obtains; This processing datum is to carry out boolean by the MFAG figure before MFAG figure to be processed is processed with product to intersect the geometric surface that computing obtains.As shown in Figure 3, by (being rectangular parallelepiped with the MFAG figure of how much bodies among Fig. 3 (be product processing after MFAG figure) with MFAG figure before the product processing, not shown) carry out boolean's additive operation, can obtain 2 subcharacters, respectively subcharacter 1 and subcharacter 2, subcharacter 1 is to comprise by face set { M7, M8, MFAG figure and processing datum M6 and M10 to be processed that M9} consists of, subcharacter 2 comprises by face set { M11, M12, M13, MFAG figure and processing datum M10 to be processed that M14} consists of, the static nature model that has namely obtained the behavior of making like this.Then, carry out step S20.
In step S20, one by one analytic product each processing direction of feed, subcharacter in the static nature model is concluded optimization, formation can be for the process sequence model of how much bodies analyzing, until that each processing direction of feed is all analyzed is complete, namely cooperate its corresponding process sequence model to be defined as the feature model behavior sequence by this processing direction of feed respectively.In more detail, the quantity of this processing direction of feed is 6, is respectively X-axis forward, X-axis negative sense, Y-axis forward, Y-axis negative sense, Z axis forward, Z axis negative sense.Particularly, as shown in Figure 3, the step of the subcharacter in the static nature model being concluded optimization is as follows:
Execution in step S200 at first, the MFAG figure (A as shown in Figure 5) before the processing of definition product is source figure, and gives record.Then, carry out step S201.
In step S201, in 6 processing direction of feeds, select a processing direction of feed, and give record.Then, carry out step S202.
In step S202, check this processing direction of feed, whether search to existing processing datum on the geometric surface that should process direction of feed, if, then proceed to step S203, if not, then proceed to step S207.
In step S203, by the boolean sum computing, this source figure and the MFAG figure of one of them subcharacter with this processing datum are merged, generates new MFAG figure, with as source figure, and the MFAG that records successively this subcharacter schemes and formed this source figure.Then, carry out step S204.
In step S204, continue search along this processing direction of feed, judge whether that the processing datum of another subcharacter exists on the geometric surface that should process direction of feed, if, then proceed to step S205, if not, then proceed to step S206.
In step S205, by the boolean sum computing, the MFAG of this source figure and this subcharacter figure is merged, generates new MFAG figure, with as source figure, and record successively MFAG figure and formed this source figure of this subcharacter, follow, be back to step S204.
In step S206, by this processing direction of feed that records and successively the MFAG figure of the subcharacter through merge processing of record be defined as the process sequence model with formed source figure.Then, carry out step S207.
In step S207, judge whether also to exist Unrecorded processing direction of feed, if, then proceed to step S208, if not, then proceed to step S209.
In step S208, in Unrecorded processing direction of feed, select next processing direction of feed, then, be back to step S202.
In step S209, be the feature model behavior sequence by respectively this process sequence model construction of determining successively, and finish this feature model behavior sequence building process.
Use for more detailed understanding product-based of the present invention how much bodies feature model behavior sequence construction method how realization character make the structure of behavior sequence, below how much bodies of product in (a) shown in Figure 4 as example and cooperate Fig. 1, Fig. 3 and Fig. 5 to describe.
At first carry out above-mentioned steps S10, can from how much bodies shown in Figure 4, extract the MFAG figure (F1 shown in (b) among Fig. 4～F9) of 9 subcharacters, and the benchmark machined surface of subcharacter 1 is M0 (being the geometric surface of corresponding X-axis forward), subcharacter 2 to the benchmark machined surface of subcharacter 5 is M1 (being the geometric surface of corresponding Z axis negative sense), the benchmark machined surface of subcharacter 6 is geometric surfaces of the corresponding Z axis negative sense take source figure B5 (being detailed later) as body, the benchmark machined surface of subcharacter 7 is geometric surfaces of the corresponding Z axis negative sense take source figure B6 (being detailed later) as body, the benchmark machined surface of subcharacter 8 is geometric surfaces of the corresponding Z axis negative sense take source figure B7 (being detailed later) as body, the benchmark machined surface of subcharacter 9 is M3 (being the geometric surface of corresponding Z axis forward), then carry out above-mentioned steps S200, MFAG figure before the processing of definition product is source figure A, execution in step S201 afterwards, in the present embodiment, select the X-axis forward to process direction of feed (but not as limit as first, in other embodiments, also can select any in other 5 the Unrecorded processing direction of feeds), then execution in step S202, check this X-axis forward, search having processing datum on the geometric surface M0 of X-axis forward, then, execution in step S203, pass through Boolean calculation, source figure A and the MFAG figure F1 of the subcharacter 1 with this processing datum are merged, generate new MFAG figure, with as source figure B1, and the MFAG that records successively this subcharacter 1 schemes F1 and formed source figure B1, then, execution in step S204, continue search along the X-axis forward, find no the processing datum of another subcharacter on geometric surface M0, execution in step S206 then is by this processing direction of feed (X-axis forward) that records, and the MFAG figure through merging the subcharacter of processing of record is defined as process sequence model P1 with formed source figure (as shown in Figure 6) successively.
