Assembly coordination error optimization method and system for segmented wing structure based on spatial dimension chain

Abstract

The present invention provides a method and system for optimizing the assembly coordination error of a segmented wing structure based on a space dimension chain. The method for optimizing the assembly coordination error of a segmented wing structure realizes the accurate construction of the assembly coordination dimension chain and the quantitative analysis of the assembly error transmission accumulation result through the assembly coordination error transmission accumulation and coordination dimension chain construction, the assembly tolerance optimization model construction and the intelligent solution technology, thereby providing a data basis for the tolerance optimization design of the spacecraft structure assembly process; by establishing and solving an efficient and accurate function model that can express the correlation between the manufacturing performance and the digital model, the reasonable distribution of the assembly dimension chain tolerance is realized, the assembly performance is improved, and the repair amount and manufacturing cost in the assembly process are reduced, etc.

Description

[Technical field]

[0001] The present invention relates to the technical field of digital assembly coordination process in aerospace manufacturing, and in particular to a method and system for optimizing assembly coordination errors of a segmented wing structure based on a space dimension chain. [Background technology]

[0002] Aerospace products have complex structures, especially for segmented wing structures. The wing components are usually connected at the connecting strips by multi-hole matching. The docking intersections between the wing segments and the fuselage as a whole mainly adopt hole-shaft matching, and locally adopt hole-shaft-hole double matching surfaces. The fork ears are connected by two pin holes, and there are perpendicular fork ear matching spatial directions. In addition, while meeting the appearance assembly accuracy of each wing component segment, it is also necessary to ensure the coordination of the entire wing product and the fuselage product at the docking intersection. There are many high-requirement multiple assembly coordination accuracy indicators in the form of step difference, gap, etc. The assembly of such products belongs to the scope of comprehensive coordination of appearance and multiple spatial intersections. The coordination relationship is extremely complex, and the comprehensive coordination of the two is difficult. In actual production, a large amount of manual repair work is required, the assembly efficiency is low, and repair operations such as grinding and padding can easily cause damage to the product and reduce its mechanical properties.

[0003] In the assembly process of aerospace products, the accurate establishment of the assembly error dimension chain and the distribution control of each error link are important factors in the optimization design of the spacecraft assembly process and the guarantee of assembly coordination accuracy. By constructing the assembly dimension chain, the assembly quality can be predicted in advance and the key links in the assembly process can be quickly identified, so as to achieve accurate guarantee of the spacecraft assembly error in the process flow. The construction and optimization distribution of the assembly error space dimension chain mainly includes two parts: ① Realize the accurate prediction and calculation of the space assembly coordination dimension chain and the quantitative analysis of the cumulative results of assembly error transmission, so as to provide a data basis for the optimization design of assembly process tolerance; ② Construct an assembly tolerance optimization model and use an intelligent solution to calculate, obtain the optimized values ​​of each part, and provide optimized input data for the iterative simulation analysis of the assembly coordination dimension chain. With the continuous improvement of the quality and efficiency requirements of aerospace products, for the segmented wing structure with complex assembly and coordination relationship, there are currently technical difficulties such as lack of quantitative guidance analysis in the formulation of assembly process plan, inability to predict the cumulative transmission results of assembly errors between wing shape and intersection connection structure in advance, huge workload of repair coordination, and unreasonable assembly tolerance allocation. In particular, for the coordination errors between complex assemblies with spatial angles, a single two-dimensional dimension chain cannot reflect the transmission formation process and cumulative results of multiple key assembly coordination errors such as step difference and gap of the segmented wing structure, which leads to the inability to achieve the goals of precision coordination between the shapes of multi-segment wing components and smooth docking between multiple intersections. Therefore, in order to implement refined dimension management in the final assembly plant and provide theoretical calculation and simulation guidance for the improvement of wing assembly performance, it is necessary to construct a spatial dimension chain reflecting multiple key assembly error indicators such as step difference and gap for the segmented wing docking structure, and optimize and control the key error component links involved, so that the assembly results can achieve the expected high-performance technical indicators.

[0004] Therefore, it is necessary to study a segmented wing structure assembly coordination error optimization method and system based on spatial dimension chain to address the shortcomings of the existing technology and to solve or alleviate one or more of the above problems. [Summary of the invention]

[0005] In view of this, the present invention provides a method and system for optimizing the assembly coordination error of a segmented wing structure based on a spatial dimension chain, which can realize the precise construction of the assembly coordination dimension chain and the quantitative analysis of the cumulative results of assembly error transmission, and provide a data basis for the optimization design of the assembly process tolerance of the segmented wing structure of a spacecraft; by establishing and solving an efficient and accurate function model that can express the correlation between assembly performance and a digital model, a reasonable allocation of the assembly dimension chain tolerance is achieved, the assembly performance is improved, and the effects of reducing the amount of repairs and manufacturing costs during the assembly process, etc. are achieved.

[0006] On the one hand, the present invention provides a segmented wing structure assembly coordination error optimization method based on a spatial dimension chain, which is used to optimize the assembly coordination process of the segmented wing structure. The segmented wing structure assembly coordination error optimization method comprises the following steps:

[0007] S1: Analyze the assembly error coupling relationship of each component in the segmented wing structure, and establish a nonlinear transfer path model of assembly coordination errors between components based on the analysis results of the assembly error coupling relationship;

[0008] S2: Preset key measuring points on each component, and establish the assembly feature geometric error variation model of all key measuring points based on the nonlinear transfer path model of assembly coordination errors between components;

[0009] S3: Analyze the basic error sources and interaction relationships in the assembly coordination process and the assembly characteristics of the segmented wing, and construct a spatial assembly coordination dimension chain with multi-directional cross-transfer characteristics;

[0010] S4: Based on the nonlinear transfer path model in S1, the assembly feature geometric error variation model in S2, and the spatial assembly coordinated dimension chain in S3, a multi-process assembly error transfer and coordination error accumulation model for complex segmented wing products is established;

[0011] S5: Based on the multi-process assembly error transmission and accumulation model of complex segmented wing products in S4, an assembly error sensitivity analysis model is established and the key assembly links are identified and obtained;

[0012] S6: Based on the key assembly links and assembly error sensitivity analysis model in S5, a multi-objective coordinated optimization allocation model for assembly tolerance is established;

[0013] S7: Substitute the assembly tolerance multi-objective coordinated optimization allocation model into the intelligent algorithm for iterative solution to obtain the optimal segmented wing structure assembly coordination error allocation value.

[0014] According to the above aspects and any possible implementation manner, an implementation manner is further provided, wherein S1 specifically includes:

[0015] S11: according to the structure of the spacecraft product, analyzing the matching error type information, assembly element information and structural form information between the components of the segmented wing structure to be assembled on the spacecraft;

[0016] S12: defining assembly process planning content according to the matching error type information, assembly element information and structural form information, wherein the assembly process planning content includes: positioning, reference, connection, sequence, tolerance analysis and error analysis;

[0017] S13: constructing a three-dimensional assembly model of the object to be assembled according to the time sequence of the assembly process planning content;

[0018] S14: A nonlinear transfer path model of assembly coordination errors between components is constructed through the three-dimensional assembly model of the object to be assembled, search technology and graphics theory.

