Method and device for realizing error processing of five-axis machine tool

Abstract

The invention discloses a method and a device for realizing error processing of a five-axis machine tool, which are used for determining an error source through measurement and transmission calculation, providing a basis for optimization design and providing a technical guarantee for improving static and dynamic precision of the machine tool. Furthermore, multi-source errors are pre-compensated, various static errors and dynamic errors are processed at the same time, and the terminal precision of the machine tool is improved; compensation is carried out before errors occur, and the delay problem of real-time compensation is avoided; and through filtering, unstable factors in the compensation process are reduced.

Description

Technical Field

[0001] This application relates to, but is not limited to, the field of numerical control technology, and particularly refers to a method and device for realizing error processing of a five-axis machine tool. Background Art

[0002] A five-axis machine tool can simultaneously control the position and attitude of a tool, and can efficiently machine complex curved surfaces, and is widely used in high-end manufacturing fields such as aerospace. However, static errors and dynamic errors will occur during the manufacturing, assembly, and operation processes of the machine tool, and these errors significantly affect its machining accuracy.

[0003] Current error detection and compensation technologies mainly focus on static errors, and the research and compensation for dynamic errors are relatively insufficient. Especially in the detection of dynamic errors, there is a lack of effective monitoring and compensation means for the deformation of actuators such as tools, spindles, and worktables, which limits the further improvement of the static and dynamic accuracy of five-axis machine tools. Summary of the Invention

[0004] This application provides a method and device for realizing error processing of a five-axis machine tool, which can clarify the error sources and provide technical guarantees for improving the static and dynamic accuracy of the machine tool.

[0005] An embodiment of this application provides a method for realizing error processing of a five-axis machine tool, including:

[0006] Establish a kinematic model of the machine tool according to the structure of the machine tool and obtain an error transfer model;

[0007] Detect the terminal static error in the working space of the machine tool;

[0008] Use the machine tool to move according to a preset trajectory, and detect the terminal dynamic error of the machine tool and the error of the feed axis;

[0009] According to the obtained terminal static error and terminal dynamic error, combined with the established kinematic model and error transfer model, analyze the multi-source errors of the machine tool.

[0010] In an exemplary example, it further includes:

[0011] Through the detection of errors and the analysis of the multi-source errors of the machine tool, combined with the kinematic model and the error transfer model of the machine tool, pre-compensate the multi-source static and dynamic errors of the machine tool.

[0012] In an exemplary example, use an R-test detection device to detect the terminal static error in the working space of the detection machine tool.

[0013] In an exemplary example, the motion trajectory includes: the trajectory of the machine tool swinging around the tool tip point in different directions successively.

[0014] In an exemplary instance, detecting the terminal dynamic error of the machine tool includes:

[0015] During the process of the machine tool moving along the trajectory, record the dynamic motion state and use an R - test detection device to measure the terminal dynamic error of the machine tool.

[0016] In an exemplary instance, the errors of the feed axis include the error at the end of the feed axis and the error of the feed axis motor;

[0017] During the process of the machine tool moving along the trajectory, use a grating scale of the feed axis to measure the error at the end of the feed axis; use an encoder of the feed axis to measure the error of the feed axis motor.

[0018] In an exemplary instance, analyzing the multi - source errors of the machine tool includes:

[0019] According to the terminal static error, by analyzing the static errors at each position, process the measured values at different positions in the working space to obtain the distribution law of the errors in space;

[0020] Measure the actual position of the motor through a motor encoder, compare it with the command position to obtain the motor following error; according to the motor following error and the terminal detection result, analyze the influence of the motor following error on the terminal position, and use the error transfer model to calculate the terminal error caused by the motor following error;

[0021] Measure the actual displacement of the feed axis through a grating scale, compare the theoretical value with the actual value to calculate the deformation error of the transmission mechanism, according to the deformation error of the transmission mechanism and the terminal detection result, analyze the contribution of the deformation error of the transmission mechanism to the terminal error, and use the error transfer model to calculate the terminal error caused by the deformation error of the transmission mechanism;

[0022] Based on the terminal dynamic error, eliminate the terminal error caused by the terminal static error, the terminal error caused by the motor following error, and the terminal error caused by the deformation error of the transmission mechanism, calculate the terminal error caused by the deformation of the actuator to analyze the deformation characteristics of the actuator during the acceleration and deceleration stages;

[0023] Comprehensively analyze the law after the superposition of the above - mentioned error sources.

