CN108021683A - A kind of scale model retrieval implementation method based on three-dimensional labeling - Google Patents
A kind of scale model retrieval implementation method based on three-dimensional labeling Download PDFInfo
- Publication number
- CN108021683A CN108021683A CN201711310079.8A CN201711310079A CN108021683A CN 108021683 A CN108021683 A CN 108021683A CN 201711310079 A CN201711310079 A CN 201711310079A CN 108021683 A CN108021683 A CN 108021683A
- Authority
- CN
- China
- Prior art keywords
- msub
- mrow
- model
- dimension
- msup
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/5866—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using information manually generated, e.g. tags, keywords, comments, manually generated location and time information
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T19/00—Manipulating 3D models or images for computer graphics
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2219/00—Indexing scheme for manipulating 3D models or images for computer graphics
- G06T2219/012—Dimensioning, tolerancing
Abstract
The present invention provides a kind of scale model retrieval implementation method based on three-dimensional labeling.This method realizes the abstraction function of threedimensional model markup information by Three-dimensional CAD Software, will extract size marking information, forms threedimensional model mark property data base.The size marking information of current threedimensional model is extracted during the threedimensional model for needing similar to search, then the dimension information of extraction is handled, Similarity measures is carried out with moulded dimension classification, counting criteria value, obtains the similarity of current threedimensional model.Then according to the similarity being calculated, retrieval returns and the most similar one or more three-dimensional modeling datas of "current" model similarity, forms similar data set.The dimension information for concentrating each threedimensional model with set of metadata of similar data carries out secondary Similarity measures, re-starts similitude sequence, and combines light weighed model, and result is presented in a manner of visual.The present invention is obviously improved work efficiency, lifts designed capacity.
Description
Technical field
The present invention relates to Digitized Manufacturing Technology field, and in particular to a kind of scale model retrieval based on three-dimensional labeling is real
Existing method.
Background technology
With the development of model three-dimensional development work, more and more type products are using three dimensional design and three-dimensional manufacture skill
Art.But on the whole, in the technological design and manufacturing process of product, has the reuse of information not enough in threedimensional model
Fully, it is not implemented and efficiently uses existing three dimensional design information in model, reduces the manual operations in Process Planning, lifting
The target of technological design efficiency and quality.
Technological design based on model, main is also based on the technological design of inheritance.Technologist generally requires to look into
Whether had similar product, carried out the technological design of similar products if looking for, then by using for reference existing technological design data,
Complete the technological design of new spare part.
But under the conditions of original, do not possess efficient lookup and retrieve the computer technology means of similar products.Mainly
By the personal experience of technologist, or based on being understood to other experienced persons, work efficiency is low, actual
Effect is difficult to be guaranteed.
For this, if it is possible to realize the Product Similarity search method based on model, then can significantly lifting process design
During retrieval and reuse to data with existing.
The content of the invention
It is an object of the invention to provide a kind of scale model based on three-dimensional labeling to retrieve implementation method, it is possible to achieve pin
To specified threedimensional model, in other existing 3 d model libraries, automatically retrieval is to similar threedimensional model, according to similarity
It is ranked up and shows.
Realize the technical solution of the object of the invention：A kind of scale model retrieval implementation method based on three-dimensional labeling, the party
Method comprises the following steps that：
(1) manufacturing sector receives threedimensional model (a.1) of the design part with size marking, and mould is realized in PDM systems
The management of type；
(2) by PDM system interfaces, based on the receiving time section of threedimensional model (a.1), read with incremental mode batch
Threedimensional model (a.1) in PDM systems, establishes threedimensional model copy (b.1)；
(3) by being integrated with Three-dimensional CAD Software, three-dimensional CAD tool software is started, traversal opens local three-dimensional model successively
Copy (b.1), travels through three-dimensional labeling information (c.1) all on each threedimensional model copy (b.1.n)；Meanwhile made with figure number
For unique mark, corresponding three-dimensional light weighed model is generated；
(4) according to size marking information (c.1) feature, by size marking information (c.1) according to linear dimension (c.1.1),
Diameter dimension (c.1.2), radius size (c.1.3), Angular Dimension (c.1.4) carry out differential counting；
According to product threedimensional model feature, according to linear dimension, diameter dimension, radius size classification setting small size numerical value
Size threshold values F1、F2、F3；When then according still further to linear dimension, diameter dimension, radius size differential counting, exclude or filter out
Less than or equal to size threshold values F1、F2、F3Data；
(5) linear size, extracts the label direction of linear dimension, and according to coordinate system X, Y, Z, other 4 directions,
Again (c.1.1) linear dimension is classified and counted；
(6) by the X-direction linear dimension (c.1.1.1), Y-direction linear dimension (c.1.1.2), the linear ruler of Z-direction of formation
Very little (c.1.1.3), other dimension linear sizes (c.1.1.4), diameter dimension (c.1.2), radius size (c.1.3), bevel protractor
Very little (c.1.4) classification and enumeration data, according to following formula first order calculation index similarity S1：
Wherein, the standard value that C is threedimensional model classification, counts；
C1Counted for X-direction linear dimension；
C2Counted for Y-direction linear dimension；
C3Counted for Z-direction linear dimension；
C4Counted for other dimension linear sizes；
C5Counted for diameter dimension；
C6Counted for radius size；
C7Counted for Angular Dimension；
(7) according to three-dimensional model diagram code name, X-direction linear dimension, Y-direction linear dimension, Z-direction linear dimension, other
Dimension linear size, diameter dimension, radius size, Angular Dimension, aided linear size, auxiliary diameter dimension, auxiliary radius ruler
13 very little, morpheme size, roughness fields establish threedimensional model mark characteristic statistics database, and respectively by three-dimensional model diagram generation
Number, and X-direction linear dimension, Y-direction linear dimension, Z-direction linear dimension, other dimension linear sizes, diameter dimension, half
Footpath size, Angular Dimension enumeration data, store in the database；
Above through size threshold values F1、F2、F3The dimension data filtered out, respectively according to aided linear size, auxiliary diameter ruler
Very little, auxiliary radius size counts, and is stored in the aided linear size of the database, aids in diameter dimension, auxiliary 3 words of radius size
Section；
Morpheme size, roughness are counted again, are stored in morpheme size, the roughness attribute field of the database；
The level-one similarity S that will be calculated1, it is saved in the similarity field of the database；
(8) threedimensional model (d.1) of similar to search is needed by three dimensional CAD system opening in client, and is read current
The size marking information (f.1) of model；
(9) according to the C values and threshold values F of threedimensional model mark characteristic statistics database setting1、F2、F3, according to current three-dimensional
Size marking information (f.1) the X-direction linear dimension of model, Y-direction linear dimension, Z-direction linear dimension, other dimension linears
Size, diameter dimension, radius size, Angular Dimension, current threedimensional model dimension information is classified, is counted, and under
The formula in face calculates the similarity S of current threedimensional model；
Wherein, Cs1Counted for "current" model X-direction linear dimension；
Cs2Counted for "current" model Y-direction linear dimension；
Cs3Counted for "current" model Z-direction linear dimension；
Cs4For "current" model, other dimension linear sizes count；
Cs5Counted for "current" model diameter dimension；
Cs6Counted for "current" model radius size；
Cs7Counted for "current" model Angular Dimension；
(10) according to the similarity factor F of setting, similar region S-S* (1-F), S+S* (1-F) are calculated, and obtain three-dimensional mould
Level-one similarity S in type mark characteristic statistics database1One or more three-dimensional modeling datas in this section, form similar
Data set；
(11) three-dimensional modeling data that set of metadata of similar data is concentrated is traveled through, and similar data set is calculated successively according to following formula
In each three-dimensional modeling data two level similarity S2；
Wherein：
Cs1Counted for "current" model X-direction linear dimension；
Cs2Counted for "current" model Y-direction linear dimension；
Cs3Counted for "current" model Z-direction linear dimension；
Cs4For "current" model, other dimension linear sizes count；
Cs5Counted for "current" model diameter dimension；
Cs6Counted for "current" model radius size；
Cs7Counted for "current" model Angular Dimension；
Cs8Counted for "current" model aided linear size；
Cs9Diameter dimension is aided in count for "current" model；
Cs10Radius size is aided in count for "current" model；
Cs11Counted for "current" model morpheme size；
Cs12Counted for "current" model roughness；
Ci1I-th three-dimensional modeling data X-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci2I-th three-dimensional modeling data Y-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci3I-th three-dimensional modeling data Z-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci4I-th three-dimensional modeling data other dimension linear sizes counting is concentrated for set of metadata of similar data；
Ci5I-th three-dimensional modeling data diameter dimension is concentrated to count for set of metadata of similar data；
Ci6I-th three-dimensional modeling data radius size is concentrated to count for set of metadata of similar data；
Ci7I-th three-dimensional modeling data Angular Dimension is concentrated to count for set of metadata of similar data；
Ci8I-th three-dimensional modeling data aided linear size is concentrated to count for set of metadata of similar data；
Ci9I-th three-dimensional modeling data is concentrated to aid in diameter dimension to count for set of metadata of similar data；
Ci10I-th three-dimensional modeling data is concentrated to aid in radius size to count for set of metadata of similar data；
Ci11I-th three-dimensional modeling data morpheme size is concentrated to count for set of metadata of similar data；
Ci12I-th three-dimensional modeling data roughness is concentrated to count for set of metadata of similar data；
(12) according to the similarity S being calculated2, set of metadata of similar data concentrated into three-dimensional modeling data, by similarity S2By greatly to
Small rearrangement, is presented the three-dimensional modeling data and similarity S of set of metadata of similar data concentration in a manner of list2；
By associated lightweight threedimensional model, the geometry of threedimensional model can be directly viewable, realizes and is based on light weight
Change model, similarity S2Model similarity integrated decision-making；Associated at the same time by figure number unique mark, corresponding lightweight is presented
Model, realizes the visualization of result.