[0019] According to the above aspects and any possible implementation manner, an implementation manner is further provided, wherein S2 specifically includes:

[0020] S21: Through the nonlinear transfer path model and search technology of assembly coordination errors between various components and graphics theory, the assembly geometric error transfer path model construction and the expression of multi-directional transfer relationship view are obtained;

[0021] S22: Based on the measurement data of preset key measuring points, the error screw model of key geometric features on each section of the wing under the constraints of dimensional dimensions and geometric tolerances is obtained through the assembly coordination error transfer path model and the expression of the transfer relationship view;

[0022] S23: According to the error variation direction of the matching surfaces of the geometric features of the multi-segment wings and the error screw model of the key geometric features on each wing segment under the common constraints of the dimensional metric and the form and position tolerance, the assembly feature geometric error variation model of all key measuring points is established.

[0023] According to the aspects and any possible implementation methods described above, an implementation method is further provided, wherein the key measuring points in S22 are to first obtain the limited requirements of the plane, position, gap and step difference between the components after the wing is assembled, decompose the limited requirements item by item into measurable or calculable point information, and then perform measurement feature extraction to obtain the key measuring points and the corresponding key geometric features.

[0024] According to the aspects and any possible implementation methods described above, an implementation method is further provided, in which the error spin model of the key geometric features on each section of the wing under the joint constraints of dimensional tolerance and form and position tolerance in S22 is specifically: using kinematic theory and small displacement spinor method, the positions and deformation changes of typical straight lines, planes, spatial surfaces and other geometric features contained in the components of the assembly object are mathematically expressed and described, and mapped to the tolerance domain, and then the error spin model of the geometric features of each section of the wing under the joint constraints of dimensional tolerance and form and position tolerance is derived.

[0025] According to the above aspects and any possible implementation, an implementation is further provided, wherein S3 specifically includes:

[0026] S31: Based on the analysis of the basic error sources and their interaction in the assembly coordination process and the assembly characteristics of the segmented wing, determine the influencing factors of the assembly error, where the influencing factors include dimensional tolerance and assembly process links;

[0027] S32: According to the range of geometric deviation and tolerance domain, determine the range of position and posture variation of the assembled parts, define the coordinated reference transformation process, determine the position and posture variation of the subsequent parts during assembly, and then model and determine the final assembly error;

[0028] S33: According to the process steps of the assembly coordination process, the error transmission model is carried out for each coordination control link, and a spatial assembly coordination dimension chain with multi-directional cross-transmission characteristics is constructed.

[0029] According to the above aspects and any possible implementation, an implementation is further provided, wherein S4 specifically includes:

[0030] S41: Clarify the error transmission direction and transmission path, build the assembly error transmission network of the assembly object, clarify the key dimension transmission chain and calculate the assembly error variation range;

[0031] S42: Analyze the error transmission of a key section of the assembly object in the current process step through the spatial assembly coordinated dimension chain, and the inheritance and transmission relationship of errors between different processes when different components are assembled, and obtain the error transmission direction and transmission path in the complex product multi-process assembly error transmission and coordinated error accumulation model;

[0032] S43: The nonlinear transfer characteristics and accumulation law of the error are obtained by the Monte Carlo method, and the variation range and distribution law of the assembly error in the three-dimensional space are further obtained, and then the error mean is statistically calculated.

[0033] According to the above aspects and any possible implementation manner, an implementation manner is further provided, wherein S5 specifically includes:

[0034] S51: Based on the three-dimensional dimension chain of the product to be assembled and the nonlinear transmission path of the assembly coordination error, the three-dimensional dimension chain is appropriately simplified, and the spatial assembly dimension chain is spatially decomposed. The corresponding characteristics of the assembly index are traced back to the assembly datum of each wing component, and the closed-loop construction of the error transmission link is completed to obtain a planar two-dimensional dimension chain that can reflect the assembly quality index.

[0035] S52: geometrically analyze the two-dimensional dimension chain that can reflect the assembly quality index, draw a schematic diagram of the dimension chain, clarify the functional relationship between the closed loop and each component loop on this basis, establish multiple independent variables, and then establish a plane dimension chain function equation;

[0036] S53: Establish an error total differential model for the plane dimension chain equation, calculate and obtain the comprehensive and cumulative errors of each component ring, and the derivative of the closed loop to each component ring represents the sensitivity coefficient of each component ring. The relative contribution is expressed as the ratio of the sensitivity coefficient of a component ring to the sum of the sensitivity coefficients of all component rings, thereby preliminarily obtaining the error sensitivity of the dimension chain;

[0037] S54: Based on the sensitivity and contribution calculated preliminarily in S53, analyze the influence and causes of each component ring, determine the key errors and dimensional links that affect assembly accuracy, and provide quantitative guidance for subsequent tolerance allocation optimization.

[0038] According to the above aspects and any possible implementation manner, an implementation manner is further provided, wherein S6 specifically includes:

[0039] S61: Describe and quantify the actual requirements of segmented wing assembly, construct multiple single-objective optimization functions, and set weight parameters for each according to functional requirements;

[0040] S62: fusion modeling of multiple single-objective optimization functions, establishment of the main optimization function, and setting of a series of constraint conditions;

[0041] S63: Taking the main optimization function as the core, supplementing design variables, constraints and other elements, a multi-objective coordinated optimization allocation model for assembly tolerance is constructed.

[0042] According to the aspects described above and any possible implementation method, a segmented wing structure assembly coordination error optimization system based on a spatial dimension chain is further provided, wherein the optimization system comprises a memory and a processor, wherein the memory is connected to the processor, and the segmented wing structure assembly coordination error optimization method is stored in the memory.

[0043] Compared with the prior art, the present invention can achieve the following technical effects:

[0044] 1) Construct a nonlinear transmission path model of the assembly error of the segmented wing structure, form a spatial assembly coordinated dimension chain with multi-directional cross-transmission characteristics, and realize the precise construction of the assembly error transmission and accumulation model;

[0045] 2) Construct an assembly error sensitivity analysis model and determine the key assembly links, obtain the transfer coefficient, contribution degree and other values ​​of each dimensional and geometric error link, realize the quantitative analysis of the error sensitivity of the component ring to the assembly performance index, and guide the subsequent tolerance optimization work;

[0046] 3) By establishing multiple single-objective tolerance optimization models and integrating them by determining the weight parameters of each model and imposing constraints, the reasonable distribution of assembly dimension chain tolerances can be achieved, the assembly performance can be improved, and the repair volume and manufacturing cost in the assembly process can be reduced.

