Multi-axis parallel kinematic machine tool error compensation method and apparatus, device and storage medium

Abstract

Disclosed in the present invention are a multi-axis parallel kinematic machine tool error compensation method and apparatus, a device and a storage medium, which are used for solving the problem of poor precision of multi-axis parallel kinematic machine tool error compensation methods. The method comprises: constructing a theoretical Jacobian model; respectively using geometric parameters to construct single geometric error models; using the theoretical Jacobian model and the single geometric error models to construct modeling error-containing single geometric error models; solving the modeling error-containing single geometric error models, so as to obtain modeling error-containing single geometric errors; substituting the modeling error-containing single geometric errors into the theoretical Jacobian model, so as to construct correction-quantity-containing Jacobian models corresponding to the geometric parameters; on the basis of the correction-quantity-containing Jacobian models, generating motor correction quantities; according to the motor correction quantities, calculating corrected total motor displacements; substituting the corrected total motor displacements into an error prediction evaluation model, so as to calculate predicted compensation errors with respect to the different geometric parameters; and selecting from amongst the predicted compensation errors the minimum value as a target compensation error.

Description

A multi-axis parallel machine tool error compensation method, device, equipment and storage medium Technical Field

[0001] The present invention relates to the technical field of error compensation, and in particular to a multi-axis parallel machine tool error compensation method, device, equipment and storage medium. Background Art

[0002] With the development of technologies in microelectronics, military industry, aerospace, etc., the requirements for parts processing accuracy and complexity are getting higher and higher. Multi-degree-of-freedom mechanisms represented by precision five-axis machine tools and high-precision robots are very popular. However, due to manufacturing and assembly errors, there is a large deviation between the actual structure and the theoretical structure of the mechanism, which reduces the positioning accuracy of the mechanism. Error compensation is a method that can effectively improve positioning accuracy, but its compensation effect is very dependent on the accuracy of the error model established. The traditional multi-axis end-effector error compensation method is mainly based on Jacobian modeling. However, in the method based on Jacobian matrix compensation, there is a certain error between the geometric parameters in the Jacobian matrix and the actual parameters. In addition, the equivalent infinitesimal substitution and the discarding of high-order small quantities used in Jacobian modeling will lead to modeling errors in the established Jacobian model, resulting in residual errors after multi-axis error compensation, affecting the operational accuracy of the end-effector of the mechanism.

[0003] Summary of the Invention

[0004] The present invention provides a multi-axis parallel machine tool error compensation method, device, equipment and storage medium, which are used to solve the technical problem of poor accuracy of existing multi-axis parallel machine tool error compensation methods.

[0005] The present invention provides a multi-axis parallel machine tool error compensation method, comprising:

[0006] Constructing a theoretical Jacobian model of the multi-axis parallel machine tool;

[0007] Acquiring a plurality of geometric parameters of the theoretical Jacobian model, and constructing a single geometric error model using each of the geometric parameters;

[0008] Using the theoretical Jacobi model and the single geometric error model to construct a single geometric error model containing modeling error;

[0009] Solving the single geometric error model containing the modeling error to obtain a single geometric error with the modeling error;

[0010] Substituting the single geometric error with modeling error into the theoretical Jacobian model to construct a Jacobian model with correction;

[0011] generating a motor correction value of the multi-axis parallel machine tool based on the Jacobi model with correction value;

[0012] Calculating the corrected total displacement of the motor according to the motor correction amount;

[0013] Substitute the total displacement of each corrected motor into the error prediction and evaluation model to calculate the prediction compensation error under different geometric parameters;

[0014] The minimum value of the predicted compensation errors corresponding to the geometric parameters is selected as the target compensation error.

[0015] Optionally, the step of constructing a theoretical Jacobian model of the multi-axis parallel machine tool includes:

[0016] Obtaining a motor compensation amount and an end effector error of the multi-axis parallel machine tool;

[0017] A theoretical Jacobian model is constructed using the motor compensation and the end effector error.

