Space precision evaluation compensation method for door-shaped vertical machining center

Abstract

The invention discloses a door-shaped vertical machining center spatial precision evaluation compensation method, which specifically comprises the following steps of: establishing an error model by combining influence factors of spatial precision; constructing a spatial precision evaluation system; providing a machine tool space precision evaluation method in combination with an evaluation system; error compensation is analyzed according to an evaluation result, and a spatial precision evaluation method is perfected; according to the method, the spatial precision of the high-speed and high-precision door-shaped vertical machining center is deeply analyzed, influence factors of the high-speed and high-precision door-shaped vertical machining center are discussed, an effective evaluation method is provided, a set of systematic precision evaluation process is provided in combination with establishment and analysis of a spatial error model, and corresponding error compensation is performed in combination with an evaluation result; and a theoretical basis and practical guidance are provided for improving the precision stability and the machining quality of the machining center.

Description

Technical Field

[0001] The invention relates to the technical field of machine tool processing, in particular to a spatial accuracy evaluation and compensation method for a gate-type vertical machining center. Background Art

[0002] As a core indicator for evaluating the performance of a machining center, spatial accuracy is affected by a variety of internal and external factors. Internal factors mainly include the structural design of the machine tool and the quality control during the manufacturing process. The rationality of the structural design is directly related to the rigidity and stability of the machine tool, which in turn affects the machining accuracy. For example, the design of the columns and beams of a portal vertical machining center must ensure sufficient support and minimal deformation. Material selection, heat treatment process, and assembly accuracy during the manufacturing process are also key internal factors that affect accuracy.

[0003] External factors involve a wider range of content. Changes in ambient temperature can cause thermal expansion or contraction of the machine tool structure, causing processing errors. Changes in humidity may also affect the physical properties of the material and lubrication conditions. In addition, vibration and impact loads to which the machine tool is subjected during use can also have an adverse effect on its accuracy. The material properties of the workpiece itself and the clamping method will also affect the processing results. The existence of these external factors makes precision control more complicated.

[0004] Affected by internal and external factors of the machine tool, the spatial accuracy of the machine tool will produce certain errors. The types of errors can be classified according to their manifestations and generation mechanisms. Static errors usually refer to the inherent deviations of the machine tool when it is not working, such as the straightness error of the guide rail, the radial runout of the spindle, etc. These errors are relatively stable and their impact can be reduced through calibration and compensation. Dynamic errors are generated during the operation of the machine tool, such as displacement errors caused by inertial forces caused by accelerated motion, or vibration errors caused by uneven force during cutting. The randomness and complexity of dynamic errors make them more difficult to predict and control. Therefore, in-depth research and effective management of static and dynamic errors are crucial to improving the spatial accuracy of machining centers. Summary of the invention

[0005] The main purpose of the present invention is to provide a method for evaluating and compensating the spatial accuracy of a portal-type vertical machining center, aiming to solve the existing technical problems.

[0006] To achieve the above object, the present invention provides a method for evaluating and compensating the spatial accuracy of a portal vertical machining center, which specifically includes the following steps:

[0007] The error model is established by combining the factors affecting spatial accuracy;

[0008] Construct a spatial accuracy evaluation system;

[0009] Combined with the evaluation system, an evaluation method for machine tool spatial accuracy is given;

[0010] Analyze the error compensation based on the evaluation results and improve the spatial accuracy evaluation method.

[0011] Furthermore, the error model is established by linearly superposing the errors of the kinematic pair at the same degree of freedom and simplifying and merging the error elements of the three-axis precision CNC machine tool, as follows:

[0012] When the worktable X-axis moves a distance x, there are three movement (geometric) errors δ yX , δ xX , δ zX , three angle errors ε yX , ε xX , ε zX , 1 verticality error S yX , 3 thermal drift errors δ xX (t),δ yX (t),δ zX (t) and three force errors δ xX (f), δ yX (f), δ zX (f), so the error transformation matrix from the reference coordinate system to the X-axis is:

[0013]