[0047] Of course, any product implementing the present invention does not necessarily need to achieve all of the above-mentioned technical effects at the same time.

Brief Description of the Drawings

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1 It is a flow chart of construction and optimization of assembly error space dimension chain provided by one embodiment of the present invention;

[0050] Figure 2 It is a step difference dimension chain diagram of a segmented wing assembly provided by an embodiment of the present invention;

[0051] Figure 3 It is a chain diagram of the gap dimensions for sectional wing assembly provided by one embodiment of the present invention. [Specific implementation method]

[0052] In order to better understand the technical solution of the present invention, the embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0053] It should be clear that the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0055] The present invention provides a segmented wing structure assembly coordination error optimization method and system based on a space dimension chain, which are used to optimize the assembly coordination process of the segmented wing structure. The segmented wing structure assembly coordination error optimization method comprises the following steps:

[0056] S1: Analyze the assembly error coupling relationship of each component in the segmented wing structure, and establish a nonlinear transfer path model of assembly coordination errors between components based on the analysis results of the assembly error coupling relationship;

[0057] S2: Preset key measuring points on each component, and establish the assembly feature geometric error variation model of all key measuring points based on the nonlinear transfer path model of assembly coordination errors between components;

[0058] S3: Analyze the basic error sources and interaction relationships in the assembly coordination process and the assembly characteristics of the segmented wing, and construct a spatial assembly coordination dimension chain with multi-directional cross-transfer characteristics;

[0059] S4: Based on the nonlinear transfer path model in S1, the assembly feature geometric error variation model in S2, and the spatial assembly coordinated dimension chain in S3, a multi-process assembly error transfer and coordination error accumulation model for complex segmented wing products is established;

[0060] S5: Based on the multi-process assembly error transmission and accumulation model of complex segmented wing products in S4, an assembly error sensitivity analysis model is established and the key assembly links are identified and obtained;

[0061] S6: Based on the key assembly links and assembly error sensitivity analysis model in S5, a multi-objective coordinated optimization allocation model for assembly tolerance is established;

[0062] S7: Substitute the assembly tolerance multi-objective coordinated optimization allocation model into the intelligent algorithm for iterative solution to obtain the optimal segmented wing structure assembly coordination error allocation value.

[0063] The S1 specifically includes:

[0064] S11: according to the structure of the spacecraft product, analyzing the matching error type information, assembly element information and structural form information between the components of the segmented wing structure to be assembled on the spacecraft;

[0065] S12: defining assembly process planning content according to the matching error type information, assembly element information and structural form information, wherein the assembly process planning content includes: positioning, reference, connection, sequence, tolerance analysis and error analysis;

[0066] S13: constructing a three-dimensional assembly model of the object to be assembled according to the time sequence of the assembly process planning content;

[0067] S14: A nonlinear transfer path model of assembly coordination errors between components is constructed through the three-dimensional assembly model of the object to be assembled, search technology and graphics theory.

[0068] The S2 specifically includes:

[0069] S21: Through the nonlinear transfer path model and search technology and graphics theory between the assembly coordination errors of various components, the assembly geometric error transfer path model construction and the expression of the multi-directional transfer relationship view are obtained;

[0070] S22: Based on the measurement data of preset key measuring points, the error screw model of key geometric features on each section of the wing under the constraints of dimensional dimensions and geometric tolerances is obtained through the assembly coordination error transfer path model and the expression of the transfer relationship view;

[0071] S23: According to the error variation direction of the matching surfaces of the geometric features of the multi-segment wings and the error screw model of the key geometric features on each wing segment under the common constraints of the dimensional metric and the form and position tolerance, the assembly feature geometric error variation model of all key measuring points is established.

[0072] The key measuring points in S22 are to first obtain the limited requirements of the plane, position, gap and step difference between the components after the wing is assembled, decompose the limited requirements item by item into measurable or calculable point information, and then perform measurement feature extraction to obtain the key measuring points and the corresponding key geometric features.

[0073] The error screw model of the key geometric features on each section of the wing in S22 under the joint constraints of dimensional tolerance and form and position tolerance is specifically: using kinematic theory and small displacement screw method, the positions and deformation changes of typical straight lines, planes, spatial surfaces and other geometric features contained in the components of the assembly object are mathematically expressed and described, and mapped to the tolerance domain, and then the error screw model of the geometric features of each section of the wing under the joint constraints of dimensional tolerance and form and position tolerance is derived.

[0074] The S3 specifically includes:

[0075] S31: Based on the analysis of the basic error sources and their interaction in the assembly coordination process and the assembly characteristics of the segmented wing, determine the influencing factors of the assembly error, where the influencing factors include dimensional tolerance and assembly process links;

[0076] S32: According to the range of geometric deviation and tolerance domain, determine the range of position and posture variation of the assembled parts, define the coordinated reference transformation process, determine the position and posture variation of the subsequent parts during assembly, and then model and determine the final assembly error;

[0077] S33: According to the process steps of the assembly coordination process, the error transmission model is carried out for each coordination control link, and a spatial assembly coordination dimension chain with multi-directional cross-transmission characteristics is constructed.

[0078] The S4 specifically includes:

[0079] S41: Clarify the error transmission direction and transmission path, build the assembly error transmission network of the assembly object, clarify the key dimension transmission chain and calculate the assembly error variation range;

[0080] S42: Analyze the error transmission of a key section of the assembly object in the current process step through the spatial assembly coordinated dimension chain, and the inheritance and transmission relationship of errors between different processes when different components are assembled, and obtain the error transmission direction and transmission path in the complex product multi-process assembly error transmission and coordinated error accumulation model;

[0081] S43: The nonlinear transfer characteristics and accumulation law of the error are obtained by the Monte Carlo method, and the variation range and distribution law of the assembly error in the three-dimensional space are further obtained, and then the error mean is statistically calculated.

[0082] The S5 specifically includes:

[0083] S51: Based on the three-dimensional dimension chain of the product to be assembled and the nonlinear transmission path of the assembly coordination error, the three-dimensional dimension chain is appropriately simplified, and the spatial assembly dimension chain is spatially decomposed. The corresponding characteristics of the assembly index are traced back to the assembly datum of each wing component, and the closed-loop construction of the error transmission link is completed to obtain a planar two-dimensional dimension chain that can reflect the assembly quality index.

[0084] S52: geometrically analyze the two-dimensional dimension chain that can reflect the assembly quality index, draw a schematic diagram of the dimension chain, clarify the functional relationship between the closed loop and each component loop on this basis, establish multiple independent variables, and then establish a plane dimension chain function equation;

[0085] S53: Establish an error total differential model for the plane dimension chain equation, calculate and obtain the comprehensive and cumulative errors of each component ring, and the derivative of the closed loop to each component ring represents the sensitivity coefficient of each component ring. The relative contribution is expressed as the ratio of the sensitivity coefficient of a component ring to the sum of the sensitivity coefficients of all component rings, thereby preliminarily obtaining the error sensitivity of the dimension chain;

[0086] S54: Based on the sensitivity and contribution calculated preliminarily in S53, analyze the influence and causes of each component ring, determine the key errors and dimensional links that affect assembly accuracy, and provide quantitative guidance for subsequent tolerance allocation optimization.