[0018] Optionally, the step of constructing a single geometric error model containing modeling error by using the theoretical Jacobian model and the single geometric error model includes:

[0019] Calculating a modeling error difference between the theoretical Jacobian model and the single geometric error model;

[0020] The modeling error difference is substituted into the single geometric error model to construct a single geometric error model containing the modeling error.

[0021] Optionally, the step of substituting the corrected total displacements of the motors into an error prediction and evaluation model to calculate the predicted compensation errors under different geometric parameters includes:

[0022] Inputting the corrected total displacement of the motor into a preset virtual linear model to obtain a corrected output of the motor;

[0023] Calculating a theoretical virtual output of the virtual linear model under a theoretical motor input;

[0024] Calculating a first output ratio of the motor corrected output to a theoretical virtual output;

[0025] Get the actual model deviation coefficient;

[0026] Calculating a second output ratio of the motor corrected output to the actual physical model output using the actual model deviation coefficient and the first output ratio;

[0027] Obtaining a kinematics theoretical output of the virtual linear model under the theoretical motor input;

[0028] The second output ratio and the kinematic theory output are used to calculate prediction compensation errors under different geometric parameters.

[0029] The present invention also provides an error compensation device for a multi-axis parallel machine tool, comprising:

[0030] A theoretical Jacobian model building module, used to build a theoretical Jacobian model of the multi-axis parallel machine tool;

[0031] a single geometric error model construction module, used to obtain a plurality of geometric parameters of the theoretical Jacobian model and respectively construct a single geometric error model using each of the geometric parameters;

[0032] A single geometric error model construction module including modeling error is used to construct a single geometric error model including modeling error by using the theoretical Jacobi model and the single geometric error model;

[0033] A solving module, configured to solve the single geometric error model containing the modeling error to obtain a single geometric error with the modeling error;

[0034] A Jacobian model construction module with correction, used for substituting the single geometric error with modeling error into the theoretical Jacobian model to construct the Jacobian model with correction;

[0035] A motor correction value generation module, configured to generate a motor correction value of the multi-axis parallel machine tool based on the Jacobi model with correction value;

[0036] A module for calculating the total displacement of the motor after correction, used for calculating the total displacement of the motor after correction according to the motor correction amount;

[0037] The error prediction and evaluation module is used to substitute the total displacement of each corrected motor into the error prediction and evaluation model to calculate the predicted compensation error under different geometric parameters;

[0038] The target compensation error selection module is used to select the minimum value of the predicted compensation errors corresponding to the geometric parameters as the target compensation error.

[0039] Optionally, the theoretical Jacobi model construction module includes:

[0040] A motor compensation amount and end effector error acquisition submodule, used to acquire the motor compensation amount and end effector error of the multi-axis parallel machine tool;

[0041] The theoretical Jacobian model construction submodule is used to construct a theoretical Jacobian model using the motor compensation amount and the end effector error.

[0042] Optionally, the single geometric error model construction module containing modeling error includes:

[0043] A modeling error difference calculation submodule, used to calculate the modeling error difference between the theoretical Jacobian model and the single geometric error model;

[0044] The submodule for constructing a single geometric error model including modeling errors is used to substitute the modeling error differences into the single geometric error model to construct a single geometric error model including modeling errors.

[0045] Optionally, the error prediction and evaluation module includes:

[0046] A motor correction output acquisition submodule is used to input the corrected total motor displacement into a preset virtual linear model to obtain a motor correction output;

[0047] A theoretical virtual output calculation submodule, used to calculate the theoretical virtual output of the virtual linear model under theoretical motor input;

[0048] A first output ratio calculation submodule, configured to calculate a first output ratio between the motor corrected output and a theoretical virtual output;

[0049] The actual model deviation coefficient acquisition submodule is used to obtain the actual model deviation coefficient;

[0050] a second output ratio calculation submodule, configured to calculate a second output ratio of the motor corrected output to the actual physical model output using the actual model deviation coefficient and the first output ratio;

[0051] A kinematics theory output acquisition submodule, configured to acquire the kinematics theory output of the virtual linear model under the theoretical motor input;

[0052] The motor correction actual output calculation submodule is used to calculate the prediction compensation error under different geometric parameters using the second output ratio and the kinematic theory output.

