Precision optimal distribution method and system for ultra-precision grinding machine

Abstract

The embodiment of the invention provides a precision optimization distribution method and system for an ultra-precision grinding machine. The method comprises the steps that the topological relation between moving parts of a machine tool is determined; based on the topological relation, constructing a machine tool motion error model representing the motion error of the motion part; based on the machine tool motion error model, determining the influence of the motion error item of each motion axis of the machine tool on the element surface shape precision; based on the influence of the motion error term of each motion axis on the element surface shape precision and the motion error term, constructing a machine tool precision optimization distribution model; and distributing the precision of the machine tool based on the machine tool precision optimization distribution model and the element surface shape precision requirement of the machine tool. According to the method, the machine tool motion precision index meeting the element machining precision can be determined, and the development cost of the ultra-precision grinding machine tool is reduced.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and more specifically to a method and system for optimizing the allocation of precision in an ultra-precision grinding machine. Background Technology

[0002] Optical components are typically made of hard and brittle materials such as fused silica and barium borate glass (BK7). In ultra-precision grinding, this material is deterministically removed, thus establishing a deterministic relationship between machine tool motion accuracy and component machining accuracy. Higher grinding machine tool accuracy generally leads to better component surface accuracy, but this also increases machine tool development costs and assembly requirements. Therefore, understanding how to deduce machine tool accuracy based on component machining needs is crucial for reducing machine tool manufacturing costs and development risks.

[0003] In the past, machine tool manufacturers typically used analogy or empirical methods when designing machine tool precision, referring to existing machine tools to design the precision of the next generation of machine tools. This relied on the experience and knowledge of designers, lacking theoretical and systematic design guidance. In recent years, precision optimization allocation methods based on tolerance-cost models and tool tip trajectory accuracy have been proposed to address the problem of machine tool precision optimization allocation. While these methods have filled the theoretical gap in machine tool precision optimization design, for the ultra-precision grinding manufacturing of optical components, where grinding quality is evaluated based on component surface accuracy, there is still no theoretical method to solve the problem of machine tool precision optimization allocation with component surface accuracy as the design objective. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for optimizing the allocation of precision in ultra-precision grinding machines. The specific technical solution adopted is as follows: In a first aspect, embodiments of the present invention provide a method for optimizing the allocation of precision in an ultra-precision grinding machine, the method comprising: Determine the topological relationships between the moving parts of the machine tool; Based on the aforementioned topological relationship, a machine tool motion error model characterizing the motion error of the moving parts is constructed; Based on the machine tool motion error model, determine the influence of motion error terms of each motion axis of the machine tool on the surface accuracy of the component; Based on the influence of the motion error terms of each motion axis on the surface accuracy of the component and the motion error terms, a machine tool accuracy optimization allocation model is constructed. Based on the machine tool accuracy optimization allocation model and the component surface accuracy requirements of the machine tool, the accuracy of the machine tool is allocated.

[0005] Secondly, a precision optimization allocation system for an ultra-precision grinding machine is provided, the system comprising: The first determining module is used to determine the topological relationships between the moving parts of the machine tool; The first construction module is used to construct a machine tool motion error model that characterizes the motion error of the moving parts based on the topological relationship; The second determining module is used to determine the influence of motion error terms of each motion axis of the machine tool on the surface accuracy of the component based on the machine tool motion error model; The second construction module is used to construct a machine tool accuracy optimization allocation model based on the influence of the motion error terms of each motion axis on the surface accuracy of the component and the motion error terms. The allocation module is used to allocate the precision of the machine tool based on the machine tool precision optimization allocation model and the component surface precision requirements of the machine tool.

[0006] Thirdly, a computer program product is provided, comprising: computer program code, which, when run on a computer, causes the computer to perform the method described in the first aspect or any possible implementation thereof.

[0007] Fourthly, a computer-readable storage medium is provided that stores computer program code, which, when executed on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof.