Afterwards, also there is Unrecorded processing direction of feed by step S207 judgement, it is respectively the X-axis negative sense, the Y-axis forward, the Y-axis negative sense, Z axis forward and Z axis negative sense, then proceed to step S208, in Unrecorded processing direction of feed, select next processing direction of feed, in the present embodiment, select the X-axis negative sense (but not as limit, in other embodiments, also can select any in other 4 the Unrecorded processing direction of feeds), then return step S202, there is not processing datum in corresponding X-axis negative sense on inspection, then proceed to step S207, judge and also have Unrecorded processing direction of feed, it is respectively the Y-axis forward, the Y-axis negative sense, Z axis forward and Z axis negative sense, afterwards, proceed to step S208, in Unrecorded processing direction of feed, select next processing direction of feed, in the present embodiment, select the Y-axis forward (but not as limit, in other embodiments, also can select any in other 3 the Unrecorded processing direction of feeds), then repeat above-mentioned steps, judge that there is not processing datum in corresponding Y-axis forward and also has Unrecorded processing direction of feed, it is respectively the Y-axis negative sense, Z axis forward and Z axis negative sense, afterwards, proceed to step S208, in Unrecorded processing direction of feed, select next processing direction of feed, in the present embodiment, select the Y-axis negative sense (but not as limit, in other embodiments, also can select any in other 2 the Unrecorded processing direction of feeds), repeating afterwards above-mentioned steps, judge that there is not processing datum in corresponding Y-axis negative sense and also has Unrecorded processing direction of feed, is respectively Z axis forward and Z axis negative sense, then, proceed to step S208.
In step S208, in Unrecorded processing direction of feed, select next processing direction of feed, in the present embodiment, select the Z axis negative sense (but not as limit, in other embodiments, also can select the Z axis forward), then return step S202, there is processing datum on the geometric surface M1 of corresponding Z axis negative sense on inspection, then proceed to step S203, pass through Boolean calculation, source figure B1 and the MFAG figure F2 of the subcharacter 2 with this processing datum are merged, generate new MFAG figure, with as source figure B2, and the MFAG that records successively this subcharacter 2 schemes F2 and formed source figure B2, then, execution in step S204, continue search along the Z axis negative sense, judge that the processing datum that another subcharacter 3 is arranged exists on should the geometric surface M1 of Z axis negative sense, then, proceed to step S205, by the boolean sum computing, the MFAG figure F3 of this source figure B2 and this subcharacter 3 is merged, generate new MFAG figure, with as source figure B3, and the MFAG that records successively this subcharacter 3 schemes F3 and formed this source figure B3, then, be back to step S204, continue search along the Z axis negative sense, repeat above-mentioned steps, can successively search out the processing datum that still has subcharacter 4 to 8 exists on should the geometric surface of Z axis negative sense, then repeat above-mentioned steps, can record successively MFAG figure and the formed source figure of subcharacter 4 to 8, respectively (F4-B4), (F5-B5), (F6-B6), (F7-B7) and (F8-B8), at this moment, proceeded to step S204, continue search along the Z axis negative sense, the reference field of not finding another subcharacter except subcharacter 2 to 8 exists on the geometric surface of corresponding Z axis negative sense, then proceed to step S206, by this processing direction of feed (Z axis negative sense) that records, and the MFAG figure through merging the subcharacter of processing of record is defined as process sequence model P2 with formed source figure (as shown in Figure 7) successively.
Afterwards, also there is Unrecorded processing direction of feed by step S207 judgement, it is the Z axis forward, then proceed to step S208, in Unrecorded processing direction of feed (Z axis forward), select next processing direction of feed, in the present embodiment, can only select the Z axis forward, then return step S202, check this Z axis forward, search having processing datum on the geometric surface M3 of Z axis forward, then, execution in step S203, pass through Boolean calculation, source figure B8 and the MFAG figure F9 of the subcharacter 9 with this processing datum are merged, generate new MFAG figure, with as source figure C, and record successively MFAG figure F9 and the formed source figure C of this subcharacter 9, then, execution in step S204 continues search along the Z axis forward, finds no the processing datum of another subcharacter on geometric surface M3, execution in step S206 then, by this processing direction of feed (Z axis forward) that records, and the MFAG figure through merging the subcharacter of processing of record is defined as process sequence model P3 with formed source figure (as shown in Figure 8) successively, and in the present embodiment, source figure C is the MFAG figure of how much final bodies.
Afterwards, there is not Unrecorded processing direction of feed by step S207 judgement, then proceed to step S209, namely be configured to feature model behavior sequence (as shown in Figure 9) by respectively this process sequence model P1, P2, the P3 that determine successively, structural representation corresponding shown in Figure 5.