A kind of scale model retrieval implementation method based on three-dimensional labeling as described above, in its step (4), size threshold values
F1、F2、F3Setting can be set in 3 d model library, can also be by being calculated；If by the way of calculating,
Need by the percentage of classification setting threshold values first in 3 d model library, then by obtaining linear dimension, diameter dimension, half
The full-size numerical value each classified in the size of footpath, corresponding threshold values data are obtained after being multiplied by percentage.
A kind of scale model retrieval implementation method based on three-dimensional labeling as described above, in its step (4), size threshold values
F1、F2、F3Setting, generally can use retain decimal point after three bit digitals.
A kind of scale model retrieval implementation method based on three-dimensional labeling as described above is general to set in its step (6)
C=10, can also be adjusted according to product model feature, but be directed to same 3 d model library, should set identical numerical value.
A kind of scale model retrieval implementation method based on three-dimensional labeling as described above, in its step (12), passes through phase
Associated like threedimensional model and technological design data, process knowledge, realize that technological design data, process knowledge are based on threedimensional model
Knowledge push, realize Knowledge based engineering three-dimensional process design.
A kind of scale model retrieval implementation method based on three-dimensional labeling of the present invention, this method combination three-dimensional CAD
Tool software, extracts the size marking information on threedimensional model, is then based on size marking information, realizes threedimensional model similarity
Calculating and three-dimensional model search, its implement step be：
(1) Three Dimensional Design Model；
(2) computation model similarity；
(3) scale model is retrieved；
Wherein, step (1) includes：Manufacturing sector receives threedimensional model (a.1) of the design department with size marking,
The management of threedimensional model is realized in PDM systems, forms 3 d model library；
Wherein, step (2) includes：
(2.1) by PDM system interfaces, based on the receiving time section of threedimensional model (a.1), read with incremental mode batch
The threedimensional model (a.1) in PDM systems is taken, establishes the local replica (b.1) of threedimensional model；
(2.2) by being integrated with Three-dimensional CAD Software, start three-dimensional CAD tool software, travel through successively, open local three-dimensional
Model copy (b.1), travels through, obtains three-dimensional dimension markup information (c.1) all on each model (b.1.n), meanwhile, to scheme
Number it is unique mark, generates corresponding three-dimensional light weighed model；
(2.3) according to the feature of size marking information (c.1), by size marking information (c.1) according to linear dimension
(c.1.1), (c.1.4) diameter dimension (c.1.2), radius size (c.1.3), Angular Dimension are classified, are counted；
, can be three-dimensional according to product to avoid the less size of some numerical value from interfering the similitude of threedimensional model entirety
Model feature, the size threshold values F of small size numerical value is set according to linear dimension, diameter dimension, radius size classification1、F2、F3；So
When afterwards according still further to linear dimension, diameter dimension, radius size classification, counting, exclude or filter out less than or equal to size threshold values F1、
F2、F3Data；
(2.4) linear size, extracts the label direction of linear dimension, and according to coordinate system X, Y, Z, other 4 sides
To, and again (c.1.1) linear dimension is classified and counted；
(2.5) it is the X-direction linear dimension (c.1.1.1), Y-direction linear dimension (c.1.1.2), Z-direction of formation is linear
Size (c.1.1.3), other dimension linear sizes (c.1.1.4), diameter dimension (c.1.2), radius size (c.1.3), angle
Size (c.1.4) is classified and enumeration data, according to following formula first order calculation similarity S1：
Wherein, the standard value that C is threedimensional model classification, counts；
C1Counted for X-direction linear dimension；
C2Counted for Y-direction linear dimension；
C3Counted for Z-direction linear dimension；
C4Counted for other dimension linear sizes；
C5Counted for diameter dimension；
C6Counted for radius size；
C7Counted for Angular Dimension；
(2.6) according to three-dimensional model diagram code name, X-direction linear dimension, Y-direction linear dimension, Z-direction linear dimension, its
His direction linear dimension, diameter dimension, radius size, Angular Dimension, aided linear size, auxiliary diameter dimension, auxiliary radius
13 size, morpheme size, roughness fields establish three-dimensional modeling data storehouse, and respectively by three-dimensional model diagram code name, and X side
To linear dimension, Y-direction linear dimension, Z-direction linear dimension, other dimension linear size, diameter dimension, radius size, angles
Size enumeration data is spent, is stored in the three-dimensional modeling data storehouse；
Above through size threshold values F1、F2、F3The dimension data filtered out, respectively according to aided linear size, auxiliary diameter ruler
Very little, auxiliary radius size counts, and is stored in the aided linear size of the three-dimensional modeling data storehouse, aids in diameter dimension, auxiliary radius
3 fields of size；Morpheme size, roughness are counted again, are stored in morpheme size, the roughness attribute of the three-dimensional modeling data storehouse
Field；The level-one similarity S that will be calculated1, it is saved in the similarity field of the three-dimensional modeling data storehouse；
Wherein, step (3) includes：
(3.1) threedimensional model (d.1) of similar to search is needed by three-dimensional CAD tool open in client, is then passed through
Integrated functionality opens three-dimensional search function module, reads the size marking information (f.1) of "current" model automatically by the module；
(3.2) according to the C values and size threshold values F set in three-dimensional modeling data storehouse1、F2、F3, according to current threedimensional model
Size marking information (f.1) X-direction linear dimension, Y-direction linear dimension, Z-direction linear dimension, other dimension linear sizes,
Diameter dimension, radius size, Angular Dimension, current threedimensional model dimension information is classified, is counted, and according to following public affairs
Formula calculates the similarity S of current threedimensional model；
Wherein：
Cs1Counted for "current" model X-direction linear dimension；
Cs2Counted for "current" model Y-direction linear dimension；
Cs3Counted for "current" model Z-direction linear dimension；
Cs4For "current" model, other dimension linear sizes count；
Cs5Counted for "current" model diameter dimension；
Cs6Counted for "current" model radius size；
Cs7Counted for "current" model Angular Dimension；
(3.3) in three-dimensional search function module, the current threedimensional model similarity S being calculated is called；According to three-dimensional mould
The coefficient of similarity F set in type database, calculates similar region S-S* (1-F), S+S* (1-F), and obtains 3 d model library
Middle level-one similarity S1One or more three-dimensional modeling datas in this section, form similar data set；
(3.4) three-dimensional modeling data concentrated in three-dimensional search function module, traversal set of metadata of similar data, and according to following public affairs
Formula calculates the two level similarity S that set of metadata of similar data concentrates each three-dimensional modeling data successively2；
Wherein：
Cs1Counted for "current" model X-direction linear dimension；
Cs2Counted for "current" model Y-direction linear dimension；
Cs3Counted for "current" model Z-direction linear dimension；
Cs4For "current" model, other dimension linear sizes count；
Cs5Counted for "current" model diameter dimension；
Cs6Counted for "current" model radius size；
Cs7Counted for "current" model Angular Dimension；
Cs8Counted for "current" model aided linear size；
Cs9Diameter dimension is aided in count for "current" model；
Cs10Radius size is aided in count for "current" model；
Cs11Counted for "current" model morpheme size；
Cs12Counted for "current" model roughness；
Ci1I-th three-dimensional modeling data X-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci2I-th three-dimensional modeling data Y-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci3I-th three-dimensional modeling data Z-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci4I-th three-dimensional modeling data other dimension linear sizes counting is concentrated for set of metadata of similar data；
Ci5I-th three-dimensional modeling data diameter dimension is concentrated to count for set of metadata of similar data；
Ci6I-th three-dimensional modeling data radius size is concentrated to count for set of metadata of similar data；
Ci7I-th three-dimensional modeling data Angular Dimension is concentrated to count for set of metadata of similar data；
Ci8I-th three-dimensional modeling data aided linear size is concentrated to count for set of metadata of similar data；
Ci9I-th three-dimensional modeling data is concentrated to aid in diameter dimension to count for set of metadata of similar data；
Ci10I-th three-dimensional modeling data is concentrated to aid in radius size to count for set of metadata of similar data；
Ci11I-th three-dimensional modeling data morpheme size is concentrated to count for set of metadata of similar data；
Ci12I-th three-dimensional modeling data roughness is concentrated to count for set of metadata of similar data；
(3.5) according to the similarity S being calculated2, set of metadata of similar data concentrated into three-dimensional modeling data, by similarity S2By big
To small rearrangement, three-dimensional modeling data and similarity S that set of metadata of similar data is concentrated are presented in a manner of list2, by associated
Lightweight threedimensional model, can be directly viewable the geometry of threedimensional model, realize the visualization of retrieval result, realize based on light
Quantitative model, similarity S2Model similarity integrated decision-making.