[0008] This invention offers the following advantages: By determining the topological relationships between the moving parts of a machine tool, a machine tool motion error model characterizing the motion errors of these moving parts is constructed, resulting in higher accuracy of the machine tool motion error model. Subsequently, based on this motion error model, the influence of motion error terms of each motion axis on the surface accuracy of components is determined. Furthermore, through the influence of motion error terms of each motion axis on the surface accuracy of components and the motion error terms themselves, a machine tool accuracy optimization allocation model is constructed. This model, combined with the surface accuracy requirements of the machine tool's components, allocates the accuracy of the machine tool. Thus, using component machining accuracy as input, a machine tool motion error model characterizing the motion errors of the moving parts is determined, enabling the design of accuracy margins for ultra-precision grinding machine tools. Furthermore, the machine tool accuracy optimization allocation model can determine the machine tool motion accuracy indicators that meet the component machining accuracy requirements, thereby reducing the development cost of ultra-precision grinding machine tools. Attached Figure Description

[0009] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a schematic diagram illustrating the implementation process of an ultra-precision grinding machine precision optimization allocation method provided in an embodiment of the present invention; Figure 2 This is a structural diagram of the ultra-precision grinding machine tool provided in the embodiments of the present invention; Figure 3 This is a schematic diagram of another implementation process of an ultra-precision grinding machine precision optimization allocation method provided in an embodiment of the present invention; Figure 4 This is a topological structure diagram of the ultra-precision grinding machine tool provided in the embodiments of the present invention; Figure 5 This is a graph showing the sensitivity analysis results of the motion error term of the machine tool motion axis provided in an embodiment of the present invention; Figure 6 This is a flowchart of the fmincon iterative solution provided in an embodiment of the present invention; Figure 7 This is a diagram illustrating the convergence process of the objective function in the machine tool accuracy optimization allocation provided in this embodiment of the invention. Figure 8 This invention provides the surface shape error results of a 610mm×440mm workpiece based on the accuracy allocation results. Figure 9 This is a schematic diagram of the composition structure of an ultra-precision grinding machine precision optimization and allocation system provided in an embodiment of the present invention; Figure 10 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0011] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a precision optimization allocation method for an ultra-precision grinding machine proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined from any suitable form.

[0012] In the description of the embodiments of the present invention, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of the present invention, "multiple" means two or more.

[0013] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0014] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0015] In some embodiments, for the ultra-precision grinding manufacturing of optical components, the focus is on the surface accuracy of the components (peak to valley (PV) value). A mapping model between the motion accuracy of the machine tool's motion axes and the surface accuracy of the components is established. Using the surface accuracy of the components as the design input, the motion accuracy of each motion axis of the machine tool is determined. This achieves the optimized allocation of precision in the ultra-precision grinding machine tool for optical components, which is a problem that needs to be solved in the current ultra-precision grinding machine tool industry.

[0016] Based on this, embodiments of the present invention provide a method for optimizing the allocation of precision in an ultra-precision grinding machine. The specific scheme of an ultra-precision grinding machine precision optimization allocation system provided by the present invention is described below in conjunction with the accompanying drawings. Please refer to... Figure 1 The diagram illustrates a flowchart of an embodiment of the present invention providing a method for optimizing the allocation of precision in an ultra-precision grinding machine. The method includes: 101. Determine the topological relationships between the moving parts of the machine tool.

[0017] Here, the relationship between the machine tool structure and the motion of the linkage axis is analyzed, and the topological relationship between the moving parts of the machine tool is established through multibody kinematics theory. The structure of the ultra-precision grinding machine tool is as follows: Figure 2 As shown, the ultra-precision grinding machine is a three-axis linkage machine tool, including three linear linkage axes: X, Y, and Z. Based on multibody kinematics theory, the topological relationships between the moving parts of the machine tool are described, and rigid bodies are numbered as follows: 1-bed base, 2-worktable (Y-axis), 3-workpiece, 4-column (X-axis), 5-spindle box (Z-axis), 6-grinding wheel.

[0018] 102. Based on the aforementioned topological relationship, a machine tool motion error model characterizing the motion error of the moving component is constructed.

[0019] Here, each moving component is considered a rigid body, and the position of the rigid body in the body coordinate system is determined. Based on the topological relationship of the machine tool moving components and the positional relationship of the origin of the body coordinate system, a homogeneous coordinate transformation matrix is ​​established between adjacent rigid bodies to describe the position transfer of the object of interest between the rigid bodies. Considering the motion error of the machine tool motion axis, a machine tool motion error model is established to determine the mapping relationship between the motion accuracy index of the machine tool motion axis and the machining accuracy of the components.