[0014] There are three movement (geometric) errors δ when the worktable Y axis moves a distance y yY , δ xY , δ zY , three angle errors ε yY , ε xY , ε zY , 3 thermal drift errors δ xY (t),δ yY (t),δ zY (t) and three force errors δ xY (f), δ yY (f), δ zY (f), according to the coordinate transformation and small error hypothesis theory, the transformation matrix from the Y axis to the reference coordinate system is:

[0015]

[0016] When the worktable Z axis moves a distance z, there are three movement (geometric) errors δ yZ , δ xZ , δ zZ , three angle errors ε yz , ε xZ , ε zZ , 2 verticality errors S xz, S yz , 3 thermal drift errors δ xZ (t),δ yZ (t),δ zZ (t) and three force errors δ xZ (f), δ yZ (f), δ zZ (f), so the error transformation matrix from the reference coordinate system to the Z axis is:

[0017]

[0018] When the machine tool moves x, y, and z distances along the X, Y, and Z axes respectively, the transformation matrix is:

[0019]

[0020] Furthermore, the evaluation system includes fuzzy comprehensive evaluation, and the fuzzy comprehensive evaluation includes:

[0021] According to the evaluation objectives, an evaluation index system is established and an evaluation index set is extracted;

[0022] Determine indicator weights;

[0023] Construct indicator membership function and comprehensive evaluation mathematical model.

[0024] Furthermore, the process of establishing an evaluation index system includes gradually decomposing the evaluation objectives into sub-objectives at various levels according to the overall objective, criterion level, and indicator level, thereby obtaining an evaluation index system with a progressive structure. Sub-objectives at various levels are collectively referred to as evaluation indicators. Evaluation indicators describe different aspects of the evaluated object and characterize the characteristics of the evaluated object.

[0025] Furthermore, the evaluation system also includes establishing a fuzzy relationship between the factor set U and the evaluation set V in the primary fuzzy comprehensive evaluation process. In a finite domain, It can be represented by matrix R, r ij =μ R (u i ,v j ),0≤r ij ≤1, indicating that from factor u i Corresponding to a research object being rated as v j The degree of membership is determined, the weight vector W is determined, and Y=WR is obtained. The result is evaluated according to the Y value.

[0026] Furthermore, the evaluation system also includes establishing a multi-level evaluation model, including firstly conducting a primary comprehensive evaluation within each layer, and then conducting a higher-level comprehensive evaluation between the evaluation results of each layer. The steps of multi-level fuzzy comprehensive evaluation are as follows:

[0027] (1) Factor X = {x 1 ,x 2 ,...,x n} is divided into s subsets according to the attributes,

[0028]

[0029] (2) Pair Factor X i Make comprehensive decisions respectively, let y = {y 1 ,y 2 ,...,y m} is the evaluation set, X i The weight distribution of each factor in is

[0030]

[0031] in

[0032]

[0033] If R i is a single factor matrix, then the first-level judgment vector is

[0034]

[0035] (3) Each X i Considered as a factor,

[0036] X={X 1 ,X 2 ,...,X s}

[0037] The single factor decision matrix of X is

[0038]

[0039] Each X i As part of X, give the weight distribution according to importance:

[0040] A=(a 1 ,a 2 ,…,a s )

[0041] So there is

[0042] B=A·R=(b 1 ,b 2 ,…,b m )

[0043] Thus, the frame diagram of the secondary fuzzy comprehensive evaluation model is obtained;

[0044] The first-level factor set X iFurther subdividing it, we get a three-level fuzzy comprehensive evaluation model, a four-level fuzzy comprehensive evaluation model, and so on.

