CN117521346A - Tolerance distribution analysis method based on digital twinning - Google Patents
Tolerance distribution analysis method based on digital twinning Download PDFInfo
- Publication number
- CN117521346A CN117521346A CN202311415892.7A CN202311415892A CN117521346A CN 117521346 A CN117521346 A CN 117521346A CN 202311415892 A CN202311415892 A CN 202311415892A CN 117521346 A CN117521346 A CN 117521346A
- Authority
- CN
- China
- Prior art keywords
- assembly
- tolerance
- digital twin
- digital
- twin model
- 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.)
- Pending
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 47
- 238000009826 distribution Methods 0.000 title claims abstract description 34
- 238000000034 method Methods 0.000 claims abstract description 43
- 230000008569 process Effects 0.000 claims abstract description 32
- 238000004088 simulation Methods 0.000 claims abstract description 23
- 238000010276 construction Methods 0.000 claims abstract description 10
- 238000004364 calculation method Methods 0.000 claims abstract description 9
- 238000013461 design Methods 0.000 claims abstract description 4
- 238000005259 measurement Methods 0.000 claims description 8
- 230000006870 function Effects 0.000 claims description 6
- 238000005516 engineering process Methods 0.000 claims description 3
- 230000008439 repair process Effects 0.000 claims description 3
- 238000012986 modification Methods 0.000 description 5
- 230000004048 modification Effects 0.000 description 5
- 230000000712 assembly Effects 0.000 description 2
- 238000000429 assembly Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000003754 machining Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- General Factory Administration (AREA)
Abstract
The invention provides a tolerance distribution analysis method based on digital twinning. The method comprises the steps of establishing a digital twin model, forming the pre-judgment of whether the assembly is qualified or not before the actual assembly by using a probability-related calculation method through a simulation means, getting rid of the dependence of a traditional design method on experience, and improving the accuracy of tolerance distribution, and comprises the following steps: 1) And constructing an assembled digital twin model. 2) And (5) pre-judging an assembly structure based on the assembled digital twin model. 3) And reusing and calling the digital twin database. 4) And (5) analyzing assembly errors in the construction of the digital twin model. 5) Tolerance distribution analysis of digital twin models. 6) Iterative adjustment based on the tolerance of the digital twin model. The invention reduces and controls the product deviation, reduces the assembly reworking and incompatibility and improves the assembly success rate in the product assembly process, and is suitable for being applied as a tolerance distribution analysis method based on digital twin.
Description
Technical Field
The invention relates to an analysis method in the field of digitization, in particular to a tolerance distribution analysis method based on digital twinning.
Background
The digital twin is a process of fully utilizing a physical model, a sensor model and operation history data, integrating simulation processes of multiple disciplines, multiple physical quantities, multiple scales and multiple probabilities, and finishing mapping in a virtual space so as to reflect the full life cycle of corresponding entity equipment. The twin body actually reflects a prototype or a model under a real tool in real time through simulation, and has two remarkable characteristics: the twin body has high similarity with the object to be reflected by the twin body in appearance (referring to the geometric shape and the size of a product), content (referring to the structural composition of the product and macroscopic and microscopic physical characteristics of the product) and properties (referring to the functions and the performances of the product); and secondly, the real device can be expressed in an abstract way, and the test under the real condition or the simulation condition can be carried out on the basis of the real device. The digital twin technology is utilized to achieve virtual-real interaction, data analysis and feedback optimization of the whole process information of the production period of the product, so that the digital twin plays a role of a tie connecting the digital space and the physical space, and the quality and the efficiency of the production of the product are improved.
In order to verify the suitability of product designs in early stages in the construction of products such as ships, airplanes, automobiles, etc., and to demonstrate the fit of the assembly, disassembly, maintenance and use of the products and their equipment, a tolerance expression model refers to a method of converting geometric tolerances of parts into deviations, with the aim of obtaining source deviations in the assembly. Tolerance analysis is an effective analysis method for product size coordination. Tolerance analysis is to accumulate the machining precision and the assembly precision of the parts in a size chain and check whether the precision of the product can meet the requirement of the product. Through the tolerance value of the continuous iterative product, the product can obtain a reasonable precision range before processing, and the assembly efficiency and quality can be improved.