A kind of scale model retrieval implementation method based on three-dimensional labeling as described above, in its step (3.2), size valve
Value F1、F2、F3Setting can be set in 3 d model library, can also be by being calculated.
A kind of scale model retrieval implementation method based on three-dimensional labeling as described above, in its step (3.2), size valve
Value F1、F2、F3Setting, generally can use retain decimal point after three bit digitals.
A kind of scale model retrieval implementation method based on three-dimensional labeling as described above, in its step (2.5), generally sets
C=10 is put, can also be adjusted according to product model feature, but is directed to same 3 d model library, identical number should be set
Value.
A kind of scale model retrieval implementation method based on three-dimensional labeling as described above, in its step (3.5), passes through phase
Associated like threedimensional model and technological design data, process knowledge, realize that technological design data, process knowledge are based on threedimensional model
Knowledge push, realize Knowledge based engineering three-dimensional process design.
Effect of the invention is that：A kind of scale model retrieval implementation method based on three-dimensional labeling of the present invention,
Markup information in automatic identification and extraction model, avoids manual operation, is obviously improved work efficiency.It believes the mark of extraction
The automatic classification of breath, and by advance similarity measure, significantly lift recall precision.By setting size threshold values, similarity
The mode of coefficient, carries out secondary similarity measure so that threedimensional model similitude is more accurate.By similar threedimensional model,
Association pushes corresponding process data, process knowledge, the efficiency and quality of lifting process design.The present invention can be based in development
During three-dimensional technological design work, can fast positioning is existing, similar product threedimensional model, and by product threedimensional model with
The incidence relation of process program, technological procedure, process knowledge etc., pushes and reuses existing process data and process knowledge, real
Now Knowledge based engineering Celerity process planning, the process design ability of lifting process personnel, realize accumulation and the knowledge of process knowledge
Reuse.
Brief description of the drawings
A kind of Fig. 1 scale model retrieval implementation method schematic diagrames based on three-dimensional labeling of the present invention.
Embodiment
A kind of scale model based on three-dimensional labeling of the present invention is retrieved with specific embodiment below in conjunction with the accompanying drawings
Implementation method is further described.
Embodiment 1
A kind of scale model retrieval implementation method based on three-dimensional labeling of the present invention, it is comprised the following steps that：
(1) manufacturing sector receives threedimensional model (a.1) of the design part with size marking, and mould is realized in PDM systems
The management of type；
(2) by PDM system interfaces, based on the receiving time section of threedimensional model (a.1), read with incremental mode batch
Threedimensional model (a.1) in PDM systems, establishes threedimensional model copy (b.1)；
(3) by being integrated with Three-dimensional CAD Software, three-dimensional CAD tool software is started, traversal opens local three-dimensional model successively
Copy (b.1), travels through three-dimensional labeling information (c.1) all on each threedimensional model copy (b.1.n)；Meanwhile made with figure number
For unique mark, corresponding three-dimensional light weighed model is generated；
(4) according to size marking information (c.1) feature, by size marking information (c.1) according to linear dimension (c.1.1),
Diameter dimension (c.1.2), radius size (c.1.3), Angular Dimension (c.1.4) carry out differential counting；
According to product threedimensional model feature, according to linear dimension, diameter dimension, radius size classification setting small size numerical value
Size threshold values F1、F2、F3；When then according still further to linear dimension, diameter dimension, radius size differential counting, exclude or filter out
Less than or equal to size threshold values F1、F2、F3Data；
Size threshold values F1、F2、F3Setting can be set in 3 d model library, can also be by being calculated；If
The percentage of classification setting threshold values is pressed by the way of calculating, it is necessary to first in 3 d model library, it is then linear by obtaining
The full-size numerical value each classified in size, diameter dimension, radius size, corresponding threshold values data are obtained after being multiplied by percentage
Size threshold values F1、F2、F3Setting, generally can use retain decimal point after three bit digitals；
(5) linear size, extracts the label direction of linear dimension, and according to coordinate system X, Y, Z, other 4 directions,
Again (c.1.1) linear dimension is classified and counted；
(6) by the X-direction linear dimension (c.1.1.1), Y-direction linear dimension (c.1.1.2), the linear ruler of Z-direction of formation
Very little (c.1.1.3), other dimension linear sizes (c.1.1.4), diameter dimension (c.1.2), radius size (c.1.3), bevel protractor
Very little (c.1.4) classification and enumeration data, according to following formula first order calculation index similarity S1：
Wherein, the standard value that C is threedimensional model classification, counts；It is general that C=10 is set, can also be special according to product model
Point is adjusted, but is directed to same 3 d model library, should set identical numerical value；
C1Counted for X-direction linear dimension；
C2Counted for Y-direction linear dimension；
C3Counted for Z-direction linear dimension；
C4Counted for other dimension linear sizes；
C5Counted for diameter dimension；
C6Counted for radius size；
C7Counted for Angular Dimension；
(7) according to three-dimensional model diagram code name, X-direction linear dimension, Y-direction linear dimension, Z-direction linear dimension, other
Dimension linear size, diameter dimension, radius size, Angular Dimension, aided linear size, auxiliary diameter dimension, auxiliary radius ruler
13 very little, morpheme size, roughness fields establish threedimensional model mark characteristic statistics database, and respectively by three-dimensional model diagram generation
Number, and X-direction linear dimension, Y-direction linear dimension, Z-direction linear dimension, other dimension linear sizes, diameter dimension, half
Footpath size, Angular Dimension enumeration data, store in the database；
Above through size threshold values F1、F2、F3The dimension data filtered out, respectively according to aided linear size, auxiliary diameter ruler
Very little, auxiliary radius size counts, and is stored in the aided linear size of the database, aids in diameter dimension, auxiliary 3 words of radius size
Section；
Morpheme size, roughness are counted again, are stored in morpheme size, the roughness attribute field of the database；
The level-one similarity S that will be calculated1, it is saved in the similarity field of the database；
(8) threedimensional model (d.1) of similar to search is needed by three dimensional CAD system opening in client, and is read current
The size marking information (f.1) of model；
(9) according to the C values and threshold values F of threedimensional model mark characteristic statistics database setting1、F2、F3, according to current three-dimensional
Size marking information (f.1) the X-direction linear dimension of model, Y-direction linear dimension, Z-direction linear dimension, other dimension linears
Size, diameter dimension, radius size, Angular Dimension, current threedimensional model dimension information is classified, is counted, and under
The formula in face calculates the similarity S of current threedimensional model；
Wherein, Cs1Counted for "current" model X-direction linear dimension；
Cs2Counted for "current" model Y-direction linear dimension；
Cs3Counted for "current" model Z-direction linear dimension；
Cs4For "current" model, other dimension linear sizes count；
Cs5Counted for "current" model diameter dimension；
Cs6Counted for "current" model radius size；
Cs7Counted for "current" model Angular Dimension；
(10) according to the similarity factor F of setting, similar region S-S* (1-F), S+S* (1-F) are calculated, and obtain three-dimensional mould
Level-one similarity S in type mark characteristic statistics database1One or more three-dimensional modeling datas in this section, form similar
Data set；
(11) three-dimensional modeling data that set of metadata of similar data is concentrated is traveled through, and similar data set is calculated successively according to following formula
In each three-dimensional modeling data two level similarity S2；
Wherein：
Cs1Counted for "current" model X-direction linear dimension；
Cs2Counted for "current" model Y-direction linear dimension；
Cs3Counted for "current" model Z-direction linear dimension；
Cs4For "current" model, other dimension linear sizes count；
Cs5Counted for "current" model diameter dimension；
Cs6Counted for "current" model radius size；
Cs7Counted for "current" model Angular Dimension；
Cs8Counted for "current" model aided linear size；
Cs9Diameter dimension is aided in count for "current" model；
Cs10Radius size is aided in count for "current" model；
Cs11Counted for "current" model morpheme size；
Cs12Counted for "current" model roughness；
Ci1I-th three-dimensional modeling data X-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci2I-th three-dimensional modeling data Y-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci3I-th three-dimensional modeling data Z-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci4I-th three-dimensional modeling data other dimension linear sizes counting is concentrated for set of metadata of similar data；
Ci5I-th three-dimensional modeling data diameter dimension is concentrated to count for set of metadata of similar data；
Ci6I-th three-dimensional modeling data radius size is concentrated to count for set of metadata of similar data；
Ci7I-th three-dimensional modeling data Angular Dimension is concentrated to count for set of metadata of similar data；
Ci8I-th three-dimensional modeling data aided linear size is concentrated to count for set of metadata of similar data；
Ci9I-th three-dimensional modeling data is concentrated to aid in diameter dimension to count for set of metadata of similar data；
Ci10I-th three-dimensional modeling data is concentrated to aid in radius size to count for set of metadata of similar data；
Ci11I-th three-dimensional modeling data morpheme size is concentrated to count for set of metadata of similar data；
Ci12I-th three-dimensional modeling data roughness is concentrated to count for set of metadata of similar data；
(12) according to the similarity S being calculated2, set of metadata of similar data concentrated into three-dimensional modeling data, by similarity S2By greatly to
Small rearrangement, is presented the three-dimensional modeling data and similarity S of set of metadata of similar data concentration in a manner of list2；
By associated lightweight threedimensional model, the geometry of threedimensional model can be directly viewable, realizes and is based on light weight
Change model, similarity S2Model similarity integrated decision-making；Associated at the same time by figure number unique mark, corresponding lightweight is presented
Model, realizes the visualization of result.
