CN105045996A - Automatic generation method for assembly tolerance synthesis of complex assembly body - Google Patents
Automatic generation method for assembly tolerance synthesis of complex assembly body Download PDFInfo
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- CN105045996A CN105045996A CN201510412622.XA CN201510412622A CN105045996A CN 105045996 A CN105045996 A CN 105045996A CN 201510412622 A CN201510412622 A CN 201510412622A CN 105045996 A CN105045996 A CN 105045996A
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Abstract
The invention discloses an automatic generation method for assembly tolerance synthesis of a complex assembly body. The method comprises the following steps of: (1) constructing a three-dimensional assembly model of a product; (2) disassembling the three-dimensional model; (3) extracting assembly restriction relations among parts; (4) extracting assembly characteristic surfaces of the parts; (5) constructing an assembly tolerance synthesis body class and attributes; (6) constructing an assertion axiom set for representing the assembly restriction relations among the parts; (7) constructing an assertion axiom set for representing assembly restriction relations among the characteristic surfaces; (8) constructing an assertion axiom set for representing space relations among geometric elements of the assembly characteristic surfaces; (9) determining an assembly tolerance type and an assembly tolerance value of each part by inference; (10) performing optimal distribution on the tolerance values; and (11) performing assemblability evaluation. The method adopts a network body language and a semantic web rule language for describing the whole inference process, and has the advantages of simplicity, high efficiency, intelligence and the like.
Description
Technical field
The invention belongs to computer-aided tolerance design (CAT) field, be specifically related to a kind of Complex Assembly body build-up tolerance comprehensive automation generation method.
Background technology
Tolerance comprehensively refers to when meeting Product Assembly functional requirement, and with the assembling capacity of product and product manufacturability for constraint, making total cost minimum is the Tolerance assignment process of target.In the design process of current geometric product, tolerance integrated information is specify by deviser is manual in CAD system substantially.Due to the difference on deviser's experience, different devisers likely specifies different build-up tolerance types and tolerance value to same geometric product, and this will cause the uncertainty in product design process.In order to reduce this uncertainty, solving tolerance information simultaneously between heterogeneous system, transmitting not smooth problem, needing to represent tolerance information with unified semanteme.How automatically to generate the problem with smooth and easy transmission of effectively sharing of rational tolerance type and tolerance value and tolerance information, become one of bottleneck that CAD develops and CAX is integrated.
Summary of the invention
For " in product design process, tolerance comprehensively cannot generate automatically " and " tolerance information is transmitted not smooth between isomery CAX system " this two problems, the present invention draws artificial intelligence field newest research results, provides a kind of Complex Assembly body build-up tolerance comprehensive automation generation method.
A kind of Complex Assembly body build-up tolerance comprehensive automation generation method, its step is as follows:
(1) build the three-dimensional assembling model of product, according to the functional requirement of product and the ideal dimensions of each part, use three-dimensional solid modeling software SolidWorks to construct the three-dimensional assembling model of product;
(2) the three-dimensional assembling model of de-assembly product, according to the structure of product, carries out de-assembly to the three-dimensional assembling model of product in SolidWorks, is more than 2 parts by model decomposition;
(3) extract the assembly restriction between part, from the three-dimensional assembling model of product, extract the assembly restriction between each part;
(4) extract the assembly features surface of each part, each part in product three-dimensional model is decomposed into further more than 2 assembly features surfaces, automatically extract the assembly features surface of each part;
(5) structure of the comprehensive body class of build-up tolerance and attribute, by analyzing build-up tolerance general field relevant knowledge, extracting concept wherein and relation, building the class in the comprehensive body of tolerance and attribute;
(6) build represent assembly restriction between part assert axiom collection, according to the assembly restriction between the part that step 3 is extracted, build represent assembly restriction between part assert axiom collection;
(7) build represent restriction relation between assembly features surface assert axiom collection, assembly restriction between the expression part that the assembly features surface of each part extracted according to step 4 and step 6 build assert axiom collection, build represent restriction relation between assembly features surface assert axiom collection;