[0024] In an exemplary instance, pre - compensating the multi - source static and dynamic errors of the machine tool includes:

[0025] According to the detected error results, classify and reveal the laws of each part of the error; use the classified error laws, combine with the sequential numerical control instructions of the machine tool to predict the machine tool error; compensate the value through filtering and superimpose it with the original numerical control instruction to finally achieve the pre - compensation of the error.

[0026] In an exemplary instance, the pre - compensation includes:

[0027] Obtaining the static error and dynamic error data of the machine tool through experimental measurement, and analyzing the error rules under different positions and working conditions;

[0028] Dividing the error into static error and dynamic error, analyzing the variation rules of each error with position, speed, and acceleration, and establishing a mathematical model;

[0029] Using the above rules and models, combined with the sequential numerical control instructions, predicting the error during the motion process;

[0030] Filtering the predicted dynamic error to generate a smooth compensation signal;

[0031] Superimposing the compensation signal on the original numerical control instruction to generate a new control instruction, driving the machine tool to move, and realizing the pre - compensation of the error.

[0032] In an exemplary instance, the error result includes the static error and the dynamic error;

[0033] The dynamic error includes one or any combination of the following: the dynamic following error of the motor, the elastic deformation error of the transmission mechanism, and the dynamic deformation error of the actuator.

[0034] The embodiment of the present application also provides a computer - readable storage medium storing computer - executable instructions for executing the method for realizing the error processing of a five - axis machine tool as described in any one of the above.

[0035] The embodiment of the present application further provides a computer device including a memory and a processor, wherein the memory stores the following instructions executable by the processor: steps for executing the method for realizing the error processing of a five - axis machine tool as described in any one of the above.

[0036] The embodiment of the present application also provides a device for realizing the error processing of a five - axis machine tool, including: a modeling module, a first detection module, a second detection module, and an analysis module; wherein,

[0037] The modeling module is used to establish the kinematic model of the machine tool according to the structure of the machine tool and obtain the error transfer model;

[0038] The first detection module is used to detect the terminal static error within the working space of the machine tool;

[0039] The second detection module is used to use the machine tool to move along a preset trajectory to detect the terminal dynamic error of the machine tool and the error of the feed axis;

[0040] An analysis module, configured to analyze the multi-source errors of the machine tool according to the obtained terminal static error and terminal dynamic error, in combination with the established kinematic model and error transfer model;

[0041] In an exemplary instance, it further includes a compensation module, configured to:

[0042] Through the detection of the errors and the analysis of the multi-source errors of the machine tool, in combination with the kinematic model and the error transfer model of the machine tool, pre-compensate the multi-source static and dynamic errors of the machine tool.

[0043] Through measurement and transfer calculation in the embodiments of the present application, the error sources are clarified, the characteristics of multi-source errors are analyzed, laying a foundation for error compensation, and thus providing technical guarantee for improving the static and dynamic accuracy of the machine tool.

[0044] Furthermore, according to the terminal error result, a compensation strategy can be designed to reduce the influence of errors on the machining accuracy. Through pre-compensation, various static errors and dynamic errors are processed simultaneously, improving the terminal accuracy of the machine tool; compensation is performed before the occurrence of errors, avoiding the delay problem of real-time compensation; through filtering, the unstable factors in the compensation process are reduced. The embodiments of the present application solve the problem that it is difficult to detect and compensate the deformation of the actuator. Through the proposed detection and compensation method, the detection and compensation of multi-source errors are realized, and the motion accuracy of the machine tool is improved.

[0045] Other features and advantages of the present application will be described below, and part of them will become obvious from the specification, or will be understood by implementing the present application. The objectives and other advantages of the present application can be realized and obtained through the structures specifically pointed out in the specification, claims and drawings. Description of the Drawings

[0046] The drawings are used to provide a further understanding of the technical solutions of the present application, and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solutions of the present application, and do not constitute a limitation to the technical solutions of the present application.