[0087] The S6 specifically includes:

[0088] S61: Describe and quantify the actual requirements of segmented wing assembly, construct multiple single-objective optimization functions, and set weight parameters for each according to functional requirements;

[0089] S62: fusion modeling of multiple single-objective optimization functions, establishment of the main optimization function, and setting of a series of constraint conditions;

[0090] S63: Taking the main optimization function as the core, supplementing design variables, constraints and other elements, a multi-objective coordinated optimization allocation model for assembly tolerance is constructed.

[0091] The present invention also provides a segmented wing structure assembly coordination error optimization system based on a spatial dimension chain. The optimization system includes a memory and a processor. The memory is connected to the processor, and the segmented wing structure assembly coordination error optimization method is stored in the memory.

[0092] like Figure 1 As shown, the method of the present invention comprises the following steps:

[0093] Step 1: Establish a nonlinear transfer path model of coordination error based on assembly error coupling relationship analysis;

[0094] Step 2: Establish an assembly feature geometric error variation model based on key measuring points;

[0095] Step 3: Construct a spatial assembly coordinated dimension chain with multi-directional cross-transfer characteristics;

[0096] Step 4: Establish the multi-process assembly error transfer and coordination error accumulation model of complex segmented wing products;

[0097] Step 5: Establish an assembly error sensitivity analysis model and identify key assembly links;

[0098] Step 6: Establish a multi-objective coordinated optimization allocation model for assembly tolerance;

[0099] Step 7: Substitute the above model into the intelligent algorithm for iterative solution.

[0100] The specific expression of the nonlinear transfer path model in step 1 is:

[0101] According to the structure of the spacecraft product, the information such as the type of matching error, assembly elements, structural form, etc. between the key components of the spacecraft product to be assembled is analyzed, and the assembly process planning contents such as positioning, benchmark, connection, sequence, tolerance analysis and error analysis are defined based on this. The time sequence factors of the assembly process are integrated to realize the construction of the three-dimensional assembly model of the object to be assembled, thereby completing the construction of the nonlinear transfer path model of assembly error and assembly coordination error.

[0102] In the step 1, based on the search technology and graphics theory, the assembly geometric error transfer path model is constructed and the transfer relationship view is expressed.

[0103] In the method for constructing the assembly feature geometric error model in step 2, based on the matching technology of key measuring points and based on the measurement data of key measuring points, the error spinor model of the key geometric features on each section of the wing under the joint constraints of dimensional tolerance and form and position tolerance is derived, and according to the error change direction of the matching surfaces of the geometric features of multiple sections of the wing, a multi-source assembly error source change model is established.

[0104] The key measuring points in step 2 are to decompose these requirements into measurable or calculable point information item by item according to the requirements for the plane, position, gap, step difference, etc. between the components after the wing is assembled, and to extract the measurement features.

[0105] In the second step, kinematic theory and small displacement screw method are used to mathematically express and describe the positions and deformation changes of typical straight lines, planes, spatial surfaces and other geometric features contained in the components of the assembly object, and map them to the tolerance domain. Then, the error screw model of the geometric features of each section of the wing is derived under the joint constraints of dimensional tolerance and form and position tolerance.

[0106] The step three specifically includes:

[0107] Based on the basic error sources and their interaction in the assembly coordination process, as well as the analysis of the assembly characteristics of the segmented wing, it is determined that the main influencing factors of assembly errors are dimensional tolerance and assembly process links.

[0108] According to the range of geometric deviation and tolerance domain, the range of position and posture changes of the assembled parts is determined, the coordinated reference transformation process is defined, the position and posture changes of subsequent parts transferred by assembly are determined, and then the model is built to determine the final assembly error.

[0109] Combined with the process steps in the global assembly, the error transmission model is carried out for each coordinated control link, and the assembly directed graph and spatial assembly coordinated dimension chain are constructed.

[0110] In the method for constructing the error transmission and accumulation model of multi-process assembly of complex products in step 4, the error transmission direction and transmission path are clarified, the assembly error transmission network of the object to be assembled is constructed, the critical dimension transmission chain is clarified and the assembly error variation range is calculated.

[0111] In the method for constructing the error transmission and accumulation model of multi-process assembly of complex products in step 4, the error transmission direction and transmission path are combined with step 3 to analyze the error transmission in the current process step of a key section of components in the object to be assembled, and the inheritance transmission relationship of errors between different processes when different components are assembled, so as to obtain the coordinated error transmission direction and transmission path.

[0112] In the method for constructing the error transmission and accumulation model of multi-process assembly of complex products in step 4, the Monte Carlo method is used to obtain the nonlinear transmission characteristics and accumulation law of the error, obtain the variation range and distribution law of the assembly error in three-dimensional space, and then calculate the error mean.

[0113] In the step 5 of establishing the assembly error sensitivity analysis model and the assembly coordination error key assembly link identification method, based on the specific geometric structure of the object to be assembled and the assembly error transmission path, the sensitivity analysis of each error component link is performed to obtain the transmission coefficient, contribution degree and other values ​​of each size and shape error link, comprehensively obtain the error sensitivity, clarify the coordination relationship between each error link in different work step process and work station levels, and determine the key error and size link that affect the assembly accuracy. The step 5 specifically includes:

[0114] S51: Based on the three-dimensional dimension chain of the product to be assembled and its nonlinear transmission route, the three-dimensional dimension chain is appropriately simplified, and the spatial assembly dimension chain is spatially decomposed. The corresponding characteristics of the assembly index are traced back to the assembly datum of each wing component, and the closed-loop construction of the error transmission link is completed to obtain a planar two-dimensional dimension chain that can reflect the assembly quality index.

[0115] S52: geometrically analyze the above two-dimensional dimension chain that can reflect the assembly quality index, and draw a schematic diagram of the dimension chain. On this basis, clarify the functional relationship between the closed loop and each component loop, establish multiple independent variables, and then establish the plane dimension chain function equation.

[0116] S53: Establish an error total differential model for the plane dimension chain equation, calculate the comprehensive and cumulative errors of each component ring, and the derivative of the closed loop with respect to each component ring represents the sensitivity coefficient of each component ring. The relative contribution is expressed as the ratio of the sensitivity coefficient of a certain component ring to the sum of the sensitivity coefficients of all component rings, thereby preliminarily obtaining the error sensitivity of the dimension chain.

[0117] S54: Based on the sensitivity, contribution and other data obtained from the preliminary calculation, the influence and formation causes of each component ring are analyzed to determine the key errors and dimensional links that affect the assembly accuracy, providing quantitative guidance for subsequent tolerance allocation optimization.