(8) build represent spatial relationship between assembly features surface geometry key element assert axiom collection, axiom collection is asserted according to restriction relation between the expression assembly features surface that step 7 builds, determine that key element is derived in actual element and the matching of every figuratrix mutually retrained for a pair, according to the topological structure of these geometric elements and assembly, determine the spatial relationship between assembly features surface geometry key element, and build represent these spatial relationships assert axiom collection;
(9) build-up tolerance type and the build-up tolerance value of each part is determined in reasoning, build in step 8 represent spatial relationship between assembly features surface geometry key element assert that axiom collection is as input, the structural knowledge that network ontology language (OWL) describes is converted to the Jess fact, and the about fasciculation Knowledge conversion described by semantic net rule language (SWRL) is Jess rule, apply the reasoning of Jess inference engine afterwards and generate the optional build-up tolerance type on every assembly features surface mutually retrained for a pair and optional build-up tolerance value, finally choice and optimization is carried out to them,
(10) optimization of tolerance value distributes, after reasoning obtains optional build-up tolerance value, with cost-tolerance function for objective function, with the equality constraint of tolerance and inequality constrain for constraint condition, the optimization of setting up tolerance value distributes mathematical model, and is optimized tolerance value based on genetic algorithm;
(11) assemble ability evaluation, after achieving the optimization distribution of tolerance value, also needs to test to the assembling capacity of product.The value of random selecting spinor parameter in the tolerance interval optimized, and calculate the assembly yield corresponding to each assembling function demand.
The present invention adopts OWL and SWRL to describe whole reasoning process, has simplification, high efficiency and the advantage such as intelligent.It meets tolerance information and effectively share the demand with smooth and easy transmission between isomery CAX system, meets the top-down thinking habit of deviser, has stronger applicability.
Accompanying drawing explanation
The process flow diagram of the build-up tolerance comprehensive automation generation method of Fig. 1 designed by the present invention;
Fig. 2 is the partial view splitting gear case;
Fig. 3 is the assembly features exterior view of part;
Fig. 4 is the hierarchical relationship figure of all OWL classes that the present invention builds;
Fig. 5 is the hierarchical relationship figure of all OWL attributes that the present invention builds;
Fig. 6 is the comprehensive create-rule figure of build-up tolerance that the employing SWRL that sets up of the present invention describes;
The optional build-up tolerance type of Fig. 7 (icylindrical, s01 (p3));
The optional build-up tolerance type of Fig. 8 (s04 (p02), s01 (p3));
Fig. 9 splits gear case tolerances marking figure.
Embodiment
The implementation process that gear case carrys out illustration method is split below for a certain.These parts are made up of casing, case lid, gear shaft and lining, and designate relevant dimension information in the figure.Certain gap is had to be A between the shaft shoulder and left side bush end face after assembling
0, the basic size of each part known and tolerance (unit: mm), build-up tolerance comprehensive automation product process is shown in Fig. 1.
Step 1: the three-dimensional assembling model building product.According to the functional requirement of product and the ideal dimensions of each part, build the three-dimensional assembling model of splitting gear case at SolidWorks, Fig. 2 is shown in by its partial view.
Step 2: the three-dimensional assembling model of de-assembly product.According to the structure of splitting gear case, de-assembly is carried out to its three-dimensional assembling model, resolve into 5 parts.
Step 3: extract the assembly restriction between part.The assembly restriction between each part is extracted from the three-dimensional assembling model of product.
Step 4: the assembly features surface of extracting each part.Each part in product three-dimensional model is decomposed into 15 assembly features surfaces further, extracts the assembly features surface of each part on this basis.Part p
1, p
2, p
3, p
4and p
5assembly features surface see Fig. 3.
Step 5: the structure of the comprehensive body class of build-up tolerance and attribute.By analyzing tolerance general field knowledge, build class and the attribute of the comprehensive body of build-up tolerance.Hierarchical relationship in body between class is shown in Fig. 4, and the hierarchical relationship between object properties is shown in Fig. 5.
Step 6: build represent assembly restriction between part assert axiom collection.According to the assembly restriction between the part that step 3 is extracted, build represent assembly restriction between part assert axiom collection
wherein Part represents part, and has-ACR represents to there is assembly restriction between two parts.