[0045] Furthermore, the evaluation system includes three levels. The first level is the overall goal, i.e., the overall accuracy factor set of CNC machine tools U = {U 1 ,U 2}; The second layer is the second level target factor set U i (i=1,2), where U 1 is the static error factor set, U 2 is the dynamic error factor set, U 1 ={J 11 ,J 12 ,J 13 ,J 14 ,J 15 ,J 16},U 2 = {U 21 ,U 22 ,U 23}, the third layer is the third level target factor set U 2i (i=1,2,3), where

[0046] U 21 ={D 11 ,D 12 ,D 13 ,D 14 ,D 15 ,D 16}

[0047] U 22 ={D 21 ,D 22 ,D 23 ,D 24 ,D 25 ,D 26}

[0048] U 23 ={D 31 ,D 32 ,D 33 ,D 34 ,D 35 ,D 36}.

[0049] Furthermore, the evaluation method includes obtaining a corresponding single-factor fuzzy comprehensive evaluation matrix according to the evaluation system.

[0050]

[0051] Substitute the obtained results into the evaluation matrix to obtain the secondary fuzzy evaluation matrix R 21 And the three-level fuzzy evaluation matrix R31 , R 32 , R 33 The fuzzy comprehensive evaluation result of the second-level index can be obtained from the weight vector of the third-level index of dynamic error, and then the overall comprehensive evaluation result can be obtained by combining the fuzzy comprehensive evaluation result of the second-level index of static error.

[0052] (1) By using the fuzzy comprehensive evaluation method, combined with the three-level index weight vector A 31 , the three-level indicators for dynamic error are:

[0053] B 31 =A 31 ·R 31

[0054] Similarly

[0055] B 32 =A 32 ·R 32

[0056] B 33 =A 33 ·R 33

[0057] The obtained B 31 , B 32 , B 33 Further combined to obtain the secondary fuzzy comprehensive evaluation result B 22 , calculated as follows

[0058]

[0059] (2) The secondary indicators of static error are:

[0060] B 21 =A 21 ·R 21

[0061] Combined with the weight vector A of the first-level index 1 , so the comprehensive performance evaluation result is

[0062]

[0063] Further, the error compensation includes:

[0064] Accurate measurement and analysis of errors to determine the specific error terms that need to be compensated;

[0065] Develop compensation plans based on measurement results, including selecting appropriate compensation methods and setting compensation parameters;

[0066] Implement compensation strategies in control systems;

[0067] The compensation effect is verified by measuring and evaluating the machine tool's performance again, and the compensation strategy is further adjusted based on the feedback.

[0068] The beneficial effects of the present invention are embodied in:

[0069] In the present invention, the spatial accuracy of a high-speed and high-precision portal vertical machining center is deeply analyzed, its influencing factors are explored, and an effective evaluation method is proposed. Combined with the establishment and analysis of a spatial error model, a set of systematic accuracy evaluation processes is provided, and corresponding error compensation is performed in combination with the evaluation results, providing a theoretical basis and practical guidance for improving the accuracy stability and machining quality of the machining center. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 This is a flow chart of the evaluation compensation method of the present invention;

[0071] Figure 2 This is a schematic diagram of the evaluation process of the present invention;

[0072] Figure 3 It is a schematic diagram of the spatial accuracy evaluation system of the present invention;

[0073] Figure 4 Schematic diagram of the error compensation process of the present invention. DETAILED DESCRIPTION

[0074] 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 described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. In the absence of conflict, the embodiments in this application and the features in the embodiments can be combined with each other. Based on the embodiments in 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.

[0075] The spatial accuracy of a machine tool usually refers to the positioning accuracy of the spatial coordinates (X, Y, Z) of a CNC machine tool within the volume of its processing space.

[0076] Specifically, the spatial accuracy of machine tools is the result of the combined effect of multiple error elements, including but not limited to:

[0077] Linear displacement error: refers to the error of the machine tool when it moves in a single axial direction.

[0078] Straightness error: describes the degree to which the machine tool deviates from the ideal straight line during movement.

[0079] Perpendicularity error: refers to the deviation between the ideal perpendicular relationship that should be maintained between two or more axes and the actual perpendicular relationship.

[0080] Roll Error: The deviation from the ideal position when the machine tool rotates around an axis.

[0081] Yaw error: The swing error of the machine tool about a certain axis during movement.

[0082] Pitch error: Similar to yaw error, it is the swing error around another axis.