[0020] In some possible implementations, step 102 above can be achieved by... Figure 3 The steps shown are to be implemented as follows: 301. Determine the body coordinate system position of each moving part.

[0021] Here, each rigid body is considered as a point mass, and the coordinate system elements of each rigid body are established at its center of mass. , , , , and These are the tool coordinate system, spindle box coordinate system, column coordinate system, bed coordinate system, table coordinate system, and workpiece coordinate system. The origin of all coordinate systems is in the XZ plane, and the XYZ directions of each coordinate system are perpendicular to the XZ plane. same, , and On a straight line parallel to the X-axis, , , and On a straight line parallel to the Z-axis. 、 、 、 and Represent and 、 and 、 and 、 and and and The distances between them are shown in Table 1.

[0022] Table 1. Location data of the origin of the coordinate system between rigid bodies (unit: millimeters (mm))

[0023] 302. Based on the body coordinate system position of each moving component and the topological relationship, establish a position error matrix between adjacent moving components.

[0024] Here, while establishing the position error matrix, a position matrix between adjacent moving parts is established based on the body coordinate system position of each moving part and the topological relationship. An ideal motion model of the machine tool is then constructed based on the position matrix and the body coordinate system position. For the linear motion axis of the machine tool, there are six motion errors in space, including the linearity error and angular displacement error of the motion axis. Therefore, the three-axis linkage ultra-precision grinding machine tool has a total of 18 motion errors, as shown in Table 2.

[0025] Table 2 Machine Tool Motion Error Items

[0026] In Table 2, Indicates linear error of the motion axis, subscript Indicates the direction of error. Indicates the axis of motion in a certain direction. , ; Indicates the angular displacement error of the moving axis, subscript Indicates the direction of error. Indicates the axis of motion in a certain direction. , ; Indicates the number of each error term. 1,2,3,…,18.

[0027] like Figure 4 As shown, taking the abrasive grains on the grinding wheel as the research object, let them be... To determine the component manufacturing process exist The coordinate values ​​below, based on the machine tool topology, The transfer path between the rigid body coordinate systems is as follows: - - - - - . The homogeneous transformation matrices between the rigid body coordinate systems are shown in Table 3.

[0028] Table 3 Coordinate Transformation Matrices

[0029] In Table 3 This represents the position matrix between adjacent objects. This represents the positional error matrix between adjacent objects. This represents the motion matrix between adjacent objects. Represents the motion error matrix between adjacent bodies , 1,2,3,…,6; , , These represent the motion quantities along the X-axis, Y-axis, and Z-axis, respectively. This represents a fourth-order identity matrix.

[0030] 303. Based on the position error matrix, construct the machine tool motion error model.

[0031] Here, let's assume exist The coordinate values ​​below are shown in formula (1):

[0032] Combination Figure 4 The machine tool topology shown in Table 3 and The homogeneous transformation matrix between the rigid body coordinate systems yields results for both the ideal case and the case considering machine tool motion errors. exist The coordinate values ​​below are as follows: and As shown:

[0033] Thus, an ideal motion model and a motion error model for a three-degree-of-freedom ultra-precision grinding machine tool were established. By analyzing the body coordinate system positions and topological relationships of each moving component, a position matrix under ideal conditions and a position error matrix considering errors were established. This allows for the accurate establishment of a machine tool motion error model that precisely evaluates the mapping relationship between the motion accuracy indicators of the machine tool's motion axes and the machining accuracy of its components.

[0034] 103. Based on the machine tool motion error model, determine the influence of motion error terms of each motion axis of the machine tool on the surface accuracy of the component.

[0035] Here, the actual surface shape affected by the motion accuracy of the machine tool is analyzed through a machine tool motion error model, and then the influence of the motion error terms of each motion axis of the machine tool on the surface shape accuracy of the components is analyzed. This can be achieved through the following steps 131 and 132 (not shown in the figure): 131. Based on the ideal motion model of the machine tool and the motion error model of the machine tool, determine the ideal surface shape and actual surface shape of the component corresponding to the motion error term of each motion axis of the machine tool.