[0053] The present invention further provides an electronic device, comprising a processor and a memory:

[0054] The memory is used to store program code and transmit the program code to the processor;

[0055] The processor is configured to execute any one of the above multi-axis parallel machine tool error compensation methods according to the instructions in the program code.

[0056] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store program code, and the program code is used to execute the multi-axis parallel machine tool error compensation method as described in any one of the above items.

[0057] As can be seen from the above technical solution, the present invention has the following advantages: The present invention discloses a method for error compensation of a multi-axis parallel machine tool, comprising: constructing a theoretical Jacobian model of the multi-axis parallel machine tool; obtaining several geometric parameters of the theoretical Jacobian model and constructing a single geometric error model using each geometric parameter; constructing a single geometric error model containing modeling error using the theoretical Jacobian model and the single geometric error model; solving the single geometric error model containing modeling error to obtain a single geometric error with modeling error; substituting the single geometric error with modeling error into the theoretical Jacobian model to construct a Jacobian model with correction; generating motor corrections for the multi-axis parallel machine tool based on the Jacobian model with corrections; calculating a corrected total motor displacement based on the motor corrections; substituting each corrected total motor displacement into an error prediction and evaluation model to calculate predicted compensation errors under different geometric parameters; and selecting the minimum value of the predicted compensation errors corresponding to each geometric parameter as the target compensation error. This improves the accuracy of error compensation of the multi-axis parallel machine tool. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

[0059] Figure 1 is a schematic diagram of the residual error after Jacobi compensation;

[0060] FIG2 is a flowchart of a multi-axis parallel machine tool error compensation method provided by an embodiment of the present invention;

[0061] FIG3 is a flowchart of a multi-axis parallel machine tool error compensation method according to another embodiment of the present invention;

[0062] FIG4 is a structural block diagram of an error compensation device for a multi-axis parallel machine tool provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0063] The traditional error compensation method for multi-axis end effector is mainly through Jacobian modeling. However, in the method based on Jacobian matrix compensation, there is a certain error between the geometric parameters in the Jacobian matrix and the actual parameters. Accurately obtaining the geometric parameter correction of the Jacobian model and correcting the Jacobian model are the keys to improving the accuracy of the multi-axis end posture. In this process, the geometric parameter error in the Jacobian model and the modeling error introduced by the equivalent replacement of the Jacobian solution process (equivalent infinitesimal replacement and discarding high-order small quantities), as well as different single geometric errors will produce modeling error coupling after being substituted into the Jacobian model, resulting in unnecessary compensation effects and affecting the accuracy of error compensation. As shown in Figure 1, Figure 1 is a schematic diagram of the residual error after Jacobian compensation (where R act+jco is the theoretical Jacobi-compensated attitude, P act+jco is the theoretical Jacobian position after compensation, R jm is the theoretical posture, P jm is the theoretical position, R act is the actual posture, P act is the actual position, ΔR is the theoretical attitude error, ΔP is the theoretical position error, ΔR res is the residual attitude error after theoretical Jacobi compensation, ΔR jco is the actual attitude error compensated by the theoretical Jacobian model, ΔP res is the residual position error after theoretical Jacobi compensation, ΔP jco is the actual position error compensated by the theoretical Jacobian model). In view of this, embodiments of the present invention provide a multi-axis parallel machine tool error compensation method, apparatus, device, and storage medium for solving the technical problem of poor accuracy of existing multi-axis parallel machine tool error compensation methods.

[0064] In order to make the purpose, features, and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0065] Please refer to FIG. 2 , which is a flowchart of a multi-axis parallel machine tool error compensation method provided by an embodiment of the present invention.