[0118] In step six, the manufacturing cost and the actual processing capacity of the factory are first considered, and a single-objective tolerance allocation optimization function is defined for specific structures such as wing segment assembly and wing-fuselage space multi-intersection docking assembly. The cumulative range of assembly accuracy and the actual variation range of each error link are used as constraints to establish an assembly tolerance coordination optimization allocation model. The construction of the allocation model involves the composition of multiple factors and their unification, and the tolerance allocation problem needs to be converted into an effective and accurate mathematical model. Step six sets up multiple reasonable single-objective models and unifies the multiple models, thereby establishing an efficient and accurate function model that can express the correlation between manufacturing performance and digital models. Step six specifically includes:

[0119] S61: Describe and quantify the actual requirements of segmented wing assembly, construct multiple single-objective optimization functions such as tolerance-manufacturing cost function, tolerance-quality loss function, tolerance-repair workload function, and set reasonable weight parameters for each according to specific functional requirements.

[0120] S62: Fusion modeling is performed on the above-mentioned multiple models, the main optimization function is established, and a series of constraints are set, such as weight constraints, dimension chain tolerance constraints based on technical indicators, tolerance range constraints considering the actual processing capabilities of the factory, etc.

[0121] S63: With the main optimization function as the core, design variables, constraints and other elements are supplemented to build a multi-objective coordinated optimization allocation model for assembly tolerance. Specifically, the design variable is mainly selected as tolerance t, and each tolerance is considered to be independent, and the tolerance boundary is determined by the manufacturing process accuracy limit. In terms of constraints, there is at least one constraint, which is mainly used to achieve quality or cost restrictions, and additional constraints can also be considered in specific aspects.

[0122] In the step seven, the multi-objective optimization model of assembly tolerance is iteratively solved using an intelligent algorithm to clarify the error distribution range of multiple random variables such as size, shape and position, thereby achieving accurate allocation of tolerances.

[0123] Embodiment 1:

[0124] In this embodiment, the docking process of two-section wing assembly of a spacecraft is taken as an example to illustrate the implementation steps of the multi-objective optimization method for assembly docking dimension chain construction and tolerance allocation:

[0125] Step 1: Establish a nonlinear transfer path model based on assembly error coupling relationship analysis.

[0126] Specifically, firstly, according to the characteristics of the spacecraft wing structure and assembly process, it is analyzed that the process is mainly to first contact and dock the bottom of each wing section with the tooling fixture. There are 2 or more tooling interfaces at the bottom of the wing. The center of the oblong hole at the intersection of the two farthest interfaces is used as the reference for positioning and assembly, and then the box docking of each wing section is carried out. After each docking, the wing shape surface is measured and adjusted to meet the following accuracy requirements: wing shape surface accuracy, step difference between wing components, gap between wing components, and finally complete the assembly of the entire wing; secondly, through the assembly process The program analyzes the types of fitting errors, assembly elements, structural forms and other information between the key components of the spacecraft wing, and obtains that the assembly errors of the spacecraft wing mainly consider the following dimensional tolerances and assembly position deviations: the position tolerance of each hole, the error of the overall length of each section, the dimensional error of the joint length, and the dimensional error of the joint width; finally, through search technology and graphics theory, the assembly geometric error transfer path model is constructed and the transfer relationship view is expressed at the junction of the spacecraft wings, that is, the step difference and the outer surface of the wing, to obtain the final nonlinear transfer path model of assembly coordination error.

[0127] Step 2: Establish an assembly feature geometric error model based on key measuring points.

[0128] Specifically, according to the results of the analysis in step 1, it is known that the most critical position of the multi-section wing assembly is at the interface where the bottom of the wing is connected to the fuselage. In addition, during the assembly process of each section of the wing, the wings are assembled by fitting and hole axis, and the bottom of each section is positioned and assembled based on the center of the long circular hole at the intersection of the two farthest tooling interfaces. These key control objects in the positioning and assembly process are key features; secondly, a coordinate system is established on the center of the long circular hole on the wing interface at the key control point, and the relative position relationship between the fuselage and the wing and between the wings is converted into the point spacing of the horizontal measurement points on the wing in the physical space of the three directions of X, Y, and Z under the aircraft coordinate system O-XYZ. According to the requirements for the plane, position, gap, step difference, etc. between the components after the wing is assembled, these requirements are decomposed item by item into measurable or calculable point information, and measurement feature extraction is performed. Finally, based on the measurement data of key measuring points, the kinematic theory and small displacement screw method are used to derive the error screw model of the wing geometric characteristics under the joint constraints of dimensional metrics and form and position tolerances. Then, according to the wing geometric characteristics and surface variation errors, they are mapped to the tolerance domain to establish a multi-source assembly error source variation model.

[0129] Furthermore, a coordinate system is established at the center of the oblong hole at the wing intersection interface, with point O located at the bottom of the connection between the wing and the fuselage and at the intersection with the adjacent wing; the X direction is parallel to the axis of the connection between the fuselage and the wing and points to the direction of the wing tip; the Y direction is the direction of the axis of the connection between the wing and the wing pointing to the wing tip; and the Z direction is the direction of the axis perpendicular to the wing surface pointing upward. According to the position tolerance of the hole ±0.05mm, the kinematic theory and small displacement screw method can be used to deduce that the center tolerance domain of the oblong hole on the wing interface is the center area, and its screw model and constraint inequality are:

[0130]

[0131] Furthermore, the coordinate system is established with the center of the spacecraft wing surface as point O. According to the error of the wing shape surface accuracy being less than 0.8 mm, the kinematic theory and small displacement screw method can be used to derive the screw model of the wing surface as the plane characteristic error screw model and the constraint inequality is:

[0132]

[0133] Step 3: Construct a spatial assembly coordinated dimension chain with multi-directional cross-transfer characteristics.

[0134] Specifically, firstly, according to the assembly error coupling relationship between the spacecraft wing structure and the assembly process, the basic error sources and their interaction relationships in the assembly coordination process are deeply analyzed, and the error sources are classified. The first or second type of error deviation sources are the interface connections between the wing sections and the fuselage of the spacecraft, and the fitting deviations caused by the assembly connection between the fuselage fixtures and the wing sections and the fitting deviations caused by the assembly fitting connection between the wing sections are the third type of error deviation sources, and the parts fit and deviation directed graphs are drawn; secondly, the transfer coefficients of each component ring of the three-dimensional dimension chain of the spacecraft wing model are relatively complex and difficult to solve. By extracting the direction vectors of each dimension of the closed loop and the component ring in the assembly coordinate system, the dimension The dimension chain is projected onto the three coordinate axes of X, Y, and Z respectively, thereby changing the solution of the three-dimensional dimension chain to the solution of three one-dimensional dimension chains. Then, the dimension tolerance components of each closed loop in the X, Y, and Z directions are obtained according to the dimension tolerance components of each component ring in the three coordinate axes, and then the dimension tolerance of the closed loop is calculated according to the direction vector of the closed loop; finally, by combining the process steps in the global assembly, the coordination reference transformation process is defined, and multi-directional error transfer modeling is established for each coordination control link. Combined with their interaction relationship, a spatial assembly coordination dimension chain with multi-directional cross-transmission characteristics is constructed at the wing-to-wing joint, which accurately describes the assembly accuracy requirements such as the gap and step difference between the two wing assemblies.