[0036] Here, the position matrix between adjacent moving parts is first established and the ideal motion model of the machine tool is constructed. Then, based on the previous machine tool accuracy test results, the linear error is taken as 1 micrometer and the angular displacement error is taken as 1 arcsecond, with a numerical ratio of 1:1. The values ​​of each error term are individually substituted into the ideal motion model and the machine tool motion error model. The ideal surface shape of the component and the actual surface shape considering the influence of the machine tool motion accuracy are obtained through the ideal motion model and the machine tool motion error model, respectively.

[0037] In some possible implementations, the mapping relationship between the motion accuracy index of the machine tool's motion axis and the component machining accuracy is determined based on the machine tool motion error model; then, based on the mapping relationship, the influence of the machine tool's motion accuracy on the component surface shape is determined; finally, based on the influence of the machine tool's motion accuracy on the component surface shape, the actual surface shape considering the influence of the machine tool's motion accuracy is determined.

[0038] Here, based on the topological relationships of the moving parts of the machine tool and the positional relationships of the origin of the body coordinate system, a homogeneous coordinate transformation matrix is ​​established between adjacent rigid bodies to describe the position transfer of the object of interest between the rigid bodies. Considering the motion error of the machine tool's motion axes, a machine tool motion error model is established to determine the mapping relationship between the motion accuracy index of the machine tool's motion axes and the machining accuracy of the components. By analyzing the influence of the machine tool's motion accuracy on the surface shape of the components, the result is normalized to obtain the actual surface shape considering the influence of the machine tool's motion accuracy.

[0039] 132. Based on the ideal and actual surface shapes of the component, determine the influence of the motion error terms of each motion axis of the machine tool on the surface shape accuracy of the component.

[0040] Here, the influence of each error term on the component surface accuracy PV is analyzed by subtracting the actual surface shape from the ideal surface shape. In this way, by analyzing the ideal surface shape of the component corresponding to the motion error term of each motion axis of the machine tool and the actual surface shape considering the influence of the machine tool motion accuracy, the influence of the motion error term of each motion axis of the machine tool on the component surface accuracy can be accurately analyzed.

[0041] 104. Based on the influence of the motion error terms of each motion axis on the surface accuracy of the component and the motion error terms, a machine tool accuracy optimization allocation model is constructed.

[0042] Here, by combining the error sensitivity coefficients of the motion error terms of each motion axis of the computer tool with the motion error terms, a precise machine tool accuracy optimization allocation model can be built.

[0043] In some possible implementations, step 104 above can be achieved through steps 141 and 142 (not shown in the figure): 141. Based on the influence of the motion error terms of each motion axis on the surface accuracy of the component, determine the error sensitivity coefficient of the motion error terms of each motion axis of the machine tool.

[0044] Here, the influence of each error term on the component surface accuracy PV is analyzed by subtracting the actual surface shape from the ideal surface shape. The influence weights are normalized, and the weight calculation is shown in formula (2). The results are as follows: Figure 5 As shown, that is Figure 5 Curve 501 in the figure represents the normalized error sensitivity.

[0045] (2); in, Indicates the first The error surface shape PV value is obtained by subtracting the actual surface shape from the ideal surface shape under the error term. This represents the normalized error sensitivity coefficient for each error term. 1,2,3,…,18.

[0046] 142. Based on the sensitivity coefficient and the motion error term, a machine tool accuracy optimization allocation model is constructed.

[0047] In some possible implementations, an objective function characterizing the machine tool accuracy optimization allocation model is determined based on the sensitivity coefficient and the motion error term; and the machine tool accuracy optimization allocation model is constructed based on the objective function and preset constraints. For example, firstly, the value range of the motion error term for each motion axis and the component machining accuracy target are determined; then, the value range and the component machining accuracy target are used as the preset constraints, and the machine tool accuracy optimization allocation model is constructed based on the objective function.

[0048] Here, the sensitivity of machine tool errors is analyzed, and the sensitivity coefficients of each motion error term of the machine tool are determined. The sum of the machine tool error sensitivity coefficients and the multiplication of each motion error term of the machine tool is used as the objective function of the machine tool accuracy optimization allocation model. The range of values ​​of the machine tool motion error term and the component machining accuracy requirements are used as preset constraints to establish the machine tool accuracy optimization allocation model and solve for the motion accuracy index of each axis of the machine tool that meets the component machining accuracy.