Step 7: build represent restriction relation between assembly features surface assert axiom collection.What represent assembly restriction between part according to the assembly features of part each in step 4 surface and step 6 asserts axiom collection, build represent restriction relation between assembly features surface assert axiom collection.What built by step 6 asserts axiom collection
know, with p
3the part of assembly restriction is had to have p
2, p
4and p
5.Can build on this basis represent these 4 parts assembly features surface between restriction relation assert axiom collection
wherein RFS represents the actual characteristic surface of part, and has-ACR represents to there is restriction relation between assembly features surface.
Step 8: build represent mutually constraint assembly features surface geometry key element between spatial relationship assert axiom collection.What build according to step 7 asserts axiom collection
determine the geometric element on every assembly features surface mutually retrained for a pair.Wherein adf (s
i(p
j)) represent part p
ji-th assembly features surface matching derive key element.Make icy be the example of OWL class ICylindrical, ipl is an example of OWL class IPlanar.According to the topological structure of the geometric element determined and assembly, can build and represent part p
2, p
3, p
4and p
5between assembly features surface geometry key element, spatial relationship asserts axiom collection
Step 9: build-up tolerance type and the build-up tolerance value of each part are determined in reasoning.Build-up tolerance type, cost-tolerance function, tolerance spinor parameter and optional build-up tolerance value part inference rule are shown in Fig. 6.Such as, in order to determine T
s(icylindrical, s
01(p
3)) and T
s(s
04(p
02), s
01(p
3)) (wherein T
s(x, y) represents the set of the optional build-up tolerance type between assembly features surface x and assembly features surface y), first they should be created as the example of corresponding OWL class.What built by step 5 asserts axiom collection
in OWL assert TSL (adf (s
04(p
2))), DSL (adf (s
01(p
3))), SOC (s
01(p
3)) and ICylindrical (icylindrical) know, adf (s
04(p
2)), adf (s
01(p
3)), s
01(p
3) and icylindrical be created in Prot é g é as the example of respective class.Similarly, by
in OWL assert has-COI (adf (s
04(p
4)), adf (s
04(p
3))) and has-CON (icylindrical, s
04(p
3)) know, these two attribute assertion are also created in Prot é g é.By calling Jess inference engine, T
s(icylindrical, s
01(p
3)) and T
s(s
04(p
02), s
01(p
3)) (see Fig. 6 and Fig. 7), that is: T in Prot é g é will be created on
s(icylindrical,
t
s(s
04(p
02),
to the assembly features surface of the mutual constraint of other group, their respective optional build-up tolerance types can be obtained similarly:
Make T
f(x, y) represents the set of the build-up tolerance type finally chosen after optimizing between assembly features surface x and assembly features surface y, according to tolerance rule, chooses T
f(icylindrical, s
01(p
3))=T
f(icylindrical,
choose T
f(s
02(p
02),
split case part p
3tolerances marking see Fig. 8.
Step 10: the optimization of tolerance value distributes.The selectable value of tolerance is as following table 1, wherein t
1and t
2for parallelism tolerance, t
3and t
4for total run-out degree tolerance.
Table 1
Tolerance equality constraint: h
k(x
i, y
i, z
i, a
i, b
i, g
i; t
i)=0, i=0,1 ..., n
Tolerance inequality constrain: g
i(x
i, y
i, z
i, a
i, b
i, g
i; t
i)>=0, i=0,1 ..., n
Application genetic algorithm, the tolerance value after optimization is as table 2
Table 2
| Tolerance | t 1 | t 2 | t 3 | t 4 |
| Optimal value | 0.012 | 0.012 | 0.015 | 0.010 |
Step 11: assemble ability evaluation.All tolerance stochastic generation are met to 100 groups of spinor parameters of tolerance inequality constrain, these spinor parameters are substituted in tolerance equality constraint, calculates the spinor parameter of each Variational Geometric Constraints, meet matching requirements as calculated.
Above content is further illustrating of doing implementation process of the present invention in conjunction with case study on implementation, and can not assert that the specific embodiment of the present invention is only limitted to this.For general technical staff of the technical field of the invention; under the prerequisite not departing from design of the present invention and method; can also make some simple deduction or replace, these all should be considered as the determined scope of patent protection of claims that the present invention submits to.