Associated by similar three-dimensional model and technological design data, process knowledge, realize that technological design data, technique are known
Know the knowledge push based on threedimensional model, realize that Knowledge based engineering three-dimensional process designs.
The abstraction function of threedimensional model markup information is realized in the present invention by Three-dimensional CAD Software, by the size mark of extraction
Information is noted, in a structured way organization and management, form threedimensional model mark property data base.Extract size marking information
When, corresponding Dimension Types can be got at the same time, such as linear dimension, Angular Dimension, radius size, diameter dimension, ruler of roughness
It is very little etc., classify by type to corresponding dimension information, and can be collected according to classification, counting mode.Final institute
The classification of formation, count results, by identifying associating for (such as figure number) with threedimensional model, form threedimensional model mark feature system
Count storehouse.It is to be lifted towards a large amount of threedimensional model Similarity measures and effectiveness of retrieval, employs two level calculating, retrieval side
Formula.The pretreatment of threedimensional model, size marking information is carried out first, for example, defining a set of moulded dimension classification, the standard counted
Value, then in sizes of memory markup information, carries out Similarity measures with moulded dimension classification, counting criteria value, provides and mould
The level-one similarity of type, is saved in 3 d model library.When opened in Three-dimensional CAD Software one it is new, need similar to search
During threedimensional model, the size marking information of current threedimensional model is extracted first, then the dimension information of extraction is handled, with
Moulded dimension classification, counting criteria value carry out Similarity measures, obtain the similarity of current threedimensional model.Then according to calculating
The similarity gone out, in 3 d model library, retrieval returns and the most similar one or more threedimensional models of "current" model similarity
Data, form similar data set.Obtain similar data set and then the dimension information extracted with current threedimensional model, Yi Jiqi
Its delta size information, the dimension information for concentrating each threedimensional model with set of metadata of similar data carry out secondary Similarity measures, Ran Houzai
According to result of calculation, similitude sequence is re-started, and combines light weighed model, in a manner of visual, realizes retrieval result
Presentation.
Embodiment 2
As shown in Figure 1, a kind of scale model retrieval implementation method based on three-dimensional labeling of the present invention, its feature exist
In this method combination three-dimensional CAD tool software, extracts the size marking information on threedimensional model, is then based on size marking letter
Breath, realizes calculating and the three-dimensional model search of threedimensional model similarity, its specific implementation step is：
(1) Three Dimensional Design Model；
(2) computation model similarity；
(3) scale model is retrieved；
Wherein, step (1) includes：Manufacturing sector receives threedimensional model (a.1) of the design department with size marking,
The management of threedimensional model is realized in PDM systems, forms 3 d model library；
Wherein, step (2) includes：
(2.1) by PDM system interfaces, based on the receiving time section of threedimensional model (a.1), read with incremental mode batch
The threedimensional model (a.1) in PDM systems is taken, establishes the local replica (b.1) of threedimensional model；
(2.2) by being integrated with Three-dimensional CAD Software, start three-dimensional CAD tool software, travel through successively, open local three-dimensional
Model copy (b.1), travels through, obtains three-dimensional dimension markup information (c.1) all on each model (b.1.n), meanwhile, to scheme
Number it is unique mark, generates corresponding three-dimensional light weighed model；
(2.3) according to the feature of size marking information (c.1), by size marking information (c.1) according to linear dimension
(c.1.1), (c.1.4) diameter dimension (c.1.2), radius size (c.1.3), Angular Dimension are classified, are counted；
, can be three-dimensional according to product to avoid the less size of some numerical value from interfering the similitude of threedimensional model entirety
Model feature, the size threshold values F of small size numerical value is set according to linear dimension, diameter dimension, radius size classification1、F2、F3；So
When afterwards according still further to linear dimension, diameter dimension, radius size classification, counting, exclude or filter out less than or equal to size threshold values F1、
F2、F3Data；
(2.4) linear size, extracts the label direction of linear dimension, and according to coordinate system X, Y, Z, other 4 sides
To, and again (c.1.1) linear dimension is classified and counted；
(2.5) it is the X-direction linear dimension (c.1.1.1), Y-direction linear dimension (c.1.1.2), Z-direction of formation is linear
Size (c.1.1.3), other dimension linear sizes (c.1.1.4), diameter dimension (c.1.2), radius size (c.1.3), angle
Size (c.1.4) is classified and enumeration data, according to following formula first order calculation similarity S1：
Wherein, the standard value that C is threedimensional model classification, counts；
C1Counted for X-direction linear dimension；
C2Counted for Y-direction linear dimension；
C3Counted for Z-direction linear dimension；
C4Counted for other dimension linear sizes；
C5Counted for diameter dimension；
C6Counted for radius size；
C7Counted for Angular Dimension；
(2.6) according to three-dimensional model diagram code name, X-direction linear dimension, Y-direction linear dimension, Z-direction linear dimension, its
His direction linear dimension, diameter dimension, radius size, Angular Dimension, aided linear size, auxiliary diameter dimension, auxiliary radius
13 size, morpheme size, roughness fields establish three-dimensional modeling data storehouse, and respectively by three-dimensional model diagram code name, and X side
To linear dimension, Y-direction linear dimension, Z-direction linear dimension, other dimension linear size, diameter dimension, radius size, angles
Size enumeration data is spent, is stored in the three-dimensional modeling data storehouse；
Above through size threshold values F1、F2、F3The dimension data filtered out, respectively according to aided linear size, auxiliary diameter ruler
Very little, auxiliary radius size counts, and is stored in the aided linear size of the three-dimensional modeling data storehouse, aids in diameter dimension, auxiliary radius
3 fields of size；Morpheme size, roughness are counted again, are stored in morpheme size, the roughness attribute of the three-dimensional modeling data storehouse
Field；The level-one similarity S that will be calculated1, it is saved in the similarity field of the three-dimensional modeling data storehouse；
Wherein, step (3) includes：
(3.1) threedimensional model (d.1) of similar to search is needed by three-dimensional CAD tool open in client, is then passed through
Integrated functionality opens three-dimensional search function module, reads the size marking information (f.1) of "current" model automatically by the module；
(3.2) according to the C values and size threshold values F set in three-dimensional modeling data storehouse1、F2、F3, according to current threedimensional model
Size marking information (f.1) X-direction linear dimension, Y-direction linear dimension, Z-direction linear dimension, other dimension linear sizes,
Diameter dimension, radius size, Angular Dimension, current threedimensional model dimension information is classified, is counted, and according to following public affairs
Formula calculates the similarity S of current threedimensional model；
Wherein：
Cs1Counted for "current" model X-direction linear dimension；
Cs2Counted for "current" model Y-direction linear dimension；
Cs3Counted for "current" model Z-direction linear dimension；
Cs4For "current" model, other dimension linear sizes count；
Cs5Counted for "current" model diameter dimension；
Cs6Counted for "current" model radius size；
Cs7Counted for "current" model Angular Dimension；
(3.3) in three-dimensional search function module, the current threedimensional model similarity S being calculated is called；According to three-dimensional mould
The coefficient of similarity F set in type database, calculates similar region S-S* (1-F), S+S* (1-F), and obtains 3 d model library
Middle level-one similarity S1One or more three-dimensional modeling datas in this section, form similar data set；
(3.4) three-dimensional modeling data concentrated in three-dimensional search function module, traversal set of metadata of similar data, and according to following public affairs
Formula calculates the two level similarity S that set of metadata of similar data concentrates each three-dimensional modeling data successively2；
Wherein：
Cs1Counted for "current" model X-direction linear dimension；
Cs2Counted for "current" model Y-direction linear dimension；
Cs3Counted for "current" model Z-direction linear dimension；
Cs4For "current" model, other dimension linear sizes count；
Cs5Counted for "current" model diameter dimension；
Cs6Counted for "current" model radius size；
Cs7Counted for "current" model Angular Dimension；
Cs8Counted for "current" model aided linear size；
Cs9Diameter dimension is aided in count for "current" model；
Cs10Radius size is aided in count for "current" model；
Cs11Counted for "current" model morpheme size；
Cs12Counted for "current" model roughness；
Ci1I-th three-dimensional modeling data X-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci2I-th three-dimensional modeling data Y-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci3I-th three-dimensional modeling data Z-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci4I-th three-dimensional modeling data other dimension linear sizes counting is concentrated for set of metadata of similar data；
Ci5I-th three-dimensional modeling data diameter dimension is concentrated to count for set of metadata of similar data；
Ci6I-th three-dimensional modeling data radius size is concentrated to count for set of metadata of similar data；
Ci7I-th three-dimensional modeling data Angular Dimension is concentrated to count for set of metadata of similar data；
Ci8I-th three-dimensional modeling data aided linear size is concentrated to count for set of metadata of similar data；
Ci9I-th three-dimensional modeling data is concentrated to aid in diameter dimension to count for set of metadata of similar data；
Ci10I-th three-dimensional modeling data is concentrated to aid in radius size to count for set of metadata of similar data；
Ci11I-th three-dimensional modeling data morpheme size is concentrated to count for set of metadata of similar data；
Ci12I-th three-dimensional modeling data roughness is concentrated to count for set of metadata of similar data；
(3.5) according to the similarity S being calculated2, set of metadata of similar data concentrated into three-dimensional modeling data, by similarity S2By big
To small rearrangement, three-dimensional modeling data and similarity S that set of metadata of similar data is concentrated are presented in a manner of list2, by associated
Lightweight threedimensional model, can be directly viewable the geometry of threedimensional model, realize the visualization of retrieval result, realize based on light
Quantitative model, similarity S2Model similarity integrated decision-making.