[0049] Therefore, the machine tool accuracy optimization allocation model with component surface accuracy constraints is established as shown in formula (3): (3); in, The objective function of the machine tool accuracy optimization model is assigned. The maximum value of each error term. To consider the component surface shape for machine tool motion accuracy, For the ideal surface shape of the component, To ensure the surface accuracy of the component.

[0050] 105. Based on the machine tool accuracy optimization allocation model and the component surface accuracy requirements of the machine tool, the accuracy of the machine tool is allocated.

[0051] Here, by obtaining the surface accuracy requirements of the machine tool components, and using these accuracy requirements as constraints, the machine tool's accuracy is allocated by finding the optimal solution to the objective function.

[0052] In some possible implementations, the maximum value allowed for each motion error term is determined by constraining the value of each motion error term to meet the surface accuracy requirements of the component; and the accuracy of the machine tool is allocated based on the machine tool accuracy optimization allocation model and the maximum value allowed for each motion error term.

[0053] Here, based on the machine tool accuracy optimization allocation model shown in formula (3), with The values ​​should satisfy the constraints in the machine tool accuracy optimization allocation model. Solve the following steps. The minimum value is then used to obtain the maximum allowable value for each error term of the machine tool motion axis, thus achieving the minimum machine tool motion accuracy requirement to ensure the machining accuracy of the components. In the machine tool accuracy optimization allocation model, the surface shape of the component machining accuracy is used as a constraint, and its constraint equation includes... , … The high-order nonlinear equations are therefore used to solve the optimization variables in the machine tool accuracy optimization allocation model. The fmincon (minimum constraint nonlinear multivariable solver) solver from the MATLAB optimization toolbox is employed for variable optimization. The iterative solution process is as follows: Figure 6 As shown, the iterative solution process includes: First, define the optimization parameters, the optimization objective function, and the constraints on the optimization parameters.

[0054] Secondly, optimize the initial parameters.

[0055] Here, the optimization parameters and the objective function are initialized.

[0056] Next, optimize the solution of the objective maximum and minimum values ​​and the judgment of constraints.

[0057] Next, determine whether the constraints and the minimum objective function are satisfied. If satisfied, proceed to the next step and end the entire process; otherwise, use the interior point method to solve the problem and iterate the parameters. Then, solve for the maximum and minimum objective function and determine the constraints.

[0058] In some embodiments, after allocating the precision of the machine tool based on the machine tool precision optimization allocation model and the component surface precision requirements of the machine tool, firstly, the target machining object and the corresponding target surface precision of the ultra-precision grinding machine are obtained; then, based on the target surface precision and the machine tool precision optimization allocation model, the allocation result of the target machining object of the ultra-precision grinding machine is determined; and the allocation result is verified based on the machine tool motion error model to obtain the verification result; finally, based on the verification result, the machine tool precision optimization allocation model is updated; for example, the model parameters of the machine tool precision optimization allocation model are adjusted through the verification result so that the verification result output by the updated model is more in line with the target surface precision.

[0059] In a specific example, taking a 610 mm × 440 mm aspherical optical element as the target object to be machined by an ultra-precision grinding machine, its target surface accuracy is PV less than or equal to 5 micrometers. The optimized allocation results of its machine tool accuracy are shown in Table 4. f (E) The iterative convergence process is as follows Figure 7 As shown. Substituting the allocation results into the machine tool motion error model, the surface accuracy of the component under this accuracy condition is analyzed, and the results are as follows. Figure 8 As shown, the surface accuracy PV is 4.96 micrometers, which meets the target surface accuracy PV of less than or equal to 5 micrometers (μm), verifying the correctness of the "ultra-precision grinding machine accuracy optimization allocation method based on component surface accuracy constraints".