[0066] The present invention provides a multi-axis parallel machine tool error compensation method, which may specifically include the following steps:

[0067] Step 201, constructing a theoretical Jacobian model of a multi-axis parallel machine tool;

[0068] Step 202: obtaining several geometric parameters of the theoretical Jacobian model, and constructing a single geometric error model using each geometric parameter;

[0069] Geometric error: The deviation of the actual shape, direction and position of each element of a part from the ideal shape, direction and position is called geometric error.

[0070] In practical applications, traditional multi-axis end-effector error compensation methods primarily rely on Jacobian modeling. However, in Jacobian matrix-based compensation methods, there is a certain degree of error between the geometric parameters in the Jacobian matrix and the actual parameters. This invention eliminates the geometric errors in the Jacobian model by constructing a theoretical Jacobian model and a single geometric error model for a multi-axis parallel machine tool.

[0071] Jacobian Matrix: In vector calculus, the Jacobian matrix is ​​a matrix of first-order partial derivatives arranged in a certain order. Its determinant is called the Jacobian determinant. The importance of the Jacobian matrix lies in its representation of the best linear approximation to a differentiable equation and given points. Therefore, the Jacobian matrix is ​​analogous to the derivative of a multivariate function.

[0072] Step 203: constructing a single geometric error model containing modeling error using the theoretical Jacobian model and the single geometric error model;

[0073] Step 204 , solving a single geometric error model including a modeling error to obtain a single geometric error with a modeling error;

[0074] After generating the theoretical Jacobian model and the single geometric error model, the theoretical Jacobian model and the single geometric error model can be used to construct a single geometric error model containing the modeling error. Then, by solving the single geometric error model containing the modeling error, the single geometric error with the modeling error can be obtained.

[0075] Step 205: Substitute the single geometric error with the modeling error into the theoretical Jacobian model to construct a Jacobian model with a correction amount;

[0076] After obtaining the single geometric error with modeling error, it is substituted into the theoretical Jacobian model to construct a Jacobian model with correction amount.

[0077] Step 206 , generating motor correction values ​​for the multi-axis parallel machine tool based on the Jacobi model with correction values;

[0078] Step 207, calculating the corrected total displacement of the motor according to the motor correction amount;

[0079] After obtaining the Jacobian model with corrections, the motor corrections for the multi-axis parallel machine tool can be generated based on the Jacobian model with corrections. The corrected total motor displacement can then be calculated based on the motor corrections.

[0080] Step 208 , substituting the corrected total displacement of each motor into an error prediction and evaluation module to calculate the predicted compensation error under different geometric parameters;

[0081] After obtaining the corrected total motor displacement, the error prediction and evaluation module can be used to calculate the prediction compensation error caused by different geometric parameters.

[0082] Step 209 : Select the minimum value of the predicted compensation errors corresponding to the geometric parameters as the target compensation error.

[0083] After obtaining the predicted compensation errors calculated based on the various geometric parameters, the smallest compensation error can be selected as the target compensation error of the multi-axis parallel machine tool.

[0084] The present invention constructs a theoretical Jacobian model of a multi-axis parallel machine tool; obtains several geometric parameters of the theoretical Jacobian model and constructs a single geometric error model using each geometric parameter; constructs a single geometric error model containing modeling error using the theoretical Jacobian model and the single geometric error model; solves the single geometric error model containing modeling error to obtain a single geometric error with modeling error; substitutes the single geometric error with modeling error into the theoretical Jacobian model to construct a Jacobian model with correction; generates motor corrections for the multi-axis parallel machine tool based on the Jacobian model with corrections; calculates the corrected total motor displacement based on the motor corrections; substitutes each corrected total motor displacement into an error prediction and evaluation module to calculate predicted compensation errors under different geometric parameters; and selects the minimum value of the predicted compensation errors corresponding to each geometric parameter as the target compensation error. This improves the accuracy of error compensation for the multi-axis parallel machine tool.