In above-mentioned steps (3.2), size threshold values F1、F2、F3Setting can be set in 3 d model library, can also lead to
Cross and be calculated.Size threshold values F1、F2、F3Setting, generally can use retain decimal point after three bit digitals.
In above-mentioned steps (2.5), C=10 is generally set, can also be adjusted according to product model feature, but for same
One 3 d model library, should set identical numerical value.
In above-mentioned steps (3.5), associated by similar three-dimensional model and technological design data, process knowledge, realize work
The knowledge push of skill design data, process knowledge based on threedimensional model, realizes that Knowledge based engineering three-dimensional process designs.
Claims (10)
1. a kind of scale model retrieval implementation method based on three-dimensional labeling, it is characterised in that this method comprises the following steps that：
(1) manufacturing sector receives threedimensional model (a.1) of the design part with size marking, the implementation model in PDM systems
Management；
(2) by PDM system interfaces, based on the receiving time section of threedimensional model (a.1), PDM is read with incremental mode batch
Threedimensional model (a.1) in system, establishes threedimensional model copy (b.1)；
(3) by being integrated with Three-dimensional CAD Software, three-dimensional CAD tool software is started, traversal opens local three-dimensional model copy successively
(b.1), three-dimensional labeling information (c.1) all on each threedimensional model copy (b.1.n) is traveled through；Meanwhile using figure number as only
One mark, generates corresponding three-dimensional light weighed model；
(4) according to size marking information (c.1) feature, by size marking information (c.1) according to linear dimension (c.1.1), diameter
Size (c.1.2), radius size (c.1.3), Angular Dimension (c.1.4) carry out differential counting；
According to product threedimensional model feature, the ruler for setting small size numerical value of classifying according to linear dimension, diameter dimension, radius size
Very little threshold values F1、F2、F3；When then according still further to linear dimension, diameter dimension, radius size differential counting, exclude or filter out to be less than
Equal to size threshold values F1、F2、F3Data；
(5) linear size, extracts the label direction of linear dimension, and according to coordinate system X, Y, Z, other 4 directions, again
(c.1.1) linear dimension is classified and counted；
(6) by the X-direction linear dimension (c.1.1.1), Y-direction linear dimension (c.1.1.2), Z-direction linear dimension of formation
(c.1.1.3), other dimension linear sizes (c.1.1.4), diameter dimension (c.1.2), radius size (c.1.3), Angular Dimension
(c.1.4) classification and enumeration data, according to following formula first order calculation index similarity S1：
<mrow>
<msub>
<mi>S</mi>
<mn>1</mn>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>1</mn>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>2</mn>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>3</mn>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>4</mn>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>5</mn>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>6</mn>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>7</mn>
</msub>
</mrow>
<mrow>
<msqrt>
<mrow>
<mn>7</mn>
<mo>*</mo>
<mi>C</mi>
<mo>*</mo>
<mi>C</mi>
</mrow>
</msqrt>
<mo>*</mo>
<msqrt>
<mrow>
<msub>
<mi>C</mi>
<mn>1</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>1</mn>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mn>2</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>2</mn>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mn>3</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>3</mn>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mn>4</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>4</mn>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mn>5</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>5</mn>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mn>6</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>6</mn>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mn>7</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>7</mn>
</msub>
</mrow>
</msqrt>
</mrow>
</mfrac>
</mrow>
Wherein, the standard value that C is threedimensional model classification, counts；
C1Counted for X-direction linear dimension；
C2Counted for Y-direction linear dimension；
C3Counted for Z-direction linear dimension；
C4Counted for other dimension linear sizes；
C5Counted for diameter dimension；
C6Counted for radius size；
C7Counted for Angular Dimension；
(7) according to three-dimensional model diagram code name, X-direction linear dimension, Y-direction linear dimension, Z-direction linear dimension, other directions
Linear dimension, diameter dimension, radius size, Angular Dimension, aided linear size, auxiliary diameter dimension, auxiliary radius size, shape
Position 13 size, roughness fields establish threedimensional model mark characteristic statistics database, and respectively by three-dimensional model diagram code name, with
And X-direction linear dimension, Y-direction linear dimension, Z-direction linear dimension, other dimension linear size, diameter dimension, radius rulers
Very little, Angular Dimension enumeration data, stores in the database；
Above through size threshold values F1、F2、F3The dimension data filtered out, respectively according to aided linear size, auxiliary diameter dimension,
Aid in radius size to count, be stored in aided linear size, auxiliary diameter dimension, auxiliary 3 fields of radius size of the database；
Morpheme size, roughness are counted again, are stored in morpheme size, the roughness attribute field of the database；
The level-one similarity S that will be calculated1, it is saved in the similarity field of the database；
(8) threedimensional model (d.1) of similar to search is needed by three dimensional CAD system opening in client, and reads "current" model
Size marking information (f.1)；
(9) according to the C values and threshold values F of threedimensional model mark characteristic statistics database setting1、F2、F3, according to current threedimensional model
Size marking information (f.1) X-direction linear dimension, Y-direction linear dimension, Z-direction linear dimension, other dimension linear rulers
Very little, diameter dimension, radius size, Angular Dimension, current threedimensional model dimension information is classified, is counted, and according to following
Formula calculate the similarity S of current threedimensional model；
<mrow>
<mi>S</mi>
<mo>=</mo>
<mfrac>
<mrow>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>1</mn>
</mrow>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>2</mn>
</mrow>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>3</mn>
</mrow>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>4</mn>
</mrow>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>5</mn>
</mrow>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>6</mn>
</mrow>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>7</mn>
</mrow>
</msub>
</mrow>
<mrow>
<msqrt>
<mrow>
<mn>7</mn>
<mo>*</mo>
<mi>C</mi>
<mo>*</mo>
<mi>C</mi>
</mrow>
</msqrt>
<mo>*</mo>
<msqrt>
<mrow>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>1</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>1</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>2</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>2</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>3</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>3</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>4</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>4</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>5</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>5</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>6</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>6</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>7</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>7</mn>
</mrow>
</msub>
</mrow>
</msqrt>
</mrow>
</mfrac>
</mrow>
Wherein, Cs1Counted for "current" model X-direction linear dimension；
Cs2Counted for "current" model Y-direction linear dimension；
Cs3Counted for "current" model Z-direction linear dimension；
Cs4For "current" model, other dimension linear sizes count；
Cs5Counted for "current" model diameter dimension；
Cs6Counted for "current" model radius size；
Cs7Counted for "current" model Angular Dimension；
(10) according to the similarity factor F of setting, similar region S-S* (1-F), S+S* (1-F) are calculated, and obtain threedimensional model mark
Note level-one similarity S in characteristic statistics database1One or more three-dimensional modeling datas in this section, form set of metadata of similar data
Collection；
(11) three-dimensional modeling data that set of metadata of similar data is concentrated is traveled through, and calculates set of metadata of similar data successively according to following formula and concentrates often
The two level similarity S of a three-dimensional modeling data2；
<mrow>
<msub>
<mi>S</mi>
<mn>2</mn>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>1</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>1</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>2</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>2</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>3</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>3</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>4</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>4</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>5</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>5</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>6</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>6</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>7</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>7</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>8</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>8</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>9</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>9</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>10</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>10</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>11</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>11</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>12</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>12</mn>
</mrow>
</msub>
</mrow>
<mrow>
<msqrt>