[0060] Table 4 Machine Tool Accuracy Optimization Allocation Results

[0061] In this embodiment of the invention, by determining the topological relationship between the moving parts of the machine tool, a machine tool motion error model characterizing the motion error of the moving parts is constructed, which improves the accuracy of the machine tool motion error model. Then, based on the machine tool motion error model, the influence of the motion error terms of each motion axis of the machine tool on the surface accuracy of the components is determined; and through the influence of the motion error terms of each motion axis on the surface accuracy of the components and the motion error terms themselves, a machine tool accuracy optimization allocation model is constructed. Thus, the accuracy of the machine tool is allocated based on this machine tool accuracy optimization allocation model and the surface accuracy requirements of the machine tool's components. In this way, using component machining accuracy as input, a machine tool motion error model characterizing the motion error of the moving parts is determined, thereby achieving the accuracy margin design of the ultra-precision grinding machine tool. Furthermore, the machine tool accuracy optimization allocation model can determine the machine tool motion accuracy index that meets the component machining accuracy requirements, reducing the development cost of the ultra-precision grinding machine tool.

[0062] This invention provides an ultra-precision grinding machine precision optimization allocation system. Please refer to [link / reference]. Figure 9The diagram illustrates the structural composition of an ultra-precision grinding machine accuracy optimization allocation system according to an embodiment of the present invention. The system 900 includes: The first determining module 901 is used to determine the topological relationship between the moving parts of the machine tool; The first construction module 902 is used to construct a machine tool motion error model characterizing the motion error of the moving parts based on the topological relationship; The second determining module 903 is used to determine the influence of the motion error terms of each motion axis of the machine tool on the surface accuracy of the component based on the machine tool motion error model; The second construction module 904 is used to construct a machine tool accuracy optimization allocation model based on the influence of the motion error terms of each motion axis on the surface accuracy of the component and the motion error terms. The allocation module 905 is used to allocate the precision of the machine tool based on the machine tool precision optimization allocation model and the component surface precision requirements of the machine tool.

[0063] In some possible implementations, the second construction module 904 is further configured to determine the error sensitivity coefficient of the motion error term of each motion axis of the machine tool based on the influence of the motion error term of each motion axis on the surface accuracy of the component; and to construct a machine tool accuracy optimization allocation model based on the sensitivity coefficient and the motion error term.

[0064] In some possible implementations, the second construction module 904 is further configured to determine an objective function characterizing the machine tool accuracy optimization allocation model based on the sensitivity coefficient and the motion error term; and to construct the machine tool accuracy optimization allocation model based on the objective function and preset constraints.

[0065] In some possible implementations, the second construction module 904 is further configured to determine the value range of the motion error term of each motion axis and the component machining accuracy target; and to construct the machine tool accuracy optimization allocation model based on the objective function, using the value range and the component machining accuracy target as the preset constraint conditions.

[0066] In some possible implementations, the first construction module 902 is further configured to determine the body coordinate system position of each moving component; establish a position matrix between adjacent moving components and a position error matrix between adjacent moving components based on the body coordinate system position of each moving component and the topological relationship; construct an ideal motion model of the machine tool based on the position matrix and the body coordinate system position; and construct a motion error model of the machine tool based on the position error matrix.

[0067] In some possible implementations, the second determining module 903 is further configured to determine the ideal surface shape and actual surface shape of the component corresponding to the motion error term of each motion axis of the machine tool based on the ideal motion model of the machine tool and the motion error model of the machine tool; and to determine the influence of the motion error term of each motion axis of the machine tool on the surface shape accuracy of the component based on the ideal surface shape and actual surface shape of the component.

[0068] In some possible implementations, the second determining module 903 is further configured to determine, based on the machine tool motion error model, the mapping relationship between the motion accuracy index of the machine tool's motion axis and the component machining accuracy; based on the mapping relationship, determine the influence of the machine tool's motion accuracy on the component surface shape; and based on the influence of the machine tool's motion accuracy on the component surface shape, determine the actual surface shape considering the influence of the machine tool's motion accuracy.

[0069] In some possible implementations, the allocation module 905 is further configured to determine the maximum allowable value of each motion error term, with the constraint that the value of each motion error term meets the surface accuracy requirements of the component; and to allocate the accuracy of the machine tool based on the machine tool accuracy optimization allocation model and the maximum allowable value of each motion error term.

[0070] In some possible implementations, the allocation module 905 is further configured to acquire the target machining object of the ultra-precision grinding machine and the corresponding target surface accuracy; determine the allocation result of the target machining object of the ultra-precision grinding machine based on the target surface accuracy and the machine tool accuracy optimization allocation model; verify the allocation result based on the machine tool motion error model to obtain the verification result; and update the machine tool accuracy optimization allocation model based on the verification result.