[0085] Please refer to FIG3 , which is a flowchart of a multi-axis parallel machine tool error compensation method provided by another embodiment of the present invention. Specifically, the method may include the following steps:

[0086] Step 301, obtaining the motor compensation and end effector error of the multi-axis parallel machine tool;

[0087] Step 302 , constructing a theoretical Jacobian model using motor compensation and end effector error;

[0088] In an embodiment of the present invention, the theoretical Jacobian model is:

[0089] in, is the motor compensation, J is the theoretical Jacobian model, and δE is the end effector error.

[0090] Step 303: obtaining several geometric parameters of the theoretical Jacobian model, and constructing a single geometric error model using each geometric parameter;

[0091] In the embodiment of the present invention, a single geometric parameter of the theoretical Jacobian model may be slightly perturbed or differentiated to establish a single geometric error model.

[0092] Among them, the single geometric error model is as follows:

[0093] Expanded to: δz+δsH1+(δcH2+δcδH2+cδH2)H1+δH2Q=0

[0094] Among them, z is the position matrix, s is the posture matrix composed of sin function, H1 is the geometric parameter matrix 1, H2 is the geometric parameter matrix 2, c is the posture matrix composed of cos function, jm is the theoretical value, δ is the posture parameter, and Q is the motor displacement.

[0095] Step 304 , constructing a single geometric error model including modeling error using the theoretical Jacobian model and the single geometric error model;

[0096] After obtaining the theoretical Jacobian model and the single geometric error model, the theoretical Jacobian model and the single geometric error model can be used to construct a single geometric error model containing modeling error.

[0097] In one example, step 304 may include the following sub-steps:

[0098] S11, calculate the modeling error difference between the theoretical Jacobian model and the single geometric error model;

[0099] In the embodiment of the present invention, the modeling error difference of the theoretical Jacobian model and the single geometric error model is:

[0100] Among them, α is the attitude parameter.

[0101] S12, substituting the modeling error difference into the single geometric error model to construct a single geometric error model containing the modeling error.

[0102] The modeling error difference ΔE JM Substituting into the single geometric error model, the single geometric error model containing modeling error can be obtained as follows:

[0103] Step 305, solving a single geometric error model including a modeling error to obtain a single geometric error with a modeling error;

[0104] Solving the single geometric error model with modeling error, we can get the single geometric error with modeling error as:

[0105] Among them, δH1 and δH2 are single geometric errors with modeling errors.

[0106] Step 306: Substitute the single geometric error with the modeling error into the theoretical Jacobian model to construct a Jacobian model with a correction amount;

[0107] Substituting δH1 or δH2 into the theoretical Jacobian model, the Jacobian model with correction can be generated as follows:

[0108] in, is the Jacobian model after the geometric parameter H1 is modified, is the Jacobian model after the modified geometric parameter H2, and JM is the theoretical value.

[0109] Step 307 , generating motor correction values ​​for the multi-axis parallel machine tool based on the Jacobi model with correction values;

[0110] The motor correction values ​​of the multi-axis parallel machine tool generated based on the Jacobi model with correction values ​​are as follows:

[0111] in, To correct the motor correction amount formed by the geometric parameter H1, The motor correction amount is formed by correcting the geometric parameter H2.

[0112] Step 308, calculating the corrected total displacement of the motor according to the motor correction amount;

[0113] The total displacement of the motor after correction calculated based on the motor correction amount is:

[0114] in, To correct the total displacement of the motor formed by the geometric parameter H1, is the total displacement of the motor formed by the modified geometric parameter H2, Q jm is the theoretical value of the motor.

[0115] Step 309 , substituting the corrected total displacement of each motor into the error prediction and evaluation model to calculate the prediction compensation error under different geometric parameters;

[0116] After calculating the corrected total motor displacement, the error prediction and evaluation module can be used to calculate the predicted compensation error under different geometric parameters.

[0117] In one example, step 309 may include the following sub-steps:

[0118] S21, inputting the corrected total displacement of the motor into a preset virtual linear model to obtain a corrected motor output;

[0119] S22, calculates the theoretical virtual output of the virtual linear model under the theoretical motor input;

[0120] S23, calculating a first output ratio between the motor corrected output and the theoretical virtual output;

[0121] S24, obtaining the actual model deviation coefficient;

[0122] S25, calculating a second output ratio between the motor correction output and the actual physical model output using the actual model deviation coefficient and the first output ratio;

[0123] S26, obtaining the kinematic theoretical output of the virtual linear model under theoretical motor input;

[0124] S27, using the second output ratio and kinematic theory output, calculate the prediction compensation error under different geometric parameters.

[0125] In the specific implementation, the sensitivity-based virtual linear model is:

[0126] in, is the end effector displacement, σ is the sensitivity coefficient, that is, J -1 The matrix elements in .

[0127] The theoretical virtual output of the virtual linear model under the theoretical motor input is:

[0128] The actual model deviation coefficient is:

[0129] in, is the actual model deviation coefficient, ΔX is the measured kinematic error, and X is the kinematic theory output.

[0130] The corrected total motor displacement Q jm+Δ Substituting into the virtual linear model, the motor correction output can be obtained as:

[0131] The first output ratio of the motor correction output to the theoretical virtual output is:

[0132] The second output ratio of the motor correction output to the actual physical model output is:

[0133] The actual output of the motor correction is: A=η·*X

[0134] The predicted compensation error of the multi-axis parallel machine tool under different geometric parameters is calculated as follows:

[0135] Step 310 : Select the minimum value of the predicted compensation errors corresponding to the geometric parameters as the target compensation error.

[0136] After obtaining the compensation errors calculated based on the various geometric parameters, the smallest predicted compensation error can be selected as the target compensation error of the multi-axis parallel machine tool.

[0137] The present invention converts the original nonlinear indeterminate equation into a linear equation by accurately solving the analytical solution of the Jacobian geometric parameters including geometric errors and modeling errors, avoiding the problems of multiple solutions and no solutions during direct solution, as well as the weak generalization problem of the iterative method, eliminating the residual error of the traditional Jacobi method, and making the positioning accuracy of the multi-axis mechanism higher, so as to achieve the purpose of the multi-axis mechanism or the end effector of the equipment meeting the high-precision operation.

[0138] Please refer to FIG4 , which is a structural block diagram of an error compensation device for a multi-axis parallel machine tool provided by an embodiment of the present invention.

[0139] An embodiment of the present invention provides an error compensation device for a multi-axis parallel machine tool, comprising:

[0140] Theoretical Jacobian model construction module 401 is used to construct a theoretical Jacobian model of a multi-axis parallel machine tool;

[0141] A single geometric error model construction module 402 is used to obtain a plurality of geometric parameters of the theoretical Jacobian model and construct a single geometric error model using each geometric parameter;

[0142] A single geometric error model construction module 403 including modeling error is used to construct a single geometric error model including modeling error using a theoretical Jacobi model and a single geometric error model;

[0143] A solving module 404 is used to solve a single geometric error model including a modeling error to obtain a single geometric error with a modeling error;

[0144] A Jacobian model with correction amount construction module 405 is used to substitute a single geometric error with a modeling error into a theoretical Jacobian model to construct a Jacobian model with correction amount;

[0145] A motor correction value generation module 406 is used to generate motor correction values ​​for a multi-axis parallel machine tool based on a Jacobi model with correction values;

[0146] A corrected motor total displacement calculation module 407 is used to calculate the corrected motor total displacement according to the motor correction value;

[0147] The error prediction and evaluation calculation module 408 is used to substitute the total displacement of each corrected motor into the error prediction and evaluation model to calculate the prediction compensation error under different geometric parameters;

[0148] The target compensation error selection module 409 is used to select the minimum value of the predicted compensation errors corresponding to the geometric parameters as the target compensation error.

[0149] In this embodiment of the present invention, the theoretical Jacobian model construction module 401 includes:

[0150] The motor compensation and end-effector error acquisition submodule is used to obtain the motor compensation and end-effector error of the multi-axis parallel machine tool;

[0151] The theoretical Jacobian model construction submodule is used to construct a theoretical Jacobian model using motor compensation and end-effector error.

[0152] In an embodiment of the present invention, a single geometric error model construction module containing modeling errors includes:

[0153] Modeling error difference calculation submodule, used to calculate the modeling error difference between the theoretical Jacobian model and the single geometric error model;

[0154] The submodule for constructing a single geometric error model including modeling error is used to substitute the modeling error difference into the single geometric error model to construct a single geometric error model including modeling error.

[0155] In this embodiment of the present invention, the error prediction evaluation calculation module 408 includes:

[0156] The motor correction output acquisition submodule is used to input the corrected total motor displacement into a preset virtual linear model to obtain the motor correction output;

[0157] Theoretical virtual output calculation submodule, used to calculate the theoretical virtual output of the virtual linear model under theoretical motor input;

[0158] A first output ratio calculation submodule, used to calculate a first output ratio between the motor corrected output and the theoretical virtual output;

[0159] The actual model deviation coefficient acquisition submodule is used to obtain the actual model deviation coefficient;

[0160] A second output ratio calculation submodule, configured to calculate a second output ratio between the motor correction output and the actual physical model output using the actual model deviation coefficient and the first output ratio;

[0161] Kinematics theory output acquisition submodule, used to obtain the kinematics theory output of the virtual linear model under theoretical motor input;

[0162] The motor correction actual output calculation submodule is used to calculate the prediction compensation error under different geometric parameters using the second output ratio and kinematic theory output.

[0163] An embodiment of the present invention further provides an electronic device, the device including a processor and a memory:

[0164] The memory is used to store program codes and transmit the program codes to the processor;

[0165] The processor is used to execute the multi-axis parallel machine tool error compensation method according to the instructions in the program code.

[0166] An embodiment of the present invention further provides a computer-readable storage medium, which is used to store program code, and the program code is used to execute the multi-axis parallel machine tool error compensation method of the embodiment of the present invention.

[0167] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0168] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0169] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, apparatus, or computer program products. Thus, embodiments of the present invention may take the form of a fully hardware embodiment, a fully software embodiment, or an embodiment combining software and hardware. Furthermore, embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0170] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate a device for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0171] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0172] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce computer-implemented processing, so that the instructions executed on the computer or other programmable terminal device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0173] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they are aware of the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0174] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or terminal device that includes the element.

[0175] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-axis parallel machine tool error compensation method, characterized in that: include: Constructing a theoretical Jacobian model of the multi-axis parallel machine tool; Acquire several geometric parameters of the theoretical Jacobian model, and respectively use the geometric parameters to construct a single geometric error model; Using the theoretical Jacobi model and the single geometric error model to construct a single geometric error model containing modeling errors; Solving the single geometric error model containing modeling error to obtain a single geometric error with modeling error; Substituting the single geometric error with modeling error into the theoretical Jacobian model to construct a Jacobian model with correction; Generate a motor correction amount of the multi-axis parallel machine tool based on the Jacobi model with correction amount; Calculate the corrected total displacement of the motor according to the motor correction amount; Substituting the total displacement of each corrected motor into the error prediction and evaluation model to calculate the prediction compensation error under different geometric parameters; The minimum value of the predicted compensation errors corresponding to the geometric parameters is selected as the target compensation error.

2. The method according to claim 1, characterized in that The step of constructing a theoretical Jacobian model of the multi-axis parallel machine tool comprises: Obtaining a motor compensation amount and an end effector error of the multi-axis parallel machine tool; The motor compensation amount and the end effector error are used to construct a theoretical Jacobian model.

3. The method according to claim 1, characterized in that The step of using the theoretical Jacobian model and the single geometric error model to construct a single geometric error model containing modeling errors comprises: Calculating a modeling error difference between the theoretical Jacobian model and the single geometric error model; The modeling error difference is substituted into the single geometric error model to construct a single geometric error model containing the modeling error.

4. The method according to claim 1, characterized in that: The step of substituting each corrected total displacement of the motor into the error prediction and evaluation model to calculate the prediction compensation error under different geometric parameters includes: Inputting the corrected total displacement of the motor into a preset virtual linear model to obtain a corrected output of the motor; Calculating a theoretical virtual output of the virtual linear model under a theoretical motor input; Calculating a first output ratio of the motor corrected output to a theoretical virtual output; Get the actual model deviation coefficient; Calculating a second output ratio of the motor correction output to the actual physical model output using the actual model deviation coefficient and the first output ratio; Obtaining a kinematic theory output of the virtual linear model under the theoretical motor input; The second output ratio and the kinematic theory output are used to calculate the prediction compensation error under different geometric parameters.

5. A multi-axis parallel machine tool error compensation device, characterized in that: include: A theoretical Jacobian model building module, used to build a theoretical Jacobian model of the multi-axis parallel machine tool; A single geometric error model construction module is used to obtain a plurality of geometric parameters of the theoretical Jacobian model and respectively use the geometric parameters to construct a single geometric error model; A single geometric error model construction module including modeling error, used to construct a single geometric error model including modeling error by using the theoretical Jacobian model and the single geometric error model; A solving module, used for solving the single geometric error model containing modeling error to obtain a single geometric error with modeling error; A Jacobian model construction module with correction, used for substituting the single geometric error with modeling error into the theoretical Jacobian model to construct the Jacobian model with correction; A motor correction value generation module, used for generating the motor correction value of the multi-axis parallel machine tool based on the Jacobi model with correction value; A corrected motor total displacement calculation module, used to calculate the corrected motor total displacement according to the motor correction amount; The error prediction and evaluation module is used to substitute the total displacement of each corrected motor into the error prediction and evaluation model to calculate the prediction compensation error under different geometric parameters; The target compensation error selection module is used to select the minimum value of the predicted compensation errors corresponding to the geometric parameters as the target compensation error.

6. The device according to claim 5, characterized in that The theoretical Jacobi model building blocks include: A motor compensation amount and end effector error acquisition submodule, used to acquire the motor compensation amount and end effector error of the multi-axis parallel machine tool; The theoretical Jacobian model construction submodule is used to construct a theoretical Jacobian model using the motor compensation amount and the end effector error.

7. The device according to claim 5, characterized in that The single geometric error model construction module containing modeling errors includes: A modeling error difference calculation submodule, used for calculating the modeling error difference between the theoretical Jacobian model and the single geometric error model; The submodule for constructing a single geometric error model including modeling errors is used to substitute the modeling error differences into the single geometric error model to construct a single geometric error model including modeling errors.

8. The device according to claim 5, characterized in that The error prediction evaluation module comprises: A motor correction output acquisition submodule is used to input the corrected motor total displacement into a preset virtual linear model to obtain a motor correction output; A theoretical virtual output calculation submodule, used for calculating the theoretical virtual output of the virtual linear model under theoretical motor input; A first output ratio calculation submodule, used for calculating a first output ratio between the motor corrected output and the theoretical virtual output; An actual model deviation coefficient acquisition submodule is used to obtain the actual model deviation coefficient; A second output ratio calculation submodule, configured to calculate a second output ratio of the motor correction output to the actual physical model output by using the actual model deviation coefficient and the first output ratio; A kinematics theory output acquisition submodule, used to acquire the kinematics theory output of the virtual linear model under the theoretical motor input; The motor correction actual output calculation submodule is used to calculate the prediction compensation error under different geometric parameters by using the second output ratio and the kinematic theory output.

9. An electronic device, characterized in that: The device comprises a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the multi-axis parallel machine tool error compensation method according to any one of claims 1 to 4 according to the instructions in the program code.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program codes, and the program codes are used to execute the multi-axis parallel machine tool error compensation method according to any one of claims 1 to 4.

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