<mrow>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>1</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>2</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>3</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>4</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>5</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>6</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>7</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>8</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>9</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>10</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>11</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>12</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
<mo>*</mo>
<msqrt>
<mrow>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>1</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>*</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>1</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>2</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>3</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>4</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>5</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>6</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>7</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>8</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>9</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>10</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>11</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>12</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mrow>
</mfrac>
</mrow>
Wherein：
Cs1Counted for "current" model X-direction linear dimension；
Cs2Counted for "current" model Y-direction linear dimension；
Cs3Counted for "current" model Z-direction linear dimension；
Cs4For "current" model, other dimension linear sizes count；
Cs5Counted for "current" model diameter dimension；
Cs6Counted for "current" model radius size；
Cs7Counted for "current" model Angular Dimension；
Cs8Counted for "current" model aided linear size；
Cs9Diameter dimension is aided in count for "current" model；
Cs10Radius size is aided in count for "current" model；
Cs11Counted for "current" model morpheme size；
Cs12Counted for "current" model roughness；
Ci1I-th three-dimensional modeling data X-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci2I-th three-dimensional modeling data Y-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci3I-th three-dimensional modeling data Z-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci4I-th three-dimensional modeling data other dimension linear sizes counting is concentrated for set of metadata of similar data；
Ci5I-th three-dimensional modeling data diameter dimension is concentrated to count for set of metadata of similar data；
Ci6I-th three-dimensional modeling data radius size is concentrated to count for set of metadata of similar data；
Ci7I-th three-dimensional modeling data Angular Dimension is concentrated to count for set of metadata of similar data；
Ci8I-th three-dimensional modeling data aided linear size is concentrated to count for set of metadata of similar data；
Ci9I-th three-dimensional modeling data is concentrated to aid in diameter dimension to count for set of metadata of similar data；
Ci10I-th three-dimensional modeling data is concentrated to aid in radius size to count for set of metadata of similar data；
Ci11I-th three-dimensional modeling data morpheme size is concentrated to count for set of metadata of similar data；
Ci12I-th three-dimensional modeling data roughness is concentrated to count for set of metadata of similar data；
(12) according to the similarity S being calculated2, set of metadata of similar data concentrated into three-dimensional modeling data, by similarity S2It is descending heavy
New sort, is presented the three-dimensional modeling data and similarity S of set of metadata of similar data concentration in a manner of list2；
By associated lightweight threedimensional model, the geometry of threedimensional model can be directly viewable, realizes and is based on lightweight mould
Type, similarity S2Model similarity integrated decision-making；Associated at the same time by figure number unique mark, corresponding lightweight mould is presented
Type, realizes the visualization of result.
A kind of 2. scale model retrieval implementation method based on three-dimensional labeling according to claim 1, it is characterised in that step
Suddenly in (4), size threshold values F1、F2、F3Setting can be set in 3 d model library, can also be by being calculated；If
The percentage of classification setting threshold values is pressed by the way of calculating, it is necessary to first in 3 d model library, it is then linear by obtaining
The full-size numerical value each classified in size, diameter dimension, radius size, corresponding threshold number is obtained after being multiplied by percentage
According to.
A kind of 3. scale model retrieval implementation method based on three-dimensional labeling according to claim 1, it is characterised in that step
Suddenly in (4), size threshold values F1、F2、F3Setting, generally can use retain decimal point after three bit digitals.
A kind of 4. scale model retrieval implementation method based on three-dimensional labeling according to claim 1, it is characterised in that step
Suddenly in (6), C=10 is generally set, can also be adjusted according to product model feature, but is directed to same 3 d model library,
Identical numerical value should be set.
A kind of 5. scale model retrieval implementation method based on three-dimensional labeling according to claim 1, it is characterised in that step
Suddenly in (12), associated by similar three-dimensional model and technological design data, process knowledge, realize technological design data, technique
Knowledge push of the knowledge based on threedimensional model, realizes that Knowledge based engineering three-dimensional process designs.
A kind of 6. scale model retrieval implementation method based on three-dimensional labeling, it is characterised in that this method combination three-dimensional CAD instrument
Software, extracts the size marking information on threedimensional model, is then based on size marking information, realizes the meter of threedimensional model similarity
Calculate and three-dimensional model search, its specific implementation step are：
(1) Three Dimensional Design Model；
(2) computation model similarity；
(3) scale model is retrieved；
Wherein, step (1) includes：Manufacturing sector receives threedimensional model (a.1) of the design department with size marking, in PDM systems
The management of threedimensional model is realized in system, forms 3 d model library；
Wherein, step (2) includes：
(2.1) by PDM system interfaces, based on the receiving time section of threedimensional model (a.1), read with incremental mode batch
Threedimensional model (a.1) in PDM systems, establishes the local replica (b.1) of threedimensional model；
(2.2) by being integrated with Three-dimensional CAD Software, start three-dimensional CAD tool software, travel through successively, open local three-dimensional model
Copy (b.1), travels through, obtains three-dimensional dimension markup information (c.1) all on each model (b.1.n), meanwhile, using figure number as
Unique mark, generates corresponding three-dimensional light weighed model；
(2.3) according to the feature of size marking information (c.1), by size marking information (c.1) according to linear dimension (c.1.1),
(c.1.4) diameter dimension (c.1.2), radius size (c.1.3), Angular Dimension are classified, are counted；
, can be according to product threedimensional model to avoid the less size of some numerical value from interfering the similitude of threedimensional model entirety
Feature, the size threshold values F of small size numerical value is set according to linear dimension, diameter dimension, radius size classification1、F2、F3；Then again
During according to linear dimension, diameter dimension, radius size classification, counting, exclude or filter out less than or equal to size threshold values F1、F2、F3
Data；
(2.4) linear size, extracts the label direction of linear dimension, and according to coordinate system X, Y, Z, other 4 directions, and
Again (c.1.1) linear dimension is classified and counted；
(2.5) by the X-direction linear dimension (c.1.1.1), Y-direction linear dimension (c.1.1.2), Z-direction linear dimension of formation
(c.1.1.3), other dimension linear sizes (c.1.1.4), diameter dimension (c.1.2), radius size (c.1.3), Angular Dimension
(c.1.4) classification and enumeration data, according to following formula first order calculation similarity S1：
<mrow>
<msub>
<mi>S</mi>
<mn>1</mn>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>1</mn>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>2</mn>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>3</mn>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>4</mn>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>5</mn>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>6</mn>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>7</mn>
</msub>
</mrow>
<mrow>
<msqrt>
<mrow>
<mn>7</mn>
<mo>*</mo>
<mi>C</mi>
<mo>*</mo>
<mi>C</mi>
</mrow>
</msqrt>
<mo>*</mo>
<msqrt>
<mrow>
<msub>
<mi>C</mi>
<mn>1</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>1</mn>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mn>2</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>2</mn>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mn>3</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>3</mn>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mn>4</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>4</mn>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mn>5</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>5</mn>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mn>6</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>6</mn>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mn>7</mn>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mn>7</mn>
</msub>
</mrow>
</msqrt>
</mrow>
</mfrac>
</mrow>
Wherein, the standard value that C is threedimensional model classification, counts；
C1Counted for X-direction linear dimension；
C2Counted for Y-direction linear dimension；
C3Counted for Z-direction linear dimension；
C4Counted for other dimension linear sizes；
C5Counted for diameter dimension；
C6Counted for radius size；
C7Counted for Angular Dimension；
(2.6) according to three-dimensional model diagram code name, X-direction linear dimension, Y-direction linear dimension, Z-direction linear dimension, its other party
To linear dimension, diameter dimension, radius size, Angular Dimension, aided linear size, auxiliary diameter dimension, auxiliary radius size,
13 morpheme size, roughness fields establish three-dimensional modeling data storehouse, and respectively by three-dimensional model diagram code name, and X-direction line
Property size, Y-direction linear dimension, Z-direction linear dimension, other dimension linear size, diameter dimension, radius size, bevel protractors
Very little enumeration data, stores in the three-dimensional modeling data storehouse；