[0047] Figure 1 It is a schematic structural diagram of a five-axis hybrid machine tool in the embodiments of the present application;

[0048] Figure 2 It is a schematic flowchart of the method for realizing the error processing of a five-axis machine tool in the embodiments of the present application;

[0049] Figure 3(a) is a schematic diagram of the terminal static error distribution surface in the X direction of a five-axis hybrid machine tool in the embodiments of the present application;

[0050] Figure 3(b) is a schematic diagram of the terminal static error distribution surface in the Y direction of a five-axis hybrid machine tool in the embodiments of the present application;

[0051] Figure 3(c) is a schematic diagram of the terminal static error distribution surface in the Z direction of the five-axis hybrid machine tool in the embodiment of the present application;

[0052] Figure 4 It is a schematic diagram of the trajectory motion embodiment of the machine tool in the embodiment of the present application;

[0053] Figure 5(a) is a schematic diagram of the influence of the force deformation of the transmission mechanism in the multi-source error analysis in the embodiment of the present application;

[0054] Figure 5(b) is a schematic diagram of the influence of the motor following error in the multi-source error analysis in the embodiment of the present application;

[0055] Figure 5(c) is a schematic diagram of the influence of the following error of the feed axis slider in the multi-source error analysis in the embodiment of the present application;

[0056] Figure 5(d) is a schematic diagram of the influence of static errors such as manufacturing and assembly errors in the multi-source error analysis in the embodiment of the present application;

[0057] Figure 5(e) is a schematic diagram of the influence of the force deformation of the actuator in the multi-source error analysis in the embodiment of the present application;

[0058] Figure 5(f) is a schematic diagram of the detection result of the terminal dynamic error in the multi-source error analysis in the embodiment of the present application;

[0059] Figure 6 It is a flowchart of the error detection and analysis embodiment in the embodiment of the present application;

[0060] Figure 7 It is a flowchart of the multi-source static and dynamic error pre-compensation embodiment in the embodiment of the present application;

[0061] Figure 8 It is a schematic diagram of the error prediction result in the embodiment of the present application;

[0062] Figure 9 It is a schematic diagram of the error compensation result in the embodiment of the present application;

[0063] Figure 10 It is a schematic diagram of the composition structure of the device for realizing the error processing of the five-axis machine tool in the embodiment of the present application. Detailed implementation manners

[0064] To make the objectives, technical solutions and advantages of the present application clearer and more understandable, the embodiments of the present application will be described in detail below with reference to the accompanying drawings. It should be noted that, without conflict, the embodiments and features in the embodiments of the present application can be combined arbitrarily with each other.

[0065] To facilitate the understanding of this application, the following will provide a more comprehensive description of this application with reference to the relevant drawings. Embodiments of this application are shown in the drawings. However, this application can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the disclosure of this application more thorough and comprehensive.

[0066] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs. The terms used in the description of this application herein are only for the purpose of describing specific embodiments and are not intended to limit this application.

[0067] It can be understood that the terms "first" and "second" used in this application are only for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In the description of this application, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0068] It can be understood that for "connection" in the following embodiments, if there is an electrical signal or data transfer between the connected circuits, modules, units, etc., it should be understood as "electrical connection", "communication connection", etc.

[0069] As used herein, the singular forms "a", "an" and "the" may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms "comprise / include" or "have" etc. specify the presence of the stated features, wholes, steps, operations, components, parts or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, wholes, steps, operations, components, parts or combinations thereof. At the same time, the term "and / or" used in this specification includes any and all combinations of the related listed items.

[0070] Taking a five-axis hybrid machine tool as an example, as Figure 1 shown, the five-axis hybrid machine tool in this example includes: a workbench that can carry a workpiece and move under the drive of the X W axis, a column that moves under the drive of the Y C axis, and a parallel mechanism. The cutting tool is installed on the moving platform of the parallel mechanism and moves under the common drive of the Z 1 axis, Z 2 axis, and Z 3 axis. Five-axis linkage can achieve five-degree-of-freedom movement of the cutting tool relative to the workpiece.

[0071] Figure 2This is a schematic flowchart of the method for implementing error processing of a five-axis machine tool in an embodiment of the present application. As Figure 2 shown, it may include:

[0072] Step 200: Establish a kinematic model of the machine tool according to the structure of the machine tool and obtain an error transfer model J.