Disclosure of Invention
Aiming at solving the defects existing in the prior art, reducing and controlling product deviation, reducing assembly reworking and incompatibility and improving assembly success rate in the product assembly process, the invention provides a tolerance distribution analysis method based on digital twinning. The method realizes tolerance distribution and analysis of product parts and solves the technical problem of tolerance distribution analysis by constructing an assembled digital twin model, pre-judging an assembly structure based on the assembled digital twin model, reusing and calling a digital twin database, analyzing assembly errors in the construction of the digital twin model, analyzing tolerance distribution of the digital twin model and adjusting the tolerance iteration of the digital twin model.
The invention solves the technical problems by adopting the scheme that:
a tolerance distribution analysis method based on digital twin establishes a digital twin model, forms the pre-judgment of whether the assembly is qualified or not before the actual assembly by using a probability-related calculation method through a simulation means, gets rid of the dependence of a traditional design method on experience, improves the accuracy of tolerance distribution, and comprises the following steps:
1) And constructing an assembled digital twin model.
In the product assembly process, according to the traditional assembly method, the assembly parts are numerous, the quality and the speed of the assembly process play a decisive role in the construction speed of subsequent products, and many assembly processes depend on the experience and the technology of workers, a digital twin model which is highly overlapped with the similarity of a real assembly body can be established in function and performance by modeling the assembly body, and the digital twin model is constructed by combining the product theoretical model and the actual measurement data of processed parts.
2) And (5) pre-judging an assembly structure based on the assembled digital twin model.
Through virtual assembly simulation of the twin model of the machined part, a probability-related calculation method is utilized to form the pre-judgment of whether the assembly is qualified or not before actual assembly.
3) And reusing and calling the digital twin database.
In the digital twin formed by the assembly, there are many similar or identical assembly modes and assembly data, and the assembly modes and assembly data are imported into the digital twin database, and in other assemblies and subsequent tolerance allocations, the data in the digital twin database can be recalled, so that parameterized data in the same assembly modes are ensured to be effectively extended.
4) And (5) analyzing assembly errors in the construction of the digital twin model.
In the same assembly process, various types of errors exist, the accuracy of assembly simulation can be improved through error analysis, constraint errors and random errors are contained in the error analysis, but all errors in the whole assembly can affect the assembly accuracy, and the assembly in the twin model is required to be subjected to error analysis, so that the real object of the twin model is mapped, and the error analysis in the real assembly is reduced.
5) Tolerance distribution analysis of digital twin models.
The simulation process description is carried out on the digital sample machine by referring to the real running condition of the physical sample machine, the process is a generic name of all events occurring when the equipment processes the part, the process is described by using a corresponding language, and the process is associated to a certain element of the digital sample machine, so that the element executes the process, and the digital sample machine is accurately simulated and analyzed.
6) Iterative adjustment based on the tolerance of the digital twin model.
Through simulation calculation of the first steps, the out-of-tolerance rate of all closed loop measurements can be obtained from simulation results, when the out-of-tolerance rate is within an acceptable range, the current machined part can be judged to be finished under the current assembly process, if the out-of-tolerance rate is within an unacceptable range, tolerance reassignment is required based on a digital twin model, component loops affecting assembly success rate are found out through analysis of an assembly dimension chain, a repair range is analyzed, and tolerance iterative adjustment is carried out.
The positive effects are as follows:
the tolerance distribution and analysis of the product parts are realized through the steps of assembly-oriented digital twin model construction, assembly structure pre-judgment based on the assembled digital twin model, reuse and calling of the digital twin database, assembly error analysis in the digital twin model construction, tolerance distribution analysis of the digital twin model and tolerance iteration adjustment based on the digital twin model. The method reduces and controls product deviation, reduces assembly reworking and incompatibility in the product assembly process, improves assembly success rate, and is suitable for being applied as a tolerance distribution analysis method based on digital twin.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention. The description of the present invention has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.
Fig. 1 is a flowchart of the present embodiment.
Description of the embodiments
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
According to the figure, a tolerance distribution analysis method based on digital twinning is specifically implemented in the following cases:
and constructing a digital twin model facing assembly of a certain shafting assembly, wherein the shafting assembly has more assembly freedom, and the digital twin model is constructed according to the assembled actual measurement data along the directions of XYZ and the like. And a digital twin model which is highly overlapped with the similarity of the real assembly body is established in terms of functions and performances, and a shafting assembly body digital model is established by combining the product theoretical model and actual measurement data of the processed parts. And (3) performing related assembly activities on the shaft assembly parts by utilizing an assembly function in three-dimensional design software, and judging whether the assembly is qualified or not before actual assembly by utilizing a 3 sigma calculation method according to the dimensional chain tolerance distribution among the shaft assemblies. And (3) calling similar assembly parameters and data in the digital twin database, and inputting the parameters and other data into the existing process for use after the calling. And analyzing assembly errors in model construction in digital twin model construction, continuously carrying out tolerance distribution analysis on the digital twin model in the shaft system assembly after analysis, and finally adjusting based on tolerance iteration of the digital twin model.