Claims (5)
1. the automatic generation method that Complex Assembly body build-up tolerance is comprehensive, is characterized in that: comprise the steps:
(1) the three-dimensional assembling model of product is built;
(2) the three-dimensional assembling model of de-assembly product;
(3) assembly restriction between part is extracted;
(4) the assembly features surface of each part is extracted;
(5) build represent assembly restriction between part assert axiom collection;
(6) build represent restriction relation between assembly features surface assert axiom collection;
(7) build represent spatial relationship between assembly features surface geometry key element assert axiom collection;
(8) reasoning determination build-up tolerance type, cost-tolerance function, tolerance spinor parameter and build-up tolerance value;
(9) build-up tolerance type and the build-up tolerance value of each part is determined in reasoning, build in step 8 represent spatial relationship between assembly features surface geometry key element assert that axiom collection is as input;
(10) optimization of tolerance value distributes;
(11) assemble ability evaluation, the value of random selecting spinor parameter in the tolerance interval optimized, and calculate the assembly yield corresponding to each assembling function demand.
2. the build-up tolerance comprehensive automation method of generationing as claimed in claim 1, is characterized in that: based on the assembly information of product, and what adopt network ontology language OWL to build assembly restriction between expression part asserts axiom collection.
3. build-up tolerance comprehensive automation generation method as claimed in claim 1, it is characterized in that: based on each part assembly features surface and represent assembly restriction between part assert axiom collection, what adopt OWL to build to represent the restriction relation between assembly features surface asserts axiom collection.
4. build-up tolerance comprehensive automation generation method as claimed in claim 1, it is characterized in that: based on assembly topological structure and represent restriction relation between assembly features surface assert axiom collection, between the assembly features surface geometry key element adopting OWL to build to represent constraint mutually, spatial relationship asserts axiom collection.
5. build-up tolerance comprehensive automation generation method as claimed in claim 1, it is characterized in that: employing OWL describes the structural knowledge in the generation of build-up tolerance type, cost-tolerance function, tolerance spinor parameter and optional build-up tolerance value, and adopts semantic net rule language SWRL to describe about fasciculation knowledge.
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| CN105718645A (en) * | 2016-01-19 | 2016-06-29 | 同济大学 | Building method of complex model of complex product |
| CN108717472A (en) * | 2018-04-03 | 2018-10-30 | 桂林电子科技大学 | A kind of assembly positioning contact priority generation method based on ontology rule description |
| CN111275828A (en) * | 2019-12-31 | 2020-06-12 | 深圳市工之易科技有限公司 | Data processing method and device for three-dimensional assembly and electronic equipment |
| CN112989518A (en) * | 2021-03-16 | 2021-06-18 | 华南理工大学 | Intelligent assembly modeling method based on design intention |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105447279A (en) * | 2015-12-30 | 2016-03-30 | 许源平 | Intelligent tolerance specification design method for geometric products and visual tolerance annotation system |
| CN109753715A (en) * | 2015-12-30 | 2019-05-14 | 成都信息工程大学 | Visualize tolerances marking system |
| CN105447279B (en) * | 2015-12-30 | 2019-07-16 | 成都信息工程大学 | Geometric product intelligence tolerance specifications design method and visualization tolerances marking system |
| CN105718645A (en) * | 2016-01-19 | 2016-06-29 | 同济大学 | Building method of complex model of complex product |
| CN105718645B (en) * | 2016-01-19 | 2019-01-11 | 同济大学 | A kind of method for building up of the complex model of complex product |
| CN108717472A (en) * | 2018-04-03 | 2018-10-30 | 桂林电子科技大学 | A kind of assembly positioning contact priority generation method based on ontology rule description |
| CN111275828A (en) * | 2019-12-31 | 2020-06-12 | 深圳市工之易科技有限公司 | Data processing method and device for three-dimensional assembly and electronic equipment |
| CN112989518A (en) * | 2021-03-16 | 2021-06-18 | 华南理工大学 | Intelligent assembly modeling method based on design intention |
| CN112989518B (en) * | 2021-03-16 | 2023-03-21 | 华南理工大学 | Intelligent assembly modeling method based on design intention |
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