[0073] In an exemplary example, step 200 may include:

[0074] Determine the geometric structure and motion mode of the machine tool, such as the arrangement combination of the rotating axis and the linear axis of the machine tool; based on the motion chain, establish a kinematic model of the machine tool, including a pose matrix and motion constraint conditions; use differential operations to analyze the error transfer path of the machine tool and construct an error transfer model J, that is, a transfer matrix of the influence of each error source on the terminal error.

[0075] The kinematic model and the error transfer model run through the entire process and are the core tools for analyzing errors, verifying experimental results, and implementing compensation. In each step, the model will combine actual measurement data to decompose, superimpose, or predict the error sources. The final compensation effect depends on the accuracy of the model, and the error transfer model directly determines the calculation accuracy of the compensation value.

[0076] The machine tool kinematic model, which is used to describe the motion relationship between the components of the machine tool, is the basis for calculating the terminal position and posture of the machine tool. The machine tool kinematic model describes the motion chain of the machine tool, that is, the motion relationship from the motor input to the tool tip or the workbench output, and provides a reference for error analysis, that is, errors are often superimposed and transferred based on the kinematic model.

[0077] The error transfer model J describes how each error source (such as motor error, transmission error) is transferred to the terminal position or posture through differential or perturbation analysis. The contribution of each error source to the terminal position error can be expressed by the transfer matrix J. The error transfer model J is an important basis for calculating the compensation value and can provide input for error compensation design.

[0078] It should be noted that this step can refer to relevant technologies or standards, and the specific implementation does not limit the protection scope of the present application. Through step 200, a kinematic model of the five-axis hybrid machine tool as Figure 1 shown is established, and an error transfer model J is obtained through differential operations. In other instances (scenarios), the kinematic model that conforms to the structure of the machine tool will be re-derived according to different machine tool structures, and the error transfer model J will be obtained through differential operations.

[0079] Step 201: Detect the terminal static error in the working space of the machine tool.

[0080] In an exemplary instance, an R-test detection device can be employed to detect the terminal static error E within the working space of the machine tool. s =(E s-X E s-Y E s-Z ) T , and through step 201, the error distribution within the working space of the machine tool in a static state is measured and quantified, providing a basic reference for subsequent dynamic error detection and analysis.

[0081] In one embodiment, an R-test detection device is used to measure different points in the working space of the machine tool. In this embodiment, the sensor of the R-test detection device is installed on the machine tool table, and the ball nose probe is installed on the machine tool spindle to ensure that it can directly reflect the static error of the machine tool end. In other instances (scenarios), the positions of the ball nose probe and the sensor can also be swapped, as long as the terminal error can be accurately measured. In this way, by controlling the machine tool to move to each detection point, the position deviations in the X, Y, and Z directions are recorded; at the same time, the changes in the rotation angles A and B (rotation axis angles) are recorded to construct a three-dimensional error distribution; and the collected error data is subjected to surface fitting.

[0082] Taking this five-axis hybrid machine tool as an example, as shown in Figures 3(a), 3(b), and 3(c), the terminal static error distribution surfaces in the X, Y, and Z directions are obtained respectively. The horizontal axes in Figures 3(a), 3(b), and 3(c) represent the rotation angle, and the vertical axes represent the errors in the corresponding directions. As shown in the X-direction error in Figure 3(a), it shows the variation of the error at the machine tool end in the X direction with the rotation angles A and B, and the error range is between ±0.03 mm, indicating that the error of the machine tool in the X direction is relatively small. As shown in the Y-direction error in Figure 3(b), it reflects the distribution characteristics of the Y-direction error. The error range is similar to that in the X direction, but it changes more significantly with the angle. The error peaks at certain angles indicate that there may be an impact from the assembly or structure of a specific mechanism. As shown in the Z-direction error in Figure 3(c), the Z-direction error distribution is relatively smooth, but there are still local error variations within a specific angle range, indicating that the geometric accuracy of the machine tool in the Z direction may be affected by mechanical constraints or gravity.