In the shafting assembling process, shafts, flanges and interfaces are assembled, a digital model similar to a real shafting assembly is built in function and performance by modeling the shafts, an assembly body, the flanges and the interfaces, and the digital twin model is built by combining a product theoretical model and actual measurement data of processed parts.
The method comprises the steps of pre-judging an assembly structure based on an assembled digital twin model, pre-judging the assembly structure in a shafting assembly twin model, performing assembly simulation verification in Catia V6, and performing relevant verification on a simulation result by using the probability of super-geometric distribution to form pre-judging whether the assembly is qualified or not before actual assembly.
The digital twin database is reused and called, a plurality of similar or identical assembly modes and assembly data exist in the digital twin formed by the assembly, the assembly modes and the assembly data are imported into the shafting digital model, and the data in the database are recalled in assembly and subsequent tolerance distribution, so that parameterized data in the same assembly mode are ensured to be effectively extended.
During the assembly process of the shafting assembly, errors in the directions of deviation and three degrees of freedom exist, the accuracy of the shafting assembly is improved through the error analysis of the shafting assembly, constraint errors and random errors are contained in the error analysis, the errors in the whole shafting assembly can affect the assembly accuracy, the assembly in the twin model is required to be analyzed, and therefore the real object of the twin model is mapped, and the errors in the shafting assembly are reduced.
And carrying out tolerance distribution analysis on the digital twin model, carrying out secondary tolerance distribution according to assembly simulation in the shafting assembly part model and according to simulation results, defining a shafting assembly part closed loop according to assembly of products, obtaining various tolerances in the shafting assembly part closed loop, and carrying out tolerance distribution analysis according to the digital twin model.
Based on the tolerance iterative adjustment of the digital twin model, the over-tolerance rate of all closed loop measurement of the shafting assembly can be obtained from simulation results through simulation calculation of the first steps, when the over-tolerance rate is within an acceptable range, the current machined part can be judged to be finished under the current assembly process, if the over-tolerance rate is within an unacceptable range, tolerance redistribution is needed based on the digital twin model of the shafting assembly, the component loops influencing the assembly success rate are found out through analysis of an assembly dimension chain, the repair range is analyzed, and the tolerance iterative adjustment is carried out.
Finally, it should be noted that:
the foregoing description is only illustrative of the preferred embodiments of the present invention, and although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described, or equivalents may be substituted for elements thereof, and any modifications, equivalents, improvements or changes may be made without departing from the spirit and principles of the present invention.
Claims (7)
1. A tolerance distribution analysis method based on digital twinning is characterized in that:
the method comprises the steps of establishing a digital twin model, forming the pre-judgment of whether the assembly is qualified or not before the actual assembly by using a probability-related calculation method through a simulation means, getting rid of the dependence of a traditional design method on experience, and improving the accuracy of tolerance distribution, and comprises the following steps:
1) Constructing an assembled digital twin model;
2) Pre-judging an assembly structure based on an assembled digital twin model;
3) Reusing and calling the digital twin database;
4) Assembling error analysis in digital twin model construction;
5) Tolerance distribution analysis of the digital twin model;
6) Iterative adjustment based on the tolerance of the digital twin model.
2. The tolerance distribution analysis method based on digital twinning according to claim 1, wherein:
in the step 1), in the product assembling process, according to the traditional assembling method, the assembling parts are numerous, the quality and the speed of the assembling process play a decisive role in the building speed of subsequent products, and many assembling processes depend on experience and technology of workers, a digital twin model which is highly overlapped with the similarity of a real assembling body can be established in function and performance by modeling the assembling body, and the digital twin model is constructed by combining the product theoretical model and actual measurement data of processed parts.
3. The tolerance distribution analysis method based on digital twinning according to claim 1, wherein:
in the step 2), the virtual assembly simulation of the processed part twin model is utilized to form the pre-judgment of whether the assembly is qualified or not before the actual assembly by utilizing a probability-related calculation method.
4. The tolerance distribution analysis method based on digital twinning according to claim 1, wherein:
in step 3), there are many similar or identical assembly modes and assembly data in the digital twin formed by the assembly, these assembly modes and assembly data are imported into the digital twin database, and in other assembly and subsequent tolerance allocation, the data in the digital twin database can be recalled, ensuring that parameterized data in the same assembly mode is effectively extended.