[0135] Step 4: Establish an error transmission and accumulation model for multi-process assembly of complex products.

[0136] In the stage of establishing the multi-process assembly error transmission and accumulation model of spacecraft products, the spacecraft wing is analyzed according to the nonlinear transfer path model in step one, the assembly feature geometric error model in step two, and the spatial assembly coordinated dimension chain in step three to obtain a clear key dimension transfer chain, and the variation range of the assembly error in three-dimensional space is calculated.

[0137] Specifically, in the stage of establishing the multi-process assembly error transmission and accumulation model of spacecraft products, firstly, according to the assembly feature geometric error model in step 2, the spin model of the center of the oblong hole on the wing interface is obtained (0, 0, 0, u, v, 0) and the constraint inequality is: -0.05≤u≤0.05, -0.05≤v≤0.05. The bottom of each section is positioned and assembled with the center of the oblong hole at the intersection of the two farthest tooling interfaces as the reference. The reference inclination and verticality can be calculated from the coaxiality and position as ɑ=±0.0061° and β=±0.1993°; secondly, According to the assembly error generated after the spatial assembly coordination dimension chain and the tooling interface in step three, the assembly position error of the wing-to-wing docking can be calculated. The farthest end of the wing is set to calculate the maximum position error of the wing vertical surface and the maximum position error in the direction parallel to the fuselage. Finally, in order to obtain the step difference between wings, a clear key dimension transfer chain is established with the step difference between wings as a closed loop. The Monte Carlo method is used to obtain the nonlinear transfer characteristics and accumulation law of the error, obtain the variation range and distribution law of the assembly error in three-dimensional space, and then statistically calculate the error mean.

[0138] Furthermore, Figure 2 Taking the segmented wing assembly step difference dimension chain in the example, in the construction and solution of the assembly dimension chain, firstly, the transfer coefficient of each component ring is calculated using the node information in the graph theory model, and then the matrix of the assembly dimension is established according to the transfer coefficient and the edge weight information, and the solution is obtained. Figure 2 The vertical and wing surface assembly step difference between the wing sections, and Figure 3 The assembly gap size between the wing sections along the heading direction; judge the increase and decrease rings in the figure according to the node information, and determine the transfer coefficient of the constituent rings. The first section wing and the second section wing are composed of two assemblies. The design dimensions of the parts are: L1 = 3.9165, L2 = 3.9179, L3 = 76.0311, L4 = 67.0168, L5 = 74.0255, L6 = 82.1377, L7 = 4.0561, L8 = 3.5033. Now it is required to solve the assembly size (i.e. the closed loop size) according to the design dimensions of the parts: the step difference X between the upper surface of the first section wing and the upper surface of the second section wing at the fitting place N1 .

[0139] X N1=L1+L2+L3-L6+A0

[0140] Step 5: Establish an assembly error sensitivity analysis model and identify key assembly links

[0141] Specifically, firstly, the above-mentioned spatial dimension chain and the corresponding nonlinear error transmission route are separated according to the production technical index requirements. After analysis and simplification, a planar two-dimensional dimension chain with a closed loop of Xn1 is obtained, in which A0, L5, and L10 are increasing loops, and L1 and L3 are decreasing loops. The function expression of the assembly step difference dimension chain is: Xn1 n1 =A0+L5+L 10 -L1-L3.

[0142] Further, according to Figure 2 Schematic diagram and function expression of assembly step difference dimension chain, determine that the dimension chain contains 5 component rings, and set 5 function variables.

[0143] Furthermore, a total error differential model is established based on the existing dimension chain function equation, and the sensitivities of the dimension chain components A0, L1, L3, L5, and L10 are calculated to be 1, -1, -1, +1, and +1, respectively, with contributions of 19.83%, 15.86, 23.54, 34.23 / 6.54%. Each link needs further optimization, and the specific dimension chain links required for optimization in the subsequent multi-objective optimization process are determined.

[0144] Step 6: Establish a multi-objective coordinated optimization allocation model for assembly tolerance

[0145] The tolerance optimization model establishment stage needs to be divided into three aspects according to the product assembly requirements: single-objective tolerance optimization function model construction, assembly coordination constraint and other model element supplementation, and multi-model fusion unified modeling.

[0146] Furthermore, according to the assembly characteristics of each section of the wing and the actual production needs, the construction and optimization method of the single-objective model involved in the tolerance optimization process are determined; secondly, on the basis of the establishment of the single-objective optimization model, the hierarchical analysis method is used to obtain the weight coefficient of each objective, and then the weighted sum of each objective model is taken to calculate the comprehensive evaluation index, so as to realize the fusion modeling from the establishment of the single-objective model to the multi-objective optimization model; thereafter, in order to ensure the rationality of the optimization, it is necessary to impose model constraints considering the actual assembly process and integrate and improve the multi-objective optimization model; finally, according to the above work, the dimension chain to be optimized is substituted into the above-mentioned multi-objective optimization model, and it is further converted into a function expression format that can be recognized by the algorithm to characterize the multi-objective optimization model.

[0147] Specifically, in the process of selecting and establishing the single objective function model, combined with the actual assembly production process, the MBD model of the segmented wing product is first consulted to obtain the design data of each tolerance dimension, feature processing information, etc., and then summarized and sorted for the subsequent digital model construction call; secondly, relying on engineering experience and factory production data, function models such as tolerance-quality loss, tolerance-manufacturing cost, and tolerance-maximum repair workload are established to obtain a mathematical model that can accurately map tolerance and product characteristic information; after that, the work link of specific constraint construction is carried out, which mainly includes the indicator weight constraint for coordinating multi-objective optimization, the dimension chain tolerance constraint based on technical indicators, and the tolerance range constraint considering the actual processing capacity of the factory. The assembly step difference dimension chain component ring information data is shown in Table 1.