[0083] Through the R-test detection device, the distribution law of the static error within the working space can be accurately obtained. The distribution characteristics of the static error provide basic data for subsequent processing.

[0084] Step 202: Use the machine tool to move along a pre-set trajectory to detect the terminal dynamic error of the machine tool and the error of the feed axis.

[0085] In an exemplary embodiment, the pre-set motion trajectory of the machine tool may include a swing trajectory of the machine tool successively around the tool tip point in different directions. In an embodiment, the machine tool may be instructed to swing successively around the tool tip point in different directions (such as around the X-axis and the Y-axis) to record the dynamic motion state. Figure 4 Schematic diagram of the trajectory motion of the machine tool in the embodiment of the present application, as shown in FIG. Figure 4 As shown, it first swings along the A direction, that is, rotates around the X axis, and then swings along the B direction, that is, rotates around the Y axis, to form the motion trajectory of the machine tool as shown in the figure.

[0086] In an exemplary embodiment, the machine tool follows a preset trajectory, so that the terminal dynamic error E of the machine tool can be measured using the R-test detection device. d =(E d-X E d-Y E d-Z ) T In one embodiment, the feed axis grating ruler can be used to measure the feed axis end error e r =(e r-1 e r-2 e r-3 e r-4 e r-5 ) T In one embodiment, the feed axis encoder can be used to measure the feed axis motor following error e e =(e e-1 e e-2 e e-3 e e-4 e e-5 ) T .

[0087] Step 203: According to the obtained terminal static error and terminal dynamic error, combined with the established kinematic model and error transfer model J, the multi-source error of the machine tool is analyzed.

[0088] In an exemplary embodiment, decomposing the multi-source errors according to the detected static errors and dynamic errors may include:

[0089] According to the terminal static error E s ,By analyzing (such as difference, interpolation, fitting, etc.) the static error of each position, the measured values ​​at different positions in the workspace are processed to obtain the distribution law of the error in space.,As shown in Figure 5(d). Figure 5(a)-Figure 5(f) 51f represent curves in the X direction, curves 52a, 52b, 52f represent curves in the Y direction, and curves 53a, 53b, 53f represent curves in the Z direction.

[0090] Motor following error e m =ee : Measure the actual position of the motor through the motor encoder, compare it with the command position, and obtain the motor following error. Analyze the influence of the motor following error on the terminal position according to the motor following error and the terminal detection result. Use the error transfer model J to calculate the terminal error E caused by the motor following error m = Je e , as shown in Fig. 5(b). The analysis of the motor following error can reveal the dynamic performance of the servo system and provide a basis for optimizing the servo control

[0091] Deformation error e of the transmission mechanism tm = e r - e e ; Measure the actual displacement of the feed axis through the grating scale, compare the theoretical value with the actual value, and calculate the deformation error of the transmission mechanism. Analyze the contribution of the deformation error of the transmission mechanism to the terminal error according to the deformation error of the transmission mechanism and the terminal detection result. Use the error transfer model J to calculate the terminal error E caused by the deformation error of the transmission mechanism tm = J(e r - e e ), as shown in Fig. 5(a).

[0092] Analyze the deformation characteristics of the actuator through the acceleration and deceleration stages of the terminal dynamic error. The terminal error E caused by the deformation of the actuator em = E d - E m - E tm - E s , as shown in Fig. 5(e). That is to say, based on the terminal dynamic error, after removing the terminal static error, the terminal error caused by the motor following error, and the terminal error caused by the deformation error of the transmission mechanism, calculate the terminal error caused by the deformation of the actuator, so as to analyze the deformation characteristics of the actuator during the acceleration and deceleration stages

[0093] Comprehensively analyze the law after the superposition of the above error sources, such as the terminal dynamic error decomposition results E m , E tm and E em .

[0094] The schematic diagram of the error detection process is as Figure 6 shown Figure 6 describes the flow block diagram of the error detection and analysis of the five-axis machine tool, which is mainly divided into four parts: motion information input, error source analysis, error detection, error transfer and error calculation

[0095] The motion information input section provides key parameters during the motion of the machine tool, including: position, i.e., the real-time position of each axis, which is an important input for static error analysis; speed, i.e., the speed information of each axis during the motion, used for dynamic error analysis; acceleration, i.e., the acceleration information of each axis, used to analyze the dynamic error caused by inertial force, such as the deformation error of the actuator and the transmission mechanism. These input information directly affect the calculation and decomposition of subsequent error sources.