[0071] Optionally, the transmission medium can be a wired link (e.g., but not limited to, coaxial cable, optical fiber, and Digital Subscriber Line (DSL)) or a wireless link (e.g., but not limited to, Wireless Fidelity (WIFI), Bluetooth, and mobile device networks). It should be noted that the control device provided in the above embodiments is only an example illustrating the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device can be divided into different functional modules to complete all or part of the functions described above. Furthermore, the method embodiments provided in the above embodiments belong to the same concept, and their specific implementation processes are detailed in the method embodiments, and will not be repeated here.

[0072] Figure 10 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. For example, as shown... Figure 10As shown, the computer device 1000 includes: a memory 1001, a processor 1002, and a computer program 1003 stored in the memory 1001 and running on the processor 1002, wherein when the processor 1002 executes the computer program 1003, the computer device can execute any of the aforementioned ultra-precision grinding machine precision optimization allocation methods.

[0073] Furthermore, this embodiment of the invention also protects a control device, which may include a memory and a processor. The memory stores executable program code, and the processor is used to call and execute the executable program code to perform the ultra-precision grinding machine precision optimization allocation method provided by this embodiment of the invention. This embodiment can divide the control device into functional modules based on the above method example. For example, each module can correspond to a specific function, or two or more functions can be integrated into a processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents a logical functional division; in actual implementation, there may be other division methods. It should also be noted that all relevant content of each step involved in the above method embodiment can be referenced to the functional description of the corresponding functional module, and will not be repeated here. It should be understood that the control device provided in this embodiment is used to execute the above-mentioned ultra-precision grinding machine precision optimization allocation method, and therefore can achieve the same effect as the above-mentioned implementation method. When using integrated units, the control device may include a processing module and a storage module. When the control device is applied to a device, the processing module can be used to control and manage the device's actions. The storage module can be used to support the device in executing mutual program code, etc. The processing module may be a processor or a controller, which can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this invention. The processor may also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and microprocessors, etc., and the storage module may be a memory.

[0074] Furthermore, the control device provided in the embodiments of the present invention may specifically be a chip, component, or module. The chip may include a connected processor and a memory; wherein, the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute the ultra-precision grinding machine precision optimization allocation method provided in the above embodiments. This embodiment also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the aforementioned related method steps to implement the ultra-precision grinding machine precision optimization allocation method provided in the above embodiments.

[0075] This embodiment also provides a computer program product. When the computer program product is run on a computer, it causes the computer to execute the aforementioned related steps to achieve the ultra-precision grinding machine precision optimization allocation method provided in the above embodiment. The control device, computer-readable storage medium, computer program product, or chip provided in this embodiment are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they achieve can be referred to in the beneficial effects of the corresponding methods provided above, and will not be repeated here. Through the description of the above embodiments, those skilled in the art can understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In practical applications, the above functional allocation can be completed by different functional modules as needed, that is, the internal structure of the control device can be divided into different functional modules to complete all or part of the functions described above. In the embodiments provided by this invention, it should be understood that the disclosed control device and method can be implemented in other ways. For example, the control device embodiments described above are merely illustrative. For example, the division of modules or units is merely a logical functional division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another control device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, control device or unit, and can be electrical, mechanical or other forms.

[0076] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multiple task processing and parallel processing are possible or may be advantageous. The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. The above content is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for optimizing the allocation of precision in an ultra-precision grinding machine, characterized in that, The method includes: Determine the topological relationships between the moving parts of the machine tool; Based on the aforementioned topological relationship, a machine tool motion error model characterizing the motion error of the moving parts is constructed; Based on the machine tool motion error model, determine the influence of motion error terms of each motion axis of the machine tool on the surface accuracy of the component; Based on the influence of the motion error terms of each motion axis on the surface accuracy of the component and the motion error terms, a machine tool accuracy optimization allocation model is constructed. Based on the machine tool accuracy optimization allocation model and the component surface accuracy requirements of the machine tool, the accuracy of the machine tool is allocated.