[0148] Table 1 Assembly step difference dimension chain component ring information data

[0149] Composition ring size Design Tolerance Machining Features L1 1.96 0.05 Plane Features L3 38.02 0.05 Plane Features L5 37.01 0.05 Plane Features L10 2.03 0.05 Plane Features A0 0.4 0.4 Hole position

[0150] by Figure 2 Taking the assembly step difference loop L1 in as an example, a series of single-objective optimization models are constructed. This loop is a plane feature, T is set as the tolerance, and the corresponding tolerance-manufacturing cost mathematical expression is selected:

[0151]

[0152] The deviation of the component size from the ideal target value is regarded as the quality loss. Based on this, the quality loss model is established, and the expected value of the product quality loss caused by the size loop is calculated as:

[0153]

[0154] In addition, the spacecraft production process also faces the problem of huge repair workload. The maximum repair amount is the maximum repair value generated during the repair and assembly process, which is equal to the sum of the increase and decrease tolerances of each component ring and the minimum repair amount minus the tolerance of the closed ring. The construction of this single-objective model requires the tolerance data of each component ring, and the calculation formula is:

[0155] K max =ΣT i +ΣT d -T0+K min

[0156] Among them, T0 represents a closed loop, T i To add a link to the dimensional chain, T d K is the size of the chain minus the ring min Represents the minimum repair amount, and the default value is 0. In terms of optimization implementation, the smaller the value, the better it is for all three models. The weighted sum of the three models is used to find the minimum value and obtain the best tolerance allocation solution. If the larger the better, a negative sign can be used and the weighted sum can be used.

[0157] The constraints of the multi-objective optimization model are constructed. The fusion of the single-objective optimization model mainly relies on the sum of weights. Therefore, the weight parameters are first constrained reasonably. The weight parameters of each model are set as: α, β, γ…ε, then

[0158] C o =α+β+γ+…+ε=1

[0159] Among them, C o is the sum of all weight parameters, and all parameters are greater than 0.

[0160] At the same time, there are also dimensional chain tolerance constraints based on technical indicators to ensure that the final assembly quality of the product meets production requirements. Specifically include: wing shape surface accuracy, reverse step difference between wing components, forward step difference between wing components, etc. In terms of specific application methods, the above standardization is integrated into the model construction by methods such as closed loop dimensions. In addition, the actual processing capacity of the manufacturing plant is also considered, and the optimized value is controlled within the processing capacity range to avoid the emergence of excessive tolerance requirements. The constraints are as follows:

[0161] (k i σ i ) min ≤(k i σ i )≤(k i σ i ) max

[0162] Where: (k i σ i ) min is the minimum machining capability tolerance of the tolerance of the ith component ring; (k i σ i ) max is the maximum machining capability tolerance of the tolerance of the ith component ring.

[0163] Step 7: Bring the above model into the adaptive particle swarm algorithm APSO intelligent algorithm for iterative solution

[0164] First, the algorithm implementation platform is selected, the algorithm program code is written, and the basic framework of the algorithm program is constructed; secondly, based on the functional form used to characterize the multi-objective tolerance optimization model, the multi-objective function model is written into a form that can be recognized by the algorithm platform and imported into the algorithm. Finally, the specific parameters of the algorithm are adjusted and finalized, and after confirmation, it is solved iteratively to obtain the optimal tolerance allocation plan and analyze it.

[0165] Specifically, the adaptive particle swarm algorithm APSO is first written in Matlab software, mainly establishing the objective function file, inequality function file, APSO solution function file and multiple sub-function files, and performing simple case calculations to verify the effectiveness of the algorithm. Furthermore, the code functions of the target optimization model are written one by one according to the assembly dimension chain composition ring, where the single-objective optimization model and the fusion optimization model are written into the objective function file, and the constraints are written into the inequality function file. Then, specific parameters such as particle population size are defined in the APSO solution function file to complete the overall optimization construction process. Finally, the algorithm program is run, the iterative data is recorded and analyzed, and the optimized tolerance allocation scheme is obtained. The optimization effect is shown in Table 2.

[0166] Table 2 Multi-objective tolerance optimization results and optimization effect data table

[0167]

[0168] The present invention provides a method and system for optimizing the assembly coordination error of a segmented wing structure based on a spatial dimension chain, specifically relates to a method for constructing and optimizing an assembly error spatial dimension chain, more specifically, to a spacecraft assembly coordination error transmission accumulation model, an assembly spatial dimension chain model, an assembly tolerance optimization model construction and intelligent solution method, and especially relates to a method for constructing and optimizing a segmented wing structure assembly spatial dimension chain, providing an effective solution to the problems of error transmission accumulation prediction, assembly key link identification and tolerance allocation in the spacecraft assembly process.

[0169] The present invention mainly includes two parts, namely: assembly coordination error transmission accumulation and coordinated dimension chain construction, assembly tolerance optimization model construction and intelligent solution technology. It can be seen from the effect after optimization that the method of the present invention can achieve:

[0170] 1) Accurate construction of assembly coordination dimension chain and quantitative analysis of assembly error transmission accumulation results provide data basis for spacecraft structure assembly process tolerance optimization design;

[0171] 2) Establish and solve an efficient and accurate function model that can express the correlation between manufacturing performance and digital models, realize the reasonable allocation of assembly dimension chain tolerance, improve assembly performance, and reduce the amount of repairs and manufacturing costs during the assembly process.

[0172] The above is a detailed introduction to a segmented wing structure assembly coordination error optimization method and system based on a spatial dimension chain provided in an embodiment of the present application. The description of the above embodiment is only used to help understand the method and its core idea of ​​the present application; at the same time, for a person skilled in the art, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

[0173] For example, certain words are used in the specification and claims to refer to specific components. Those skilled in the art should understand that hardware manufacturers may use different nouns to refer to the same component. This specification and claims do not use differences in names as a way to distinguish components, but use differences in the functions of components as the criteria for distinction. As mentioned throughout the specification and claims, "including" and "comprising" are open-ended terms, so they should be interpreted as "including / including but not limited to". "Approximately" means that within an acceptable error range, those skilled in the art can solve the technical problem within a certain error range and basically achieve the technical effect. The subsequent description of the specification is a preferred embodiment of the present application, but the description is for the purpose of illustrating the general principles of the present application, and is not used to limit the scope of the present application. The scope of protection of the present application shall be determined by the definition of the attached claims.

[0174] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a product or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such a product or system. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the product or system including the elements.

[0175] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0176] The above description shows and describes several preferred embodiments of the present application, but as mentioned above, it should be understood that the present application is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the application concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art do not deviate from the spirit and scope of the present application, and should be within the scope of protection of the claims attached to the present application.

Claims

1. A method for optimizing the assembly coordination error of a segmented wing structure based on a spatial dimension chain, which is used to optimize the assembly coordination process of the segmented wing structure, and is characterized in that: The segmented wing structure assembly coordination error optimization method comprises the following steps: S1: Analyze the assembly error coupling relationship of each component in the segmented wing structure, and establish a nonlinear transfer path model of assembly coordination errors between components based on the analysis results of the assembly error coupling relationship; S2: Preset key measuring points on each component, and establish the assembly feature geometric error variation model of all key measuring points based on the nonlinear transfer path model of assembly coordination errors between components; S3: Analyze the basic error sources and interaction relationships in the assembly coordination process and the assembly characteristics of the segmented wing, and construct a spatial assembly coordination dimension chain with multi-directional cross-transfer characteristics; S4: Based on the nonlinear transfer path model in S1, the assembly feature geometric error variation model in S2, and the spatial assembly coordinated dimension chain in S3, a multi-process assembly error transfer and coordination error accumulation model for complex segmented wing products is established; S5: Based on the multi-process assembly error transmission and accumulation model of complex segmented wing products in S4, an assembly error sensitivity analysis model is established and the key assembly links are identified and obtained; S6: Based on the key assembly links and assembly error sensitivity analysis model in S5, a multi-objective coordinated optimization allocation model for assembly tolerance is established; S7: Substitute the assembly tolerance multi-objective coordinated optimization allocation model into the intelligent algorithm for iterative solution to obtain the optimal segmented wing structure assembly coordination error allocation value.