[0096] The error source analysis details various error sources and classifies the errors according to different mechanisms: (1) Manufacturing and assembly errors, which are geometric errors generated during the manufacturing and assembly of the machine tool, such as the straightness error of the guide rail and the parallelism error of the lead screw. Manufacturing and assembly errors are related to position and are mainly manifested as static errors. (2) Force-induced deformation errors include: actuator deformation errors, such as the tool or the spindle, and in this embodiment, the moving parts of the parallel mechanism also belong to the actuator. The actuator undergoes elastic deformation caused by inertial force or cutting force during the motion. Transmission mechanism deformation errors, where the transmission components (such as lead screws and guide rails) undergo elastic deformation due to inertial force or load during dynamic motion. Actuator deformation errors and transmission mechanism deformation errors are related to acceleration and speed and are part of the dynamic errors. (3) Motor following error, which is the deviation between the command value and the actual response value during the dynamic control of the motor, usually caused by servo lag or inaccurate control. Motor following error is related to speed and acceleration and is another important source of dynamic error.

[0097] The error detection section obtains the numerical values of various errors through measurement devices and theoretical calculations, including: (1) Feed axis error detection: The grating scale detection is used to measure the deviation between the actual displacement of the feed axis and the command value; the encoder detection is used to measure the deviation between the target position and the actual position of the motor, which is used for calculating the motor following error. (2) Terminal static and dynamic error detection: Through the machine tool terminal measurement device, the static and dynamic errors of the terminal (tool tip or workbench position) are measured successively. (3) Error calculation and analysis, the transmission mechanism deformation error, the actuator deformation error, and the motor following error are transmitted to the terminal through the error transfer model J, and the multi-source errors are analyzed uniformly.

[0098] The embodiment of this application clarifies the error sources through measurement and transfer calculations, analyzes the characteristics of multi-source errors, lays a foundation for error compensation, and thus provides a technical guarantee for improving the static and dynamic accuracy of the machine tool. Further, according to the terminal error results, a compensation strategy can be designed to reduce the impact of errors on machining accuracy.

[0099] In an exemplary example, on the basis of the above decomposition of multi-source errors, step 204 may further be included:

[0100] Through the detection of errors and the analysis of multi-source errors of the machine tool, combined with the established kinematic model and error transfer model J of the machine tool, pre-compensation for multi-source static and dynamic errors of the machine tool is carried out.

[0101] In one embodiment, pre-compensation for multi-source static and dynamic errors of the machine tool may include:

[0102] According to the detected error results, classify and reveal the laws of each part of the error; utilize the classified error laws, combined with the sequential numerical control instructions of the machine tool, to predict the machine tool errors; compensate the values through filtering processing and superimpose them on the original numerical control instructions to finally achieve pre-compensation for the errors.

[0103] In one embodiment, the error results include static errors and dynamic errors. In one embodiment, the dynamic errors include one or any combination of the following: the dynamic following error of the motor The elastic deformation error of the transmission mechanism The dynamic deformation error of the actuator (such as the tool tip, spindle)

[0104] In one embodiment, the main process of the pre-compensation method may include:

[0105] The static error of the machine tool obtained through experimental measurement and dynamic error data, and analyze the error laws under different positions and working conditions.

[0106] Classify the errors into static errors and dynamic errors ( and / or and / or ), analyze the variation laws of each error with position, speed, and acceleration, and establish a mathematical model.

[0107] Utilize the above laws and models, combined with the sequential numerical control instructions to predict the errors during the movement process.

[0108] Perform filtering processing on the predicted dynamic errors to generate a smooth compensation signal.

[0109] Superimpose the compensation signal on the original numerical control instructions to generate a new control instruction to drive the movement of the machine tool and achieve pre-compensation for the errors.