Above through size threshold values F1、F2、F3The dimension data filtered out, respectively according to aided linear size, auxiliary diameter dimension,
Aid in radius size to count, be stored in aided linear size, auxiliary diameter dimension, the auxiliary radius size of the three-dimensional modeling data storehouse
3 fields；Morpheme size, roughness are counted again, are stored in morpheme size, the roughness attribute word of the three-dimensional modeling data storehouse
Section；The level-one similarity S that will be calculated1, it is saved in the similarity field of the three-dimensional modeling data storehouse；
Wherein, step (3) includes：
(3.1) threedimensional model (d.1) of similar to search is needed by three-dimensional CAD tool open in client, then by integrated
Function opens three-dimensional search function module, reads the size marking information (f.1) of "current" model automatically by the module；
(3.2) according to the C values and size threshold values F set in three-dimensional modeling data storehouse1、F2、F3, according to current threedimensional model size
Markup information (f.1) X-direction linear dimension, Y-direction linear dimension, Z-direction linear dimension, other dimension linear size, diameters
Size, radius size, Angular Dimension, current threedimensional model dimension information is classified, is counted, and according to following formula meter
Calculate the similarity S of current threedimensional model；
<mrow>
<mi>S</mi>
<mo>=</mo>
<mfrac>
<mrow>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>1</mn>
</mrow>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>2</mn>
</mrow>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>3</mn>
</mrow>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>4</mn>
</mrow>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>5</mn>
</mrow>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>6</mn>
</mrow>
</msub>
<mo>+</mo>
<mi>C</mi>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>7</mn>
</mrow>
</msub>
</mrow>
<mrow>
<msqrt>
<mrow>
<mn>7</mn>
<mo>*</mo>
<mi>C</mi>
<mo>*</mo>
<mi>C</mi>
</mrow>
</msqrt>
<mo>*</mo>
<msqrt>
<mrow>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>1</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>1</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>2</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>2</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>3</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>3</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>4</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>4</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>5</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>5</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>6</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>6</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>7</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>7</mn>
</mrow>
</msub>
</mrow>
</msqrt>
</mrow>
</mfrac>
</mrow>
Wherein：
Cs1Counted for "current" model X-direction linear dimension；
Cs2Counted for "current" model Y-direction linear dimension；
Cs3Counted for "current" model Z-direction linear dimension；
Cs4For "current" model, other dimension linear sizes count；
Cs5Counted for "current" model diameter dimension；
Cs6Counted for "current" model radius size；
Cs7Counted for "current" model Angular Dimension；
(3.3) in three-dimensional search function module, the current threedimensional model similarity S being calculated is called；According to threedimensional model number
According to the coefficient of similarity F set in storehouse, similar region S-S* (1-F), S+S* (1-F) are calculated, and obtain one in 3 d model library
Level similarity S1One or more three-dimensional modeling datas in this section, form similar data set；
(3.4) in three-dimensional search function module, three-dimensional modeling data that traversal set of metadata of similar data is concentrated, and according to following formula according to
The secondary two level similarity S for calculating set of metadata of similar data and concentrating each three-dimensional modeling data2；
<mrow>
<msub>
<mi>S</mi>
<mn>2</mn>
</msub>
<mo>=</mo>
<mfrac>
<mrow>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>1</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>1</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>2</mn>
</mrow>
</msub>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>2</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>3</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>3</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>4</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>4</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>5</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>5</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>6</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>6</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>7</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>7</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>8</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>8</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>9</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>9</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>10</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>10</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>11</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>11</mn>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>12</mn>
</mrow>
</msub>
<mo>*</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>12</mn>
</mrow>
</msub>
</mrow>
<mrow>
<msqrt>
<mrow>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>1</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>2</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>3</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>4</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>5</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>6</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>7</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>8</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>9</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>10</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>11</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>s</mi>
<mn>12</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
<mo>*</mo>
<msqrt>
<mrow>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>1</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>*</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>1</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>2</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>3</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>4</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>5</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>6</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>7</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>8</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>9</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>10</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>11</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>C</mi>
<mrow>
<mi>i</mi>
<mn>12</mn>
</mrow>
</msub>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mrow>
</mfrac>
</mrow>
Wherein：
Cs1Counted for "current" model X-direction linear dimension；
Cs2Counted for "current" model Y-direction linear dimension；
Cs3Counted for "current" model Z-direction linear dimension；
Cs4For "current" model, other dimension linear sizes count；
Cs5Counted for "current" model diameter dimension；
Cs6Counted for "current" model radius size；
Cs7Counted for "current" model Angular Dimension；
Cs8Counted for "current" model aided linear size；
Cs9Diameter dimension is aided in count for "current" model；
Cs10Radius size is aided in count for "current" model；
Cs11Counted for "current" model morpheme size；
Cs12Counted for "current" model roughness；
Ci1I-th three-dimensional modeling data X-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci2I-th three-dimensional modeling data Y-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci3I-th three-dimensional modeling data Z-direction linear dimension is concentrated to count for set of metadata of similar data；
Ci4I-th three-dimensional modeling data other dimension linear sizes counting is concentrated for set of metadata of similar data；
Ci5I-th three-dimensional modeling data diameter dimension is concentrated to count for set of metadata of similar data；
Ci6I-th three-dimensional modeling data radius size is concentrated to count for set of metadata of similar data；
Ci7I-th three-dimensional modeling data Angular Dimension is concentrated to count for set of metadata of similar data；
Ci8I-th three-dimensional modeling data aided linear size is concentrated to count for set of metadata of similar data；
Ci9I-th three-dimensional modeling data is concentrated to aid in diameter dimension to count for set of metadata of similar data；
Ci10I-th three-dimensional modeling data is concentrated to aid in radius size to count for set of metadata of similar data；
Ci11I-th three-dimensional modeling data morpheme size is concentrated to count for set of metadata of similar data；
Ci12I-th three-dimensional modeling data roughness is concentrated to count for set of metadata of similar data；
(3.5) according to the similarity S being calculated2, set of metadata of similar data concentrated into three-dimensional modeling data, by similarity S2It is descending
Rearrangement, is presented the three-dimensional modeling data and similarity S of set of metadata of similar data concentration in a manner of list2, pass through associated light weight
Change threedimensional model, the geometry of threedimensional model can be directly viewable, realize the visualization of retrieval result, realization is based on lightweight
Model, similarity S2Model similarity integrated decision-making.
A kind of 7. scale model retrieval implementation method based on three-dimensional labeling according to claim 6, it is characterised in that step
Suddenly in (3.2), size threshold values F1、F2、F3Setting can be set in 3 d model library, can also be by being calculated.
A kind of 8. scale model retrieval implementation method based on three-dimensional labeling according to claim 6, it is characterised in that step
Suddenly in (3.2), size threshold values F1、F2、F3Setting, generally can use retain decimal point after three bit digitals.
A kind of 9. scale model retrieval implementation method based on three-dimensional labeling according to claim 6, it is characterised in that step
Suddenly in (2.5), C=10 is generally set, can also be adjusted according to product model feature, but is directed to same threedimensional model
Storehouse, should set identical numerical value.