[0083] The spatial accuracy of machine tools directly affects the dimensional accuracy and shape accuracy of machined parts. By classifying the above indicators, spatial accuracy is roughly composed of the following parts:

[0084] (1) Positioning accuracy: This refers to the deviation between the actual position of the machine tool at the specified coordinate position and the target position. The higher the positioning accuracy, the smaller the dimensional error of the product processed by the machine tool.

[0085] (2) Repeatability: This refers to the consistency of the actual position of the machine tool when it reaches the same target position multiple times. A high-precision machine tool can achieve a repeatability of 0.1 μm or higher.

[0086] (3) Twenty-one errors: These include the comprehensive reflection of geometric accuracy such as straightness, flatness, parallelism, equidistance, coincidence, perpendicularity and rotation. These errors together determine the overall spatial accuracy of the machine tool.

[0087] See also Figure 1-4 The present invention provides a method for evaluating and compensating the spatial accuracy of a portal vertical machining center, which specifically includes the following steps:

[0088] S1: Establish an error model based on the factors affecting spatial accuracy;

[0089] In one embodiment, establishing the error model includes simplifying and merging the error elements of the three-axis precision CNC machine tool according to the linear superposition of the errors of the kinematic pair in the same degree of freedom, as shown in the following table:

[0090] Table 1 Geometric error elements

[0091]

[0092]

[0093] Table 2 Thermal error elements

[0094]

[0095] Table 3 Force error elements

[0096]

[0097] Based on the above table, in actual situations, there are three movement (geometric) errors δ when the worktable X-axis moves a distance x yX , δ xX , δ zX , three angle errors ε yX , ε xX , ε zX , 1 verticality error S yX , 3 thermal drift errors δ xX (t),δ yX (t),δ zX (t) and three force errors δ xX (f), δ yX (f), δ zX (f), so the error transformation matrix from the reference coordinate system to the X-axis is:

[0098]

[0099] There are three movement (geometric) errors δ when the worktable Y axis moves a distance y yY , δ xY , δ zY , three angle errors ε yY , ε xY , ε zY , 3 thermal drift errors δ xY (t),δ yY (t),δ zY (t) and three force errors δ xY (f), δ yY (f), δ zY (f), according to the coordinate transformation and small error hypothesis theory, the transformation matrix from the Y axis to the reference coordinate system is:

[0100]

[0101] When the worktable Z axis moves a distance z, there are three movement (geometric) errors δ yZ , δ xZ , δ zZ , three angle errors ε yZ , ε xZ , ε zZ , 2 verticality errors S xz , S yz , 3 thermal drift errors δ xZ (t),δ yZ (t),δ zZ (t) and three force errors δ xZ (f), δ yZ (f), δ zZ (f), so the error transformation matrix from the reference coordinate system to the Z axis is:

[0102]

[0103] When the machine tool moves x, y, and z distances along the X, Y, and Z axes respectively, the transformation matrix is:

[0104]

[0105] S2: Construct a spatial accuracy evaluation system;

[0106] In one embodiment, the evaluation system includes a fuzzy comprehensive evaluation, and the fuzzy comprehensive evaluation includes:

[0107] S21: Establish an evaluation index system and extract an evaluation index set according to the evaluation objectives;

[0108] The process of establishing an evaluation index system includes gradually decomposing the evaluation objectives into sub-objectives at various levels according to the overall objective, criterion level, and indicator level, thereby obtaining an evaluation index system with a progressive structure. Sub-objectives at various levels are collectively referred to as evaluation indicators. Evaluation indicators describe different aspects of the evaluated object and characterize the characteristics of the evaluated object.

[0109] S22: Determine the indicator weights;

[0110] Establish the fuzzy relationship between the factor set U and the evaluation set V in the primary fuzzy comprehensive evaluation process In a finite domain, It can be represented by matrix R, r ij =μ R (u i ,v j ),0≤r ij ≤1, indicating that from factor u i Corresponding to a research object being rated as v j The degree of membership is determined, the weight vector W is determined, and Y=WR is obtained. The result is evaluated according to the Y value.