5. The tolerance distribution analysis method based on digital twinning according to claim 1, wherein:
in the step 4), in the same assembly process, various types of errors exist, the accuracy of assembly simulation can be improved through error analysis, constraint errors and random errors are contained in the error analysis, but all errors in the whole assembly can affect the assembly accuracy, and the assembly in the twin model is required to be subjected to error analysis, so that the real object of the twin model is mapped, and the error analysis in the real assembly is reduced.
6. The tolerance distribution analysis method based on digital twinning according to claim 1, wherein:
in step 5), the digital sample machine carries out simulation process description by referring to the real running condition of the physical model machine, the process is a generic name of all events occurring when the equipment processes the part, the process is described by using a corresponding language, the process is associated to a certain element of the digital sample machine, the element executes the process, and the digital sample machine carries out accurate simulation analysis.
7. The tolerance distribution analysis method based on digital twinning according to claim 1, wherein:
in step 6), through simulation calculation of the first steps, the out-of-tolerance rate of all closed loop measurements can be obtained from simulation results, when the out-of-tolerance rate is within an acceptable range, the current machined part is judged to be finished under the current assembly process, if the out-of-tolerance rate is within an unacceptable range, tolerance redistribution is needed based on a digital twin model, a component loop affecting assembly success rate is found out through analysis of an assembly dimension chain, a repair range is analyzed, and tolerance iterative adjustment is carried out.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311415892.7A CN117521346A (en) | 2023-10-30 | 2023-10-30 | Tolerance distribution analysis method based on digital twinning |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311415892.7A CN117521346A (en) | 2023-10-30 | 2023-10-30 | Tolerance distribution analysis method based on digital twinning |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117521346A true CN117521346A (en) | 2024-02-06 |
Family
ID=89740929
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311415892.7A Pending CN117521346A (en) | 2023-10-30 | 2023-10-30 | Tolerance distribution analysis method based on digital twinning |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117521346A (en) |
-
2023
- 2023-10-30 CN CN202311415892.7A patent/CN117521346A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111145236B (en) | Product quasi-physical assembly model generation method based on digital twinning and implementation framework | |
| US8881392B2 (en) | Method of repairing machined components such as turbomachine blades or blades of blisks | |
| CN111274671A (en) | Precise repairing and assembling method for complex product assembling process based on digital twinning and operation system thereof | |
| CN110826130A (en) | Application method of BIM modeling in design and construction of special-shaped curved surface structure body | |
| CN106020147A (en) | Systematic analysis method for assembling precision of complex precise mechanical product | |
| CN111931340A (en) | Tolerance management system and management method | |
| CN108009327B (en) | Virtual pre-assembly error judgment method based on steel member deformation analysis | |
| CN114969976B (en) | Integrated structure virtual assembly method based on digital measured data | |
| CN112031487A (en) | DMBP (distributed binary BP) assembly type machine room construction method based on BIM (building information modeling) technology | |
| CN111723440A (en) | Thin-wall part machining precision prediction hybrid modeling method | |
| CN111310318A (en) | Digital twinning-based process margin processing method and system and mechanical manufacturing assembly | |
| CN109582989A (en) | The three-dimensional bias modeling analysis method of the porous assembly of one side for aircraft | |
| CN111581804A (en) | Method for generating minimum part repair scheme based on actual measurement model | |
| CN112548032A (en) | Casting method based on three-dimensional scanning | |
| CN111241699B (en) | Method for improving warping deformation of automobile headlamp mask | |
| CN104484511A (en) | Simulation analysis based dynamic characteristic design method for robot structures | |
| CN106295015B (en) | A kind of profile modification method of involute spur gear pair and special parameters CAD system matched with its | |
| CN113191071B (en) | Method for virtually calibrating engine model and related device thereof | |
| CN113496064A (en) | Compensation adjustment method for straightness of numerical control machine tool | |
| CN117521346A (en) | Tolerance distribution analysis method based on digital twinning | |
| JP2011086024A (en) | Forming simulation system using numerical pattern, and recording medium | |
| Smith et al. | Discrete-event simulation and machine learning for prototype composites manufacture lead time predictions | |
| CN116204974B (en) | Method for evaluating geometric consistency of CAD model of aeroengine blade part | |
| Du et al. | Digital Twin Modeling Method for Assembly Quality Control of Complex Products | |
| Petruccioli et al. | Development of a Computer-Aided integrated method for the tolerance-cost multi-disciplinary optimization of an automotive engine |
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 |