In sum, the present invention mainly starts with from defining how much Ontological concepts of complete product, by the undirected adjacent map of the machined surface of analytic product, set up the static nature model of how much bodies of product, then one by one analytic product each processing direction of feed, subcharacter in the static nature model is concluded optimization, and formation can be for the process sequence model of how much bodies analyzing, but and has finally formed the feature model behavior sequence of guide product processing.Use the present invention, the static state that not merely is confined to the feature of product is extracted (being the static nature model), also cooperate the processing direction of feed to analyze each subcharacter, to form Dynamic Manufacturing behavior (being the process sequence model), so, being association of activity and inertia can be in order and the feature model behavior sequence of definition product.
Above-described embodiment is illustrative principle of the present invention and effect thereof only, but not is used for restriction the present invention.Any person of an ordinary skill in the technical field all can be under spirit of the present invention and category, and above-described embodiment is modified and changed.Therefore, the scope of the present invention should be listed such as the scope of appending claims.
Claims (6)
1. the feature model behavior sequence construction method of how much bodies of a product-based is characterized in that, described construction method comprises:
1) the undirected adjacent map of the machined surface of analytic product (Manufacturing Face Adjacency Graph, MFAG figure) extracts at least one subcharacter of product, one by one to form the static nature model of manufacturing behavior; And
2) one by one analytic product each processing direction of feed, subcharacter in the static nature model is concluded optimization, formation can be for the process sequence model of how much bodies analyzing, until each processing direction of feed is all analyzed complete, namely cooperate its corresponding process sequence model to be defined as the feature model behavior sequence by this processing direction of feed respectively, and finish this construction method.
2. the feature model behavior sequence construction method of how much bodies of product-based according to claim 1 is characterized in that, described subcharacter comprises the processing datum of MFAG figure to be processed and corresponding described MFAG figure to be processed.
3. the feature model behavior sequence construction method of how much bodies of product-based according to claim 2, it is characterized in that, described MFAG figure to be processed carries out the MFAG figure that boolean's additive operation obtains by the MFAG figure with the MFAG figure before the product processing and how much bodies.
4. the feature model behavior sequence construction method of how much bodies of product-based according to claim 2, it is characterized in that, described processing datum is to carry out boolean by the MFAG figure before MFAG figure to be processed is processed with product to intersect the geometric surface that computing obtains.
5. the feature model behavior sequence construction method of how much bodies of product-based according to claim 1, it is characterized in that, the quantity of described processing direction of feed is 6, is respectively X-axis forward, X-axis negative sense, Y-axis forward, Y-axis negative sense, Z axis forward and Z axis negative sense.
6. the feature model behavior sequence construction method of how much bodies of product-based according to claim 5 is characterized in that described step 2) further comprise:
2-1) the MFAG figure before the processing of definition product is source figure, and gives record;
2-2) in 6 processing direction of feeds, select a processing direction of feed, and give record;
2-3) check this processing direction of feed, whether search is to existing processing datum on the geometric surface that should process direction of feed, if then by the boolean sum computing, described source figure and the MFAG figure of one of them subcharacter with this processing datum are merged, generate new MFAG figure, with as source figure, and record successively MFAG figure and formed this source figure of this subcharacter, and proceed to step 2-4), if not, then proceed to step 2-6);
2-4) continue search along this processing direction of feed, the processing datum that judges whether another subcharacter exists on the geometric surface that should process direction of feed, if, then proceed to step 2-5), if not, then by this processing direction of feed that records and successively the MFAG figure of the subcharacter through merge processing of record be defined as the process sequence model with formed source figure, and proceed to step 2-6);
2-5) by the boolean sum computing, the MFAG figure of described source figure and this subcharacter is merged, generates new MFAG and scheme, with as source figure, and the MFAG that records successively this subcharacter schemes and formed this source figure, and is back to step 2-4);
2-6) judge whether also to exist Unrecorded processing direction of feed, if then in Unrecorded processing direction of feed, select next processing direction of feed, and be back to step 2-3), if not, then proceed to step 2-7); And
Be the feature model behavior sequence by respectively this process sequence model construction of determining successively 2-7), and finish this construction method.
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| US20070067056A1 (en) * | 2005-07-06 | 2007-03-22 | Kazumi Nishinohara | Method for optimizing an industrial product, system for optimizing an industrial product and method for manufacturing an industrial product |
| CN101216706A (en) * | 2007-12-28 | 2008-07-09 | 西安交通大学 | Tool bit effective machining area calculation based on three scan line and cutter path creation method |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070067056A1 (en) * | 2005-07-06 | 2007-03-22 | Kazumi Nishinohara | Method for optimizing an industrial product, system for optimizing an industrial product and method for manufacturing an industrial product |
| CN101216706A (en) * | 2007-12-28 | 2008-07-09 | 西安交通大学 | Tool bit effective machining area calculation based on three scan line and cutter path creation method |
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| 盛精: "基于切削仿真的刀具-工件的参数化三维建模", 《武汉理工大学学报》 * |
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