[0111] S23: Construct indicator membership function and comprehensive evaluation mathematical model.

[0112] It includes establishing a multi-level evaluation model, including first conducting a primary comprehensive evaluation within each layer, and then conducting a higher-level comprehensive evaluation between the evaluation results of each layer. The steps of multi-level fuzzy comprehensive evaluation are as follows:

[0113] (1) Factor X = {x 1 ,x 2 ,...,x n} is divided into s subsets according to the attributes,

[0114]

[0115] (2) Pair Factor Xi Make comprehensive decisions respectively, let y = {y 1 ,y 2 ,...,y m} is the evaluation set, X i The weight distribution of each factor in is

[0116]

[0117] in

[0118]

[0119] If R i is a single factor matrix, then the first-level judgment vector is

[0120]

[0121] (3) Each X i Considered as a factor,

[0122] X={X 1 ,X 2 ,...,X s}

[0123] The single factor decision matrix of X is

[0124]

[0125] Each X i As part of X, give the weight distribution according to importance:

[0126] A=(a 1 ,a 2 ,…,a s )

[0127] So there is

[0128] B=A·R=(b 1 ,b 2 ,…,b m )

[0129] Thus, the frame diagram of the secondary fuzzy comprehensive evaluation model is obtained;

[0130] The first-level factor set X i Further subdividing it, we get a three-level fuzzy comprehensive evaluation model, a four-level fuzzy comprehensive evaluation model, and so on.

[0131] In one embodiment, see Figure 3 The evaluation system consists of three levels. The first level is the overall goal, i.e., the overall accuracy factor set of CNC machine tools U = {U 1 ,U 2}; The second layer is the second level target factor set U i (i=1,2), where U 1 is the static error factor set, U 2 is the dynamic error factor set, U 1 ={J 11 ,J 12 ,J 13 ,J 14 ,J 15 ,J 16},U 2 = {U 21 ,U 22 ,U 23}, the third layer is the third level target factor set U 2i (i=1,2,3), where

[0132] U 21 ={D 11 ,D 12 ,D 13 ,D 14 ,D 15 ,D 16}

[0133] U 22 ={D 21 ,D 22 ,D 23 ,D 24 ,D 25 ,D 26}

[0134] U 23 ={D 31 ,D 32 ,D 33 ,D 34 ,D 35 ,D 36}.

[0135] S3: Provide an evaluation method for the spatial accuracy of machine tools in combination with the evaluation system;

[0136] According to the weight proportion of each weight indicator, each weight vector is further obtained, and the weight vector is obtained

[0137] A 1 , A 21 , A 22 , A 31 , A 32 , A 33 The weight ratios shown in the following table are given for reference.

[0138]

[0139]

[0140]

[0141]

[0142] From the above table, we can get the weight vectors:

[0143] A 1 =(0.4,0.6)

[0144] A 21 =(0.125,0.125,0.3,0.15,0.15,0.15)

[0145] A 22 =(0.33,0.33,0.33)

[0146] A 31 =A 32 =A 33 =(0.12,0.18,0.18,0.15,0.21,0.15)

[0147] The next step is to establish a single-factor fuzzy evaluation matrix. First, an evaluation set is given. The evaluation set is a set of comments given to evaluation indicators at various levels in the industry. For different evaluation indicators, the meanings of the comment levels are different. Import it into the computer and give the evaluation set V = {v i}, there are 6 evaluation levels in total, namely V = {v 1 、v 2 、v 3 、v 4 、v 5 、v 6}, where v 1 ={Excellent}, v 2 ={better}, v 3 ={good}, v 4 = {better}, v 5 ={General}, v 6 = {poor}, that is, the evaluation set is V = {excellent, relatively excellent, good, relatively good, average, poor}. The positioning accuracy of the machine tool can be divided into six intervals according to different standards. For the machine tool with a two-way travel range of 800-1250mm, refer to the following:

[0148] Excellent: the standard deviation of positioning accuracy is within ±2μm; relatively excellent: the standard deviation of positioning accuracy is between ±2μm and ±4μm; good: the standard deviation of positioning accuracy is between ±4μm and ±6μm; relatively good: the standard deviation of positioning accuracy is between ±6μm and ±8μm; average: the standard deviation of positioning accuracy is between ±8μm and ±10μm; poor: the standard deviation of positioning accuracy exceeds ±10μm.

[0149] By measuring each accuracy index multiple times, analyzing the measurement results, and classifying them by percentage according to the accuracy range, we can get a judgment statistical table. The dynamic error three-level index judgment statistical table is listed here for reference, as shown in the following table.

[0150]

[0151] Table Indicates the proportion of accuracy evaluation results for this indicator, and meets

[0152]

[0153] According to the evaluation system, the corresponding single-factor fuzzy comprehensive evaluation matrix is ​​obtained

[0154]

[0155] Substitute the obtained results into the evaluation matrix to obtain the secondary fuzzy evaluation matrix R 21 And the three-level fuzzy evaluation matrix R 31 , R 32 , R 33 The fuzzy comprehensive evaluation result of the second-level index can be obtained from the weight vector of the third-level index of dynamic error, and then the overall comprehensive evaluation result can be obtained by combining the fuzzy comprehensive evaluation result of the second-level index of static error.

[0156] (1) By using the fuzzy comprehensive evaluation method, combined with the three-level index weight vector A 31 , the three-level indicators for dynamic error are:

[0157] B 31 =A 31 ·R 31

[0158] Similarly

[0159] B 32 =A 32 ·R 32

[0160] B 33 =A 33 ·R 33

[0161] The obtained B31 , B 32 , B 33 Further combined to obtain the secondary fuzzy comprehensive evaluation result B 22 , calculated as follows

[0162]

[0163] (2) The secondary indicators of static error are:

[0164] B 21 =A 21 ·R 21

[0165] Combined with the weight vector A of the first-level index 1 , so the comprehensive performance evaluation result is

[0166]

[0167] S4: Analyze the error compensation based on the evaluation results and improve the spatial accuracy evaluation method.

[0168] In one embodiment, the error compensation includes:

[0169] Accurate measurement and analysis of errors to determine the specific error terms that need to be compensated;

[0170] Develop compensation plans based on measurement results, including selecting appropriate compensation methods and setting compensation parameters;

[0171] Implement compensation strategies in control systems;

[0172] The compensation effect is verified by measuring and evaluating the machine tool's performance again, and the compensation strategy is further adjusted based on the feedback.

[0173] Compensation effect verification is a key process to ensure the effectiveness of the compensation strategy. Verification methods usually include re-testing the accuracy and comparing it with the test results before compensation. In addition, processing tests can be performed using standard parts to intuitively evaluate the processing accuracy after compensation. The data collected during the verification process will be used to analyze the performance of the compensation strategy, including the degree of improvement in accuracy before and after compensation, stability, and any potential new problems. Through these methods, it can be ensured that the error compensation strategy achieves the desired effect and provides a basis for future optimization.

[0174] The compensation strategies include feedback interruption strategy and origin translation strategy;

[0175] Specifically, the working principle of the feedback interruption strategy is that the computer calculates the spatial error based on the error synthesis model, converts it into a pulse signal, and performs addition and subtraction operations with the encoder feedback signal. The calculation result is inserted into the servo system feedback loop in the form of a phase signal, and the machine tool control system uses this to drive the machine tool to implement the next movement.

[0176] Specifically, the origin translation strategy first calculates the position error value of the machine tool, converts it into a compensation signal and sends it to the CNC system through the I / O port. The compensation signal is then sent to the control signal of the machine tool servo loop through the CNC system's external coordinate system origin offset function to achieve the compensation purpose. This strategy does not require changing the CNC system's hardware and software and instructions, but only requires adding data interaction program code to the PLC.

[0177] The present invention deeply analyzes the spatial accuracy of a high-speed and high-precision portal vertical machining center, explores its influencing factors, and proposes an effective evaluation method. Combined with the establishment and analysis of a spatial error model, this paper provides a set of systematic accuracy evaluation procedures, and performs corresponding error compensation based on the evaluation results, providing a theoretical basis and practical guidance for improving the accuracy stability and machining quality of the machining center.

[0178] It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present invention. In specific applications, technicians in this field can make settings as needed, and the present invention does not limit this.

[0179] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of them according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.

[0180] In addition, for technical details not fully described in this embodiment, reference can be made to the evaluation method provided in any embodiment of the present invention, and will not be repeated here.

[0181] In addition, it should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0182] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0183] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0184] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for evaluating and compensating the spatial accuracy of a portal vertical machining center, characterized in that: The specific steps include: The error model is established by combining the factors affecting spatial accuracy; Construct a spatial accuracy evaluation system; Combined with the evaluation system, an evaluation method for machine tool spatial accuracy is given; Analyze the error compensation based on the evaluation results and improve the spatial accuracy evaluation method.

2. The method for evaluating and compensating the spatial accuracy of a portal vertical machining center according to claim 1, characterized in that: The error model is established by linearly superimposing the errors of the kinematic pair in the same degree of freedom and simplifying and merging the error elements of the three-axis precision CNC machine tool. The details are as follows: When the worktable X-axis moves a distance x, there are three movement (geometric) errors δ yX , δ xX , δ zX , three angle errors ε yX , ε xX , ε zX , 1 verticality error S yX , 3 thermal drift errors δ xX (t),δ yX (t),δ zX (t) and three force errors δ xX (f), δ yX (f), δ zX (f), so the error transformation matrix from the reference coordinate system to the X-axis is: There are three movement (geometric) errors δ when the worktable Y axis moves a distance y yY , δ xY , δ zY , three angle errors ε yY , ε xY , ε zY , 3 thermal drift errors δ xY (t),δ yY (t),δ zY (t) and three force errors δ xY (f), δ yY (f), δ zY (f), according to the coordinate transformation and small error hypothesis theory, the transformation matrix from the Y axis to the reference coordinate system is: When the worktable Z axis moves a distance z, there are three movement (geometric) errors δ yZ ,δ xZ ,δ zZ , three angle errors ε yZ , ε xZ , ε zZ , 2 verticality errors S xZ , S yz , 3 thermal drift errors δ xZ (t),δ yZ (t),δ zZ (t) and three force errors δ xZ (f), δ yZ (f), δ zZ (f), so the error transformation matrix from the reference coordinate system to the Z axis is: When the machine tool moves x, y, and z distances along the X, Y, and Z axes respectively, the transformation matrix is 3. The method for evaluating and compensating the spatial accuracy of a portal vertical machining center according to claim 1, characterized in that: The evaluation system includes fuzzy comprehensive evaluation, and the fuzzy comprehensive evaluation includes: According to the evaluation objectives, an evaluation index system is established and an evaluation index set is extracted; Determine indicator weights; Construct indicator membership function and comprehensive evaluation mathematical model.

4. The method for evaluating and compensating the spatial accuracy of a portal vertical machining center as claimed in claim 3, characterized in that: The process of establishing an evaluation index system includes gradually decomposing the evaluation objectives into sub-objectives at various levels according to the overall objective, criterion level, and indicator level, thereby obtaining an evaluation index system with a progressive structure. Sub-objectives at various levels are collectively referred to as evaluation indicators. Evaluation indicators describe different aspects of the evaluated object and characterize the characteristics of the evaluated object.

5. The method for evaluating and compensating the spatial accuracy of a portal vertical machining center as claimed in claim 3, characterized in that: The evaluation system also includes establishing a fuzzy relationship between the factor set U and the evaluation set V in the primary fuzzy comprehensive evaluation process. In a finite domain, It can be represented by matrix R, r ij =μ R (u i , v j ), 0≤r ij ≤1, indicating that from factor u i Corresponding to a research object being rated as v j The degree of membership is determined, the weight vector W is determined, and Y=WR is obtained. The result is evaluated according to the Y value.

6. The method for evaluating and compensating the spatial accuracy of a portal vertical machining center according to claim 5, characterized in that: The evaluation system also includes establishing a multi-level evaluation model, including first conducting a primary comprehensive evaluation within each layer, and then conducting a higher-level comprehensive evaluation between the evaluation results of each layer. The steps of multi-level fuzzy comprehensive evaluation are as follows: (1) Factor X = {x1, x2, ..., x n } is divided into s subsets according to the attributes, (2) Pair Factor X i Make comprehensive decisions respectively, let y = {y1, y2, ..., y m } is the evaluation set, X i The weight distribution of each factor in is in If R i is a single factor matrix, then the first-level judgment vector is (3) Each X i Considered as a factor, X={X1,X2,...,X s } The single factor decision matrix of X is Each X i As part of X, give the weight distribution according to importance: <h2 style=";text-align:left;direction:ltr">A=(a1, a2,…, a<h2 style=";text-align:left;direction:ltr"> s <h2 style=";text-align:left;direction:ltr"> ) So there is B=A·R=(b1,b2,…,b m ) Thus, the frame diagram of the secondary fuzzy comprehensive evaluation model is obtained; The first-level factor set X i Further subdividing it, we get a three-level fuzzy comprehensive evaluation model, a four-level fuzzy comprehensive evaluation model, and so on.

7. The method for evaluating and compensating the spatial accuracy of a portal vertical machining center according to claim 1, characterized in that: The evaluation system includes three levels. The first level is the overall goal, i.e., the overall accuracy factor set of CNC machine tools U = {U1, U2}; the second level is the second level target factor set U i (i=1, 2), where U1 is the static error factor set, U2 is the dynamic error factor set, U1={J 11 , J 12 , J 13 , J 14 , J 15 , J 16 },U2={U 21 , U 22 , U 23 }, the third layer is the third level target factor set U 2i (i=1, 2, 3), where U 21 ={D 11 ,D 12 ,D 13 ,D 14 ,D 15 ,D 16 } U 22 ={D 21 ,D 22 ,D 23 ,D 24 ,D 25 ,D 26 } U 23 ={D 31 ,D 32 ,D 33 ,D 34 ,D 35 ,D 36 }。 8. The method for evaluating and compensating the spatial accuracy of a portal vertical machining center as claimed in claim 1, characterized in that: The evaluation method includes obtaining a corresponding single factor fuzzy comprehensive evaluation matrix according to the evaluation system. Substitute the obtained results into the evaluation matrix to obtain the secondary fuzzy evaluation matrix R 21 And the three-level fuzzy evaluation matrix R 31 , R 32 , R 33 The fuzzy comprehensive evaluation result of the second-level index can be obtained from the weight vector of the third-level index of dynamic error, and then the overall comprehensive evaluation result can be obtained by combining the fuzzy comprehensive evaluation result of the second-level index of static error. (1) By using the fuzzy comprehensive evaluation method, combined with the three-level index weight vector A 31 , the three-level indicators for dynamic error are: B 31 =A 31 ·R 31 Similarly B 32 =A 32 ·R 32 B 33 =A 33 ·R 33 The obtained B 31 , B 32 , B 33 Further combined to obtain the secondary fuzzy comprehensive evaluation result B 22 , calculated as follows (2) The secondary indicators of static error are: B 21 =A 21 ·R 21 Combined with the weight vector A1 of the first-level index, the comprehensive performance evaluation result is:

9. The method for evaluating and compensating the spatial accuracy of a portal vertical machining center according to claim 1, characterized in that: The error compensation includes: Accurate measurement and analysis of errors to determine the specific error terms that need to be compensated; Develop compensation plans based on measurement results, including selecting appropriate compensation methods and setting compensation parameters; Implement compensation strategies in control systems; The compensation effect is verified by measuring and evaluating the machine tool's performance again, and the compensation strategy is further adjusted based on the feedback.

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