2. The method according to claim 1, characterized in that, Based on the influence of the motion error terms of each motion axis on the surface accuracy of the component and the motion error terms, a machine tool accuracy optimization allocation model is constructed, including: Based on the influence of the motion error terms of each motion axis on the surface accuracy of the component, the error sensitivity coefficient of the motion error terms of each motion axis of the machine tool is determined; Based on the sensitivity coefficient and the motion error term, a machine tool accuracy optimization allocation model is constructed.

3. The method according to claim 2, characterized in that, The process of constructing a machine tool accuracy optimization allocation model based on the sensitivity coefficient and the motion error term includes: Based on the sensitivity coefficient and the motion error term, determine the objective function characterizing the machine tool accuracy optimization allocation model; Based on the objective function and preset constraints, the machine tool accuracy optimization allocation model is constructed.

4. The method according to claim 3, characterized in that, The process of constructing the machine tool accuracy optimization allocation model based on the objective function and preset constraints includes: Determine the value range of the motion error term for each motion axis and the target machining accuracy of the components; Using the value range and the component machining accuracy target as the preset constraints, the machine tool accuracy optimization allocation model is constructed based on the objective function.

5. The method according to claim 1, characterized in that, The process of constructing a machine tool motion error model characterizing the motion error of the moving parts based on the aforementioned topological relationship includes: Determine the body coordinate system position of each moving part; Based on the body coordinate system position of each moving component and the topological relationship, a position error matrix between adjacent moving components is established; Based on the position error matrix, the machine tool motion error model is constructed.

6. The method according to claim 5, characterized in that, The determination of the impact of motion error terms of each motion axis of the machine tool on the surface accuracy of the component, based on the machine tool motion error model, includes: Based on the body coordinate system position of each moving component and the topological relationship, a position matrix between adjacent moving components is established; An ideal motion model of the machine tool is constructed based on the position matrix and the position in the volume coordinate system. Based on the ideal motion model and the motion error model of the machine tool, the ideal surface shape and actual surface shape of the component corresponding to the motion error term of each motion axis of the machine tool are determined respectively. Based on the ideal and actual surface shapes of the component, the influence of the motion error terms of each motion axis of the machine tool on the surface shape accuracy of the component is determined.

7. The method according to claim 6, characterized in that, The method further includes: Based on the machine tool motion error model, the mapping relationship between the motion accuracy index of the machine tool's motion axis and the component machining accuracy is determined; Based on the mapping relationship, the influence of the machine tool's motion accuracy on the component's surface shape is determined; Based on the influence of the machine tool's motion accuracy on the component's surface shape, the actual surface shape considering the influence of the machine tool's motion accuracy is determined.

8. The method according to claim 1, characterized in that, The allocation of precision for the machine tool based on the machine tool precision optimization allocation model and the component surface precision requirements of the machine tool includes: The maximum allowable value of each motion error term is determined by constraining the requirement of surface accuracy of the component to be met by taking the values ​​of each motion error term as the constraint. The accuracy of the machine tool is allocated based on the machine tool accuracy optimization allocation model and the maximum allowable value of each motion error term.

9. The method according to claim 1, characterized in that, The method further includes: Obtain the target object to be machined on an ultra-precision grinding machine and the corresponding target surface accuracy; Based on the target surface accuracy and the machine tool accuracy optimization allocation model, the allocation result of the target machining object of the ultra-precision grinding machine is determined; The allocation result is verified based on the machine tool motion error model to obtain the verification result; Based on the verification results, the machine tool accuracy optimization allocation model is updated.

10. A precision optimization and allocation system for an ultra-precision grinding machine, characterized in that, The system includes: The first determining module is used to determine the topological relationships between the moving parts of the machine tool; The first construction module is used to construct a machine tool motion error model that characterizes the motion error of the moving parts based on the topological relationship; The second determining module is used to determine the influence of the motion error terms of each motion axis of the machine tool on the surface accuracy of the component based on the machine tool motion error model; The second construction module is used to construct a machine tool accuracy optimization allocation model based on the influence of the motion error terms of each motion axis on the surface accuracy of the component and the motion error terms. The allocation module is used to allocate the precision of the machine tool based on the machine tool precision optimization allocation model and the component surface precision requirements of the machine tool.

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