A kind of 10. scale model retrieval implementation method based on three-dimensional labeling according to claim 6, it is characterised in that
In step (3.5), associated by similar three-dimensional model and technological design data, process knowledge, realize technological design data, work
Knowledge push of the skill knowledge based on threedimensional model, realizes that Knowledge based engineering three-dimensional process designs.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711310079.8A CN108021683B (en) | 2017-12-11 | 2017-12-11 | Three-dimensional labeling-based similar model retrieval implementation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711310079.8A CN108021683B (en) | 2017-12-11 | 2017-12-11 | Three-dimensional labeling-based similar model retrieval implementation method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108021683A true CN108021683A (en) | 2018-05-11 |
| CN108021683B CN108021683B (en) | 2021-06-22 |
Family
ID=62073245
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711310079.8A Active CN108021683B (en) | 2017-12-11 | 2017-12-11 | Three-dimensional labeling-based similar model retrieval implementation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108021683B (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108875181A (en) * | 2018-06-07 | 2018-11-23 | 南京骐骏软件有限公司 | A kind of three-dimensional labeling revision change method for tracing of threedimensional model |
| CN109033523A (en) * | 2018-06-26 | 2018-12-18 | 首都航天机械公司 | A kind of Assembly process specification generation System and method for based on three-dimensional CAD model |
| CN109165669A (en) * | 2018-07-09 | 2019-01-08 | 浙江大学 | Three-dimensional dough sheet model file similarity detection method based on model identification code |
| CN110555219A (en) * | 2018-05-31 | 2019-12-10 | 首都航天机械公司 | Three-dimensional CAD model similarity retrieval system and method based on image recognition |
| CN110909697A (en) * | 2019-11-28 | 2020-03-24 | 华中科技大学 | Casting three-dimensional feature extraction and similarity measurement method combined with technological parameters |
| CN111179271A (en) * | 2019-11-22 | 2020-05-19 | 浙江众合科技股份有限公司 | Object angle information labeling method based on retrieval matching and electronic equipment |
| CN112001044A (en) * | 2020-07-31 | 2020-11-27 | 宁波浙大联科科技有限公司 | Part CAD model similarity estimation method and system |
| CN113393145A (en) * | 2021-06-25 | 2021-09-14 | 广东利元亨智能装备股份有限公司 | Model similarity obtaining method and device, electronic equipment and storage medium |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101196930A (en) * | 2008-01-04 | 2008-06-11 | 覃征 | Three-dimensional model searching system |
| CN101436213A (en) * | 2008-12-16 | 2009-05-20 | 南京大学 | Method for evaluating three-dimensional model search performance based on content |
| JP2011258036A (en) * | 2010-06-10 | 2011-12-22 | Dainippon Printing Co Ltd | Three-dimensional shape search device, three-dimensional shape search method, and program |
| CN102955848A (en) * | 2012-10-29 | 2013-03-06 | 北京工商大学 | Semantic-based three-dimensional model retrieval system and method |
| CN103021029A (en) * | 2013-01-18 | 2013-04-03 | 南京大学 | Automatic labeling method for three-dimensional model component categories |
| US20130311450A1 (en) * | 2003-01-25 | 2013-11-21 | Karthik Ramani | Methods, systems, and data structures for performing searches on three dimensional objects |
| CN104239299A (en) * | 2013-06-06 | 2014-12-24 | 富士通株式会社 | Three-dimensional model retrieval method and apparatus |
| US20150331402A1 (en) * | 2014-05-13 | 2015-11-19 | Autodesk, Inc. | Intelligent 3d printing through optimization of 3d print parameters |
| CN106910252A (en) * | 2017-01-20 | 2017-06-30 | 东北石油大学 | A kind of online mask method of threedimensional model based on semantic space projective transformation and system |
| US9836483B1 (en) * | 2012-08-29 | 2017-12-05 | Google Llc | Using a mobile device for coarse shape matching against cloud-based 3D model database |
-
2017
- 2017-12-11 CN CN201711310079.8A patent/CN108021683B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130311450A1 (en) * | 2003-01-25 | 2013-11-21 | Karthik Ramani | Methods, systems, and data structures for performing searches on three dimensional objects |
| CN101196930A (en) * | 2008-01-04 | 2008-06-11 | 覃征 | Three-dimensional model searching system |
| CN101436213A (en) * | 2008-12-16 | 2009-05-20 | 南京大学 | Method for evaluating three-dimensional model search performance based on content |
| JP2011258036A (en) * | 2010-06-10 | 2011-12-22 | Dainippon Printing Co Ltd | Three-dimensional shape search device, three-dimensional shape search method, and program |
| US9836483B1 (en) * | 2012-08-29 | 2017-12-05 | Google Llc | Using a mobile device for coarse shape matching against cloud-based 3D model database |
| CN102955848A (en) * | 2012-10-29 | 2013-03-06 | 北京工商大学 | Semantic-based three-dimensional model retrieval system and method |
| CN103021029A (en) * | 2013-01-18 | 2013-04-03 | 南京大学 | Automatic labeling method for three-dimensional model component categories |
| CN104239299A (en) * | 2013-06-06 | 2014-12-24 | 富士通株式会社 | Three-dimensional model retrieval method and apparatus |
| US20150331402A1 (en) * | 2014-05-13 | 2015-11-19 | Autodesk, Inc. | Intelligent 3d printing through optimization of 3d print parameters |
| CN106910252A (en) * | 2017-01-20 | 2017-06-30 | 东北石油大学 | A kind of online mask method of threedimensional model based on semantic space projective transformation and system |
Non-Patent Citations (3)
| Title |
|---|
| WANG,DW 等: "A Retrieval Algorithm of Sheet Metal Parts Based on Relationships of Features", 《CHINESE JOURNAL OF AERONAUTICS》 * |
| 姜宏山: "基于模型相似性的CAD部件检索方法研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 张开兴等: "三维 CAD 模型检索技术研究现状与发展分析", 《农业机械学报》 * |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110555219A (en) * | 2018-05-31 | 2019-12-10 | 首都航天机械公司 | Three-dimensional CAD model similarity retrieval system and method based on image recognition |
| CN110555219B (en) * | 2018-05-31 | 2022-12-27 | 首都航天机械公司 | Three-dimensional CAD model similarity retrieval system and method based on image recognition |
| CN108875181A (en) * | 2018-06-07 | 2018-11-23 | 南京骐骏软件有限公司 | A kind of three-dimensional labeling revision change method for tracing of threedimensional model |
| CN109033523A (en) * | 2018-06-26 | 2018-12-18 | 首都航天机械公司 | A kind of Assembly process specification generation System and method for based on three-dimensional CAD model |
| CN109033523B (en) * | 2018-06-26 | 2023-04-18 | 首都航天机械公司 | Assembly process procedure generation system and method based on three-dimensional CAD model |
| CN109165669A (en) * | 2018-07-09 | 2019-01-08 | 浙江大学 | Three-dimensional dough sheet model file similarity detection method based on model identification code |
| CN109165669B (en) * | 2018-07-09 | 2021-11-16 | 浙江大学 | Three-dimensional patch model file similarity detection method based on model identification code |
| CN111179271A (en) * | 2019-11-22 | 2020-05-19 | 浙江众合科技股份有限公司 | Object angle information labeling method based on retrieval matching and electronic equipment |
| CN110909697A (en) * | 2019-11-28 | 2020-03-24 | 华中科技大学 | Casting three-dimensional feature extraction and similarity measurement method combined with technological parameters |
| CN112001044A (en) * | 2020-07-31 | 2020-11-27 | 宁波浙大联科科技有限公司 | Part CAD model similarity estimation method and system |
| CN112001044B (en) * | 2020-07-31 | 2024-04-02 | 宁波智讯联科科技有限公司 | Method and system for estimating similarity of CAD model of part |
| CN113393145A (en) * | 2021-06-25 | 2021-09-14 | 广东利元亨智能装备股份有限公司 | Model similarity obtaining method and device, electronic equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108021683B (en) | 2021-06-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108021683A (en) | A kind of scale model retrieval implementation method based on three-dimensional labeling | |
| CN112966926B (en) | Flood sensitivity risk assessment method based on ensemble learning | |
| US20210165920A1 (en) | MBD-Based Three-Dimensional Process Designing Method and Platform for Typical Automobile Machined Part | |
| CN107704637B (en) | knowledge graph construction method for emergency | |
| CN112270027A (en) | Paperless intelligent interactive examination method for city design based on entity model | |
| CN103605970A (en) | Drawing architectural element identification method and system based on machine learning | |
| CN106777275A (en) | Entity attribute and property value extracting method based on many granularity semantic chunks | |
| CN108062484A (en) | A kind of classification stage division based on data sensitive feature and database metadata | |
| CN113987212A (en) | Knowledge graph construction method for process data in numerical control machining field | |
| CN104881689A (en) | Method and system for multi-label active learning classification | |
| CN107004141A (en) | To the efficient mark of large sample group | |
| CN110188092B (en) | System and method for mining new type contradiction dispute in people mediation | |
| CN106600046A (en) | Multi-classifier fusion-based land unused condition prediction method and device | |
| CN105740325A (en) | Trans-scale geographic information linkage updating technical method based on spatial automatic matching | |
| CN113806392A (en) | Building project list data processing method, project pricing method and device | |
| CN107392129A (en) | Face retrieval method and system based on Softmax | |
| CN111931269A (en) | Automatic checking method and system for consistency of information of BIM and important components in drawings | |
| CN104182456B (en) | Spatial entity increment extraction method based on MRS-MM (Multi-Rules Supported Matching Model) target matching model | |
| CN106897437A (en) | The many sorting techniques of high-order rule and its system of a kind of knowledge system | |
| CN102360436B (en) | Identification method for on-line handwritten Tibetan characters based on components | |
| CN110222129A (en) | A kind of credit appraisal algorithm based on relevant database | |
| CN108416137B (en) | Method for conveniently dividing and tracking simplified expression standard part in aircraft manufacturing | |
| JPH01188934A (en) | Automatic document sorting device | |
| CN110264066A (en) | A kind of automobile industry transition and upgrade information monitoring system | |
| CN115113919B (en) | Software scale measurement intelligent informatization system based on BERT model and Web technology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |