CN116363336A - Low-damage-demand-oriented ring frame assembly virtual assembly and repair analysis method - Google Patents

Low-damage-demand-oriented ring frame assembly virtual assembly and repair analysis method Download PDF

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CN116363336A
CN116363336A CN202310329740.9A CN202310329740A CN116363336A CN 116363336 A CN116363336 A CN 116363336A CN 202310329740 A CN202310329740 A CN 202310329740A CN 116363336 A CN116363336 A CN 116363336A
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assembly
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ring frame
frame assembly
constraint
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张婷玉
钟扬
王亚辉
王洁
赵一搏
高远
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Aerospace Research Institute of Materials and Processing Technology
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Abstract

A ring frame assembly virtual assembly and repair analysis method facing low damage requirements is provided, wherein a system obtains an actual measurement model of a ring frame assembly through scanning, and virtual assembly and visual assembly guidance of the ring frame assembly are realized through four steps. Firstly, importing or establishing various types of data meeting virtual assembly and assembly visualization requirements by using a model data management module, and providing necessary data sources for the whole virtual assembly process; secondly, accurately extracting required assembly characteristics based on an assembly characteristic segmentation method of matching the geometric model and the physical scanning model; thirdly, registering the parts to obtain a reverse model close to the pose of the geometric model, positioning the scanning model to a theoretical assembly position, and providing a reference basis for subsequent assembly pose adjustment; and finally, carrying out assembly pose optimization solving on all the initially installed ring frame components by combining wall thickness constraint solving and a method for detecting collision interference among models, so as to obtain the optimal assembly pose meeting the assembly requirement.

Description

Low-damage-demand-oriented ring frame assembly virtual assembly and repair analysis method
Technical Field
The invention relates to a ring frame assembly virtual assembly and repair analysis method facing low damage requirements, and belongs to the technical field of virtual assembly of products.
Background
The ring frame component is a component assembled by a series of parts with larger forming errors, and is characterized in that the ring frame component still needs to be further processed after being assembled so as to meet the requirements of the shape and the structure of the ring frame component. The ring frame component is a typical ring frame component in an aerospace vehicle, is assembled by a plurality of box-shaped parts, is of an annular structure, and needs to be processed on the outer contour after assembly of the component so as to ensure the shape precision of the outer contour. The assembly of the assembly thus requires a sufficient machining allowance to be ensured so that the peripheral wall thickness dimension of each box-shaped part after machining meets the design requirements.
At present, the ring frame assembly mostly adopts the manual mode of assembly, and the part is initially installed and positioned after, carries out the repeated adjustment of part pose according to the assembly requirement, relies on assembly personnel's experience to the assembly process is very loaded down with trivial details, seriously influences the assembly efficiency of product. Therefore, an actual model of the ring frame assembly is obtained through digital scanning, an optimal assembly pose is analyzed and found through an intelligent algorithm, visual assembly and repair guidance is provided, and the method has important significance for efficient assembly of the ring frame assembly. However, because the molding error of the ring frame assembly is larger, how to use the actual model to rapidly provide an assembly guiding scheme through a visual means, so that the assembly clearance error requirement of the ring frame assembly is ensured, and the machining wall thickness requirement is met, which is an unsolved problem at present.
Disclosure of Invention
The invention solves the technical problems that: the method for virtually assembling and repairing the ring frame component for the low damage requirement overcomes the defects of the prior art, realizes virtual assembly based on an actually measured ring frame component model, effectively ensures the assembly gap and the processing wall thickness requirement between components, and provides visual assembly guidance.
The technical scheme of the invention is as follows: a ring frame assembly virtual assembly and repair analysis method facing low damage requirement comprises the following steps:
obtaining a ring frame assembly component physical model through optical three-dimensional scanning equipment and positioning assembly hole data;
registering the ring frame assembly component physical model with the geometric model sampled by the coordinate points to ensure that the pose of the ring frame assembly component physical model is consistent with that of the geometric model;
gradually dividing the ring frame assembly component physical model to obtain a divided assembly characteristic foundation;
according to the constraint conditions of the positioning holes and the positioning surfaces of the parts, the positioning constraint optimization solution is carried out on the ring frame assembly component physical model, and an accurate reference is provided for the assembly pose optimization calculation of the component;
based on the segmented assembly characteristic foundation, combining wall thickness constraint conditions after the outer contour of the ring frame assembly is cut and side wall interference constraint of parts in each ring frame assembly, constructing an assembly pose optimization model, solving the optimal assembly pose, calculating the repair guiding quantity of the side wall contact surface of the adjacent parts of the ring frame assembly and the part optimization positioning reference, designing an auxiliary assembly tool based on the optimization positioning reference, and optimizing the assembly efficiency.
Further, the registering between the physical model of the assembly component and the geometric model sampled by the coordinate points by using the ring frame comprises the following steps: and searching the most suitable space coordinate transformation matrix between the ring frame assembly component physical model and the geometric model to be registered in the same coordinate system, and realizing the registration of the geometric model and the ring frame assembly component physical model.
Further, the registration method comprises the following steps:
C target ＝RC source +t
wherein C is target For registered target geometric model, C source The ring frames to be registered are assembled with component physical models, and R and t are rotation and translation matrixes respectively.
Further, the step-by-step segmentation of the ring frame assembly component physical model comprises the following steps:
selecting a ring frame assembly component physical model to be segmented and a geometric model matched with the ring frame assembly component physical model, obtaining a closest point set corresponding to theoretical characteristics of the ring frame assembly component physical model in an iterative search mode, removing existing repeated points in the closest point set and storing the repeated points into an assembly characteristic set of the ring frame assembly component physical model, and obtaining rough assembly characteristics after the first segmentation after the maximum iteration number is reached;
and estimating an assembly characteristic mathematical model to be segmented by using a RANSAC segmentation method on the data set with the significant characteristics, and then carrying out iterative calculation until a model meeting the preset condition is estimated.
Further, the performing iterative calculation until a model meeting a preset condition is estimated, including:
selecting a minimum data set capable of estimating a mathematical model of corresponding assembly characteristics from a given ring frame assembly component physical model;
estimating mathematical parameter expression of the assembly characteristic model by utilizing the minimum data set, bringing data points of a given physical scanning model into the mathematical model, and selecting proper local points within an error allowable range;
judging whether the local points in the model meet the given requirement, if so, terminating the calculation process, otherwise, adopting the acquired local points to re-estimate the parameter model, and repeating the steps.
Further, the RANSAC method is utilized to remove irrelevant points, and the set of the local points after iterative computation obtains accurate assembly characteristics.
Further, the solving the optimal assembly pose includes:
the method comprises the steps of constructing the wall thickness constraint of the outline of the physical model of the ring frame assembly component, matching with the side collision interference constraint and the fitness function, carrying out iterative optimization to obtain the optimal pose of the physical scanning model meeting the assembly requirement, displaying the parameters of the cutting amount and the repairing parameters of the matching side of the ring frame component through a visual interface, and providing an assembly basis for the subsequent actual product assembly process.
Further, the outline wall thickness of the ring frame assembly real model is constrained to be that for each pair A and B
Figure BDA0004154537560000031
Wherein A is the outline feature to be detected, B is the geometric model feature corresponding to the outline feature to be detected, cut min 、Cut max Respectively minimum wall thickness and maximum wall thickness, th is wall thickness value after simulated cutting in virtual environment, a i 、b i I=1, 2, …, n, n is the number of feature planes for a pair of local feature planes corresponding to each other.
Further, the fit side impact interference constraint is Gap min ≤Col(C,D)≤Gap max The method comprises the steps of carrying out a first treatment on the surface of the Wherein Gap is formed by min 、Gap max The minimum gap and the maximum gap of the scan model matching surface features of the pair of parts are respectively calculated by Col in collision detection, and C, D is the scan model matching surface features of the pair of parts.
Further, the fitness function is
Figure BDA0004154537560000041
Wherein f is the fitness of the particle function, l is the number which does not meet the wall thickness constraint, alpha is the wall thickness constraint penalty coefficient, ψ is the wall thickness of the physical part, mu is the wall thickness constraint boundary value, m is the number of single particles which do not meet the collision requirement, beta is the collision constraint penalty coefficient, I and I are a group of corresponding matched surface features, p is the model number, and delta is the boundary value of the collision constraint.
According to the method, the optimal assembly scheme can be obtained quickly in a virtual assembly mode through the scanning model of the ring frame assembly, so that the assembly profile and wall thickness requirements of the ring frame assembly are guaranteed, and the side clearance requirements of each ring frame assembly are also guaranteed. Compared with the prior art, the invention has the advantages that:
(1) At present, the ring frame assembly mostly adopts the manual mode of assembly, and the part is initially installed and positioned after, carries out the repeated adjustment of part pose according to the assembly requirement, relies on assembly personnel's experience to the assembly process is very loaded down with trivial details, seriously influences the assembly efficiency of product. The invention can be combined with the scanning model of the ring frame assembly, can quickly find the optimal assembly scheme in the virtual environment, provides specific assembly guidance in a visual mode, and can effectively improve the assembly precision, efficiency and consistency of the ring frame assembly.
(2) According to the invention, the auxiliary assembly tool and the scanning model of the ring frame assembly body are utilized to optimize the assembly pose, so that the problem that the assembly position of an actual assembly is difficult to accurately position after virtual assembly is carried out by only utilizing the virtual model can be effectively solved.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
FIG. 1 Ring frame Assembly virtual Assembly overview frame
FIG. 2 virtual assembly flow of ring frame assembly
Figure 3 ring frame assembly physical scanning model
Fig. 4 registration process for physical scan model of ring frame assembly
FIG. 5 step-by-step segmentation of ring-frame assembly features based on CAD geometric model and RANSAC
FIG. 6 initial assembly of a genetic optimization-based ring-frame assembly model
FIG. 7 is a view of ring frame assembly mounting pose optimization taking wall thickness and interface interference constraints into consideration.
Detailed Description
In order to better understand the technical solutions described above, the following detailed description of the technical solutions of the present application is provided through the accompanying drawings and specific embodiments, and it should be understood that the specific features of the embodiments and embodiments of the present application are detailed descriptions of the technical solutions of the present application, and not limit the technical solutions of the present application, and the technical features of the embodiments and embodiments of the present application may be combined with each other without conflict.
The following is a description of a low-damage-requirement-oriented ring frame assembly virtual assembly and repair analysis method provided in the embodiments of the present application in detail with reference to the accompanying drawings, and a specific implementation manner may include (as shown in fig. 1 to 7):
firstly, a physical scanning model of a ring frame assembly is obtained by utilizing a three-dimensional scanning technology, a secondary segmentation method is adopted based on the physical scanning model, the physical scanning model is gradually segmented from thick to thin, accurate assembly characteristics are obtained, positioning constraint optimization is carried out according to the auxiliary positioning constraint condition of the ring frame assembly, and an accurate part model with an assembly relation is provided for assembly pose optimization calculation of the assembly; secondly, comprehensively considering assembly gaps and wall thickness constraints to optimize assembly pose; and finally, visually displaying the contact repair cloud image of the side wall of the part and the optimal assembly pose of the part, and manufacturing an auxiliary assembly positioning tool according to the optimal assembly pose so as to realize the rapid assembly of the real object. The method comprises the following specific steps:
(1) Data importation for ring frame assemblies
First, a physical model p= { P to be assembled is obtained by scanning with a scanner i |p i ∈R 3 I=1..the term, n }, a CAD geometric model q= { Q }, is imported j |q j ∈R 3 J=1,..m }, data support is provided for subsequent virtual assembly. Wherein n and m represent the ring frame assembly data of P and Q, respectively, P i And q j And respectively represent the ring frame components to be assembled of P and Q.
(2) Fitting feature registration
Registering the physical model and the CAD geometric model sampled by the coordinate points to enable the pose of the scanning model and the pose of the CAD geometric model to be close, and providing a calculation model for subsequent rapid segmentation.
(3) Assembly feature segmentation
Based on the physical scanning model, a secondary segmentation method is adopted to gradually segment the physical scanning model from thick to thin. Firstly, the matching relation between the assembly characteristics of the CAD geometric model and the scanning model is utilized to quickly divide the assembly characteristics to obtain the rough assembly characteristics. On the basis of the rapid segmentation, because a large number of fuzzy and redundant assembly features exist in the physical scanning model P of the ring frame assembly, redundancy and outliers of the assembly features, which cannot be reflected in the rough assembly features, are found out, and more accurate assembly features are obtained.
(4) Assembly feature positioning constraints
According to the constraint conditions of the positioning holes and the positioning surfaces of the parts, an iterative optimization algorithm is adopted to perform optimization solving of positioning constraint on the physical scanning model, so that the inverse reconstruction calculation process can be effectively reduced, the calculation efficiency is improved, and an accurate reference is provided for the assembly pose optimization calculation of the component.
(5) Assembly pose optimization
Aiming at the characteristic that the whole external contour is required to be processed after the assembly of the ring frame assembly, on the basis of the fine-segmentation assembly characteristics, the wall thickness constraint condition after the external contour of the ring frame assembly is cut and the side wall interference constraint of the parts in each ring frame assembly are comprehensively considered, an assembly pose optimization model is constructed, the optimal assembly pose is solved through an optimization iterative algorithm, the assembly guiding quantity of the side wall contact surface of the adjacent parts of the ring frame assembly and the part optimization positioning reference are further visually displayed, and an auxiliary assembly tool is designed based on the optimization positioning reference, so that efficient assembly is realized.
In the scheme provided by the embodiment of the application, the virtual assembly and repair method and system for the ring frame component facing the low damage requirement are shown in fig. 1, and include an equipment layer, a model layer and an interaction layer, wherein the equipment layer is a physical equipment and the ring frame component required by executing an assembly process, the model layer provides an algorithm and a model required by the virtual assembly and repair scheme, the interaction layer is used for realizing the virtual assembly process and the assembly and repair guidance scheme of the visual display ring frame component through man-machine interaction, and the detailed implementation process of the system is shown in fig. 2, and the specific steps are as follows:
the first step: the ring frame assembly is obtained by an optical three-dimensional scanning device ATOS Q12M scanner as shown in FIG. 3, a CAD model of the ring frame assembly is imported, and assembly hole data for positioning.
And a second step of: and (3) searching the most suitable space coordinate transformation matrix between a group of scanning models to be registered and the CAD geometric model under the same coordinate system through a registration process shown in a formula (1) and a figure 4, and realizing the registration of the CAD geometric model and the physical scanning model. Wherein C is target For registered target CAD model, C source And (3) scanning a model for the ring frame assembly to be registered, wherein R and t are rotation and translation matrixes respectively.
C target ＝RC source +t(1)
And a third step of: based on the registration model, a physical scanning model is gradually segmented from thick to thin by adopting a secondary segmentation method of feature segmentation based on CAD geometric model and feature segmentation based on random uniform sampling (RANSAC), detailed steps are shown in figure 5,
(1) Selecting a physical scanning model M requiring rapid segmentation S And a CAD geometric model F matched with the model k (comprising theoretical assembly characteristics), then obtaining a closest point set corresponding to the actual scanning model and the theoretical characteristics through an iterative search mode, removing the existing repeated points and storing the repeated points into the assembly characteristics set of the physical scanning model. After the maximum number of iterations is reached (generally defined as the total number of points of the theoretical assembly feature), the rapidly segmented rough assembly feature is obtained.
(2) The assembly feature mathematical model to be segmented is estimated for the data set with the significant features by the RANSAC segmentation method, and then iterative calculation is carried out until a better model is estimated, and the specific implementation method can be realized by the following steps:
1) From a given physical scan model, selecting a minimum data set (MSS) from which a corresponding assembly feature mathematical model (such as straight line, plane, cylinder, cone, etc.) can be estimated;
2) Estimating a mathematical parameter representation of the assembled feature model using the minimum data set, bringing data points of a given physical scan model into the mathematical model, and selecting appropriate "local points" within the tolerance range;
3) Judging whether the 'local point' in the model meets the given requirement, if so, terminating the calculation process, otherwise, adopting the acquired 'local point' to re-estimate the parameter model, and repeating the steps.
And removing irrelevant points by using a RANSAC method, and obtaining accurate assembly characteristics by iterating the calculated 'local points' set.
Fourth step: based on the accurate assembly feature segmentation model, the auxiliary tool positioning features and the constraint relation, iterative optimization calculation is performed by adopting a genetic algorithm to construct an optimal space transformation matrix, and assembly positioning of the positioning constraint of the model of the ring frame assembly is completed, wherein the specific steps are shown in fig. 6.
Fifth step: and constructing a pose optimization model meeting the assembly requirements of the ring frame assembly, adopting a self-adaptive Particle Swarm Optimization (PSO), and carrying out optimization iterative computation by comprehensively considering a wall thickness constraint solving method of the ring frame assembly and a collision detection method considering side interference of the ring frame assembly to obtain the optimal assembly pose, wherein the specific steps are shown in figure 7.
(1) Outer contour wall thickness constraint construction of ring frame assembly
Assuming that the outer contour feature to be detected is A, the corresponding CAD geometric model feature is B, knowing the wall thickness A of the real part, defining Th (A, B, psi) as a wall thickness constraint calculation mode mixed with the plane and cylindrical curved surface features, and returning to the wall thickness value after simulated cutting in the virtual environment.
Figure BDA0004154537560000081
In the formula (2), plane (A, B, psi) is a plane feature, circle (A, B) is a calculation method of a cylindrical curved surface feature, and the existing wall thickness constraint is as follows:
Cut min ≤Th(A,B,Ψ)≤Cut max (3)
wherein Cut min Cut is the minimum wall thickness max Is the maximum wall thickness. Maximum wallThe thickness and the minimum wall thickness are preset values, and are required to be selected according to actual assembly requirements. In practice, there may be a plurality of features on the outer contoured surface of a single part, where the feature surface may be broken down into a plurality of local feature surfaces. Assuming a number of n sub-features, decomposing the features to a= { a 0 ,...,a n },B＝{b 0 ,...,b n (wherein a) i And b i For a pair of mutually corresponding local feature surfaces, then the wall thickness constraint of the outer contour feature can be rewritten as:
for each pair A and B
Figure BDA0004154537560000082
(2) Construction of ring frame assembly matched with side collision interference constraint
Since the mating surface is a planar feature, no feature decomposition is required. Assuming that the scan pattern mating surface features of a pair of parts are C and D, respectively, the maximum Gap is Gap max The minimum Gap is Gap min Both values are chosen according to the requirements of the actual assembly. Defining the collision detection operation as Col (C, D), then the constraint relationship that exists for each pair of mating surface features is as follows:
Gap min ≤Col(C,D)≤Gap max (5)
(3) Fitness function construction
For the construction of the particle function fitness f, it is known from the optimization model that individual particles need to meet the wall thickness constraints of the part and the side impact spacing requirements of the assembly. Assuming that for the number of models p, n pairs of single particles which do not meet the wall thickness constraint and m pairs of single particles which do not meet the collision requirement exist, giving a penalty exceeding a constraint boundary value to a certain proportion, finally searching to obtain an optimal particle (a group of optimal variables) with the minimum fitness value of the function, and constructing a fitness function as shown in a formula (6), wherein alpha is a wall thickness constraint penalty coefficient, A and B are a group of outer contour features in the part, the wall thickness psi of the real part is a wall thickness constraint boundary value, th (A, B) function calculates the cutting quantity of the outer contour, beta is a collision constraint penalty coefficient, I and I are a group of corresponding matched surface features, and delta is a boundary value of the collision constraint.
Figure BDA0004154537560000091
Based on the outer contour wall thickness constraint of the ring frame assembly, the cooperation of the side collision interference constraint and the construction of the fitness function, the optimal pose of the real object scanning model meeting the assembly requirement is finally obtained through iterative optimization, and the parameters of the cutting amount and the repair parameters of the cooperation of the ring frame assembly and the side are displayed through a visual interface, so that an assembly basis is provided for the subsequent actual product assembly process.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the spirit or scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to cover such modifications and variations.
What is not described in detail in the present specification is a well known technology to those skilled in the art.

Claims (10)

1. A ring frame assembly virtual assembly and repair analysis method facing low damage requirement is characterized by comprising the following steps:
obtaining a ring frame assembly component physical model through optical three-dimensional scanning equipment and positioning assembly hole data;
registering the ring frame assembly component physical model with the geometric model sampled by the coordinate points to ensure that the pose of the ring frame assembly component physical model is consistent with that of the geometric model;
gradually dividing the ring frame assembly component physical model to obtain a divided assembly characteristic foundation;
according to the constraint conditions of the positioning holes and the positioning surfaces of the parts, the positioning constraint optimization solution is carried out on the ring frame assembly component physical model, and an accurate reference is provided for the assembly pose optimization calculation of the component;
based on the segmented assembly characteristic foundation, combining wall thickness constraint conditions after the outer contour of the ring frame assembly is cut and side wall interference constraint of parts in each ring frame assembly, constructing an assembly pose optimization model, solving the optimal assembly pose, calculating the repair guiding quantity of the side wall contact surface of the adjacent parts of the ring frame assembly and the part optimization positioning reference, designing an auxiliary assembly tool based on the optimization positioning reference, and optimizing the assembly efficiency.
2. The method for virtual assembly and repair analysis of a ring frame assembly for low damage requirements according to claim 1, wherein the registering of the physical model of the ring frame assembly with the geometric model sampled by the coordinate points comprises: and searching the most suitable space coordinate transformation matrix between the ring frame assembly component physical model and the geometric model to be registered in the same coordinate system, and realizing the registration of the geometric model and the ring frame assembly component physical model.
3. The method for virtual assembly and repair analysis of a low-damage-demand ring frame assembly according to claim 2, wherein the method for registration is as follows:
C target ＝RC source +t
wherein C is target For registered target geometric model, C source The ring frames to be registered are assembled with component physical models, and R and t are rotation and translation matrixes respectively.
4. The method for virtually assembling and repairing and analyzing the ring frame assembly for the low damage requirement according to claim 1, wherein the step-by-step division of the physical model of the ring frame assembly comprises the steps of:
selecting a ring frame assembly component physical model to be segmented and a geometric model matched with the ring frame assembly component physical model, obtaining a closest point set corresponding to theoretical characteristics of the ring frame assembly component physical model in an iterative search mode, removing existing repeated points in the closest point set and storing the repeated points into an assembly characteristic set of the ring frame assembly component physical model, and obtaining rough assembly characteristics after the first segmentation after the maximum iteration number is reached;
and estimating an assembly characteristic mathematical model to be segmented by using a RANSAC segmentation method on the data set with the significant characteristics, and then carrying out iterative calculation until a model meeting the preset condition is estimated.
5. The method for virtual assembly and repair analysis of a low-damage-demand ring-frame assembly according to claim 4, wherein the performing the iterative calculation until a model meeting a preset condition is estimated comprises:
selecting a minimum data set capable of estimating a mathematical model of corresponding assembly characteristics from a given ring frame assembly component physical model;
estimating mathematical parameter expression of the assembly characteristic model by utilizing the minimum data set, bringing data points of a given physical scanning model into the mathematical model, and selecting proper local points within an error allowable range;
judging whether the local points in the model meet the given requirement, if so, terminating the calculation process, otherwise, adopting the acquired local points to re-estimate the parameter model, and repeating the steps.
6. The method for virtually assembling and repairing a ring frame assembly with low damage requirements according to claim 5, wherein the RANSAC method is used to remove irrelevant points, and the iterative computation of the set of local points obtains accurate assembly characteristics.
7. The method for virtual assembly and repair analysis of a low-damage-demand-oriented ring frame assembly according to claim 1, wherein the solving the optimal assembly pose comprises:
the method comprises the steps of constructing the wall thickness constraint of the outline of the physical model of the ring frame assembly component, matching with the side collision interference constraint and the fitness function, carrying out iterative optimization to obtain the optimal pose of the physical scanning model meeting the assembly requirement, displaying the parameters of the cutting amount and the repairing parameters of the matching side of the ring frame component through a visual interface, and providing an assembly basis for the subsequent actual product assembly process.
8. The method for virtually assembling and repairing a ring frame assembly with low damage requirement according to claim 7, wherein the ring frame assembly physical model outer contour wall thickness constraint is that for each pair a and B
Figure FDA0004154537550000031
Wherein A is the outline feature to be detected, B is the geometric model feature corresponding to the outline feature to be detected, cut min 、Cut max Respectively minimum wall thickness and maximum wall thickness, th is wall thickness value after simulated cutting in virtual environment, a i 、b i I=1, 2, …, n, n is the number of feature planes for a pair of local feature planes corresponding to each other.
9. The method for virtually assembling and repairing a low-damage-requirement-oriented ring-frame assembly according to claim 7, wherein the matched side-collision interference constraint is Gap min ≤Col(C,D)≤Gap max The method comprises the steps of carrying out a first treatment on the surface of the Wherein Gap is formed by min 、Gap max The minimum gap and the maximum gap of the scan model matching surface features of the pair of parts are respectively calculated by Col in collision detection, and C, D is the scan model matching surface features of the pair of parts.
10. The method for virtually assembling and repairing a low-damage-demand ring-frame assembly according to claim 7, wherein the fitness function is
Figure FDA0004154537550000032
Wherein f is the fitness of the particle function, l is the number which does not meet the wall thickness constraint, alpha is the wall thickness constraint penalty coefficient, ψ is the wall thickness of the physical part, mu is the wall thickness constraint boundary value, m is the number of single particles which do not meet the collision requirement, beta is the collision constraint penalty coefficient, I and I are a group of corresponding matched surface features, p is the model number, and delta is the boundary value of the collision constraint.
CN202310329740.9A 2023-03-30 2023-03-30 Low-damage-demand-oriented ring frame assembly virtual assembly and repair analysis method Pending CN116363336A (en)

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