2. The method for optimizing the assembly coordination error of a segmented wing structure according to claim 1, characterized in that: The S1 specifically includes: S11: according to the structure of the spacecraft product, analyzing the matching error type information, assembly element information and structural form information between the components of the segmented wing structure to be assembled on the spacecraft; S12: defining assembly process planning content according to the matching error type information, assembly element information and structural form information, wherein the assembly process planning content includes: positioning, reference, connection, sequence, tolerance analysis and error analysis; S13: constructing a three-dimensional assembly model of the object to be assembled according to the time sequence of the assembly process planning content; S14: A nonlinear transfer path model of assembly coordination errors between components is constructed through the three-dimensional assembly model of the object to be assembled, search technology and graphics theory.

3. The method for optimizing the assembly coordination error of a segmented wing structure according to claim 2, characterized in that: The S2 specifically includes: S21: Through the nonlinear transfer path model between various components, search technology and graphics theory, the assembly geometric error transfer path model construction and the expression of the transfer relationship view are obtained; S22: Based on the measurement data of preset key measuring points, the error screw model of the key geometric features on each section of the wing under the constraints of the dimension and the form and position tolerance is obtained by constructing the assembly geometric error transfer path model and expressing the transfer relationship view; S23: According to the error variation direction of the matching surfaces of the geometric features of the multi-segment wings and the error screw model of the key geometric features on each wing segment under the common constraints of the dimensional metric and the form and position tolerance, the assembly feature geometric error variation model of all key measuring points is established.

4. The method for optimizing the assembly coordination error of a segmented wing structure according to claim 3, characterized in that: The key measuring points in S22 are to first obtain the limited requirements of the plane, position, gap and step difference between the components after the wing is assembled, decompose the limited requirements item by item into measurable or calculable point information, and then perform measurement feature extraction to obtain the key measuring points and the corresponding key geometric features.

5. The method for optimizing the assembly coordination error of a segmented wing structure according to claim 4, characterized in that: The error screw model of the key geometric features on each section of the wing in S22 under the joint constraints of dimensional tolerance and form and position tolerance is specifically: using kinematic theory and small displacement screw method, the positions and deformation changes of typical straight line, plane, and spatial curved surface geometric features contained in the components of the assembly object are mathematically expressed and described, and mapped to the tolerance domain, and then the error screw model of the geometric features of each section of the wing under the joint constraints of dimensional tolerance and form and position tolerance is derived.

6. The method for optimizing the assembly coordination error of a segmented wing structure according to claim 5, characterized in that: The S3 specifically includes: S31: Based on the analysis of the basic error sources and their interaction in the assembly coordination process and the assembly characteristics of the segmented wing, determine the influencing factors of the assembly error, where the influencing factors include dimensional tolerance and assembly process links; S32: According to the range of geometric deviation and tolerance domain, determine the range of position and posture variation of the assembled parts, define the coordinated reference transformation process, determine the position and posture variation of the subsequent parts during assembly, and then model and determine the final assembly error; S33: According to the process steps of the assembly coordination process, the error transmission model is built for each coordination control link to construct a spatial assembly coordination dimension chain with multi-directional cross-transmission characteristics.

7. The method for optimizing the assembly coordination error of a segmented wing structure according to claim 1, characterized in that: The S4 specifically includes: S41: Clarify the error transmission direction and transmission path, build the assembly error transmission network of the assembly object, clarify the key dimension transmission chain and calculate the assembly error variation range; S42: Analyze the error transmission of a key section of the assembly object in the current process step through the spatial assembly coordinated dimension chain, as well as the inheritance and transmission relationship of errors between different processes when different components are assembled, and obtain the error transmission direction and transmission path in the error transmission and accumulation model of complex product multi-process assembly; S43: The nonlinear transfer characteristics and accumulation law of the error are obtained through the Monte Carlo method, and the variation range and distribution law of the assembly error in the three-dimensional space are further obtained, and then the error mean is statistically calculated.

8. The method for optimizing the assembly coordination error of a segmented wing structure according to claim 7, characterized in that: The S5 specifically includes: S51: Based on the three-dimensional dimension chain of the product to be assembled and the nonlinear transmission route of the assembly coordination error, the three-dimensional dimension chain is appropriately simplified, and the spatial assembly dimension chain is spatially decomposed, and the corresponding characteristics of the assembly index are traced back to the assembly benchmark of each section of the wing component, completing the closed-loop construction of the error transmission link, and obtaining a plane two-dimensional dimension chain that can reflect the assembly quality index; S52: geometrically analyze the two-dimensional dimension chain that can reflect the assembly quality index, draw a schematic diagram of the dimension chain, clarify the functional relationship between the closed loop and each component loop on this basis, establish multiple independent variables, and then establish a plane dimension chain function equation; S53: Establish an error total differential model for the plane dimension chain equation, calculate and obtain the comprehensive and cumulative errors of each component ring, and the derivative of the closed loop to each component ring represents the sensitivity coefficient of each component ring. The relative contribution is expressed as the ratio of the sensitivity coefficient of a component ring to the sum of the sensitivity coefficients of all component rings, thereby preliminarily obtaining the error sensitivity of the dimension chain; S54: Based on the sensitivity and contribution calculated preliminarily in S53, analyze the influence and causes of each component ring, determine the key errors and dimensional links that affect assembly accuracy, and provide quantitative guidance for subsequent tolerance allocation optimization.

9. The method for optimizing the assembly coordination error of a segmented wing structure according to claim 8, characterized in that: The S6 specifically includes: S61: Describe and quantify the actual requirements of segmented wing assembly, construct multiple single-objective optimization functions, and set weight parameters for each according to functional requirements; S62: Perform fusion modeling on multiple single-objective optimization functions, establish a main optimization function, and set a series of constraint conditions; S63: Taking the main optimization function as the core, the design variables and constraint elements are supplemented to construct a multi-objective coordinated optimization allocation model for assembly tolerance.

10. A segmented wing structure assembly coordination error optimization system based on space dimension chain, characterized in that: The optimization system includes a memory and a processor, wherein the memory is connected to the processor, and the segmented wing structure assembly coordination error optimization method as described in any one of claims 1 to 9 is stored in the memory.

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