[0110] In one embodiment, the predicted dynamic error may be as shown in formula (1):

[0111]

[0112] In formula (1), is the predicted value of the dynamic error, i.e., the predicted terminal dynamic error, which is obtained by superimposing multiple static and dynamic error sources and smoothed by the filtering function L(t). represents the static error, which depends on the position variable q of the machine tool. The static error mainly comes from assembly errors, geometric errors, etc., and is usually a fixed deviation related to the working space position. is the dynamic following error of the motor, which depends on the position q, speed acceleration The error is related to the control characteristics of the motor, such as servo lag or following deviation. The elastic deformation error of the transmission mechanism is mainly affected by the position q, speed acceleration of the machine tool. is the dynamic deformation error of the actuator (such as the tool tip, spindle), which usually occurs during the acceleration and deceleration phases and is related to the position q, speed acceleration of the machine tool. The filtering function L(t) is a filtering function for smoothing the predicted error, which is a filtering function for smoothing the predicted error.

[0113] In one embodiment, the filtering function L(t) can be implemented by selecting a low-pass filter such as a second-order Butterworth filter, and other filters can be selected in other instances. The prediction results are as Figure 8 shown, which coincide with Fig. 5(d), and the compensation effect is as Figure 9 shown. Figure 8 In, curve 81 represents the curve in the X direction, curve 82 represents the curve in the Y direction, and curve 83 represents the curve in the Z direction. Figure 9 In, curve 91 represents the curve in the X direction, curve 92 represents the curve in the Y direction, and curve 93 represents the curve in the Z direction.

[0114] A schematic diagram of the error compensation process is as Figure 7 shown. Figure 7 Taking a five-axis machine tool as an example, the multi-source static and dynamic error pre-compensation process is described. Through the prediction, transmission, filtering, and compensation signal generation of static and dynamic errors, the comprehensive compensation of the multi-axis motion of the machine tool is realized. The main processes include:

[0115] Static error prediction is used to predict the static error of the machine tool at different positions according to the geometric characteristics and assembly conditions of the machine tool. The obtained static error prediction value is used for subsequent error compensation signal generation. The static error is mainly related to the geometric error of the machine tool (such as assembly error, straightness error of the guide rail, etc.).

[0116] Feed axis following error prediction is used to predict the error caused by the control characteristics of the feed axis (such as motor servo lag) and the transmission system (such as the elastic deformation of the lead screw and guide rail), and obtain the dynamic error prediction value (feed axis error). It includes: motor following error prediction to analyze the dynamic response characteristics of the motor and predict the error caused by servo lag in motor control; transmission mechanism deformation prediction to consider the elastic deformation of transmission components under high-speed or high-acceleration motion and predict the transmission system error.

[0117] Actuator deformation prediction is used to predict the dynamic deformation error generated by the tool or spindle due to inertial force or cutting force during motion, and obtain the dynamic error prediction value (actuator error).

[0118] Error transfer is used to use the error transfer model to transfer the predicted values of each error source (static error, feed axis error, actuator error) to the terminal (such as the tool tip or workbench position) to calculate the comprehensive error of the terminal.

[0119] Filtering is used to smooth the comprehensive error signal, remove high-frequency noise, and ensure the stability of the compensation signal. For example, it can be implemented using a second-order Butterworth filter.

[0120] Inverse kinematics is used to transfer the filtered error compensation signal to each axis servo system, adjust the motion trajectory of the machine tool, and obtain the drive signal compensated for each axis.

[0121] Each axis servo system is used to adjust the motion of each axis according to the compensation signal obtained by inverse kinematics to achieve the compensation of the terminal error.

[0122] Through Figure 7 The error compensation process shown above realizes the high-precision motion of the machine tool terminal by comprehensively predicting and compensating static error and dynamic error, and is applicable to high-precision machining scenarios.

[0123] Through the pre-compensation provided by the embodiments of the present application, various static errors and dynamic errors are processed simultaneously, improving the accuracy of the machine tool terminal; compensation is performed before the error occurs, avoiding the delay problem of real-time compensation; through filtering, unstable factors in the compensation process are reduced. The embodiments of the present application solve the problem that it is difficult to detect and compensate the deformation of the actuator. Through the proposed detection and compensation method, the detection and compensation of multi-source errors are realized, and the motion accuracy of the machine tool is improved.

[0124] In an exemplary example, through analysis, it is obtained that the terminal error E caused by the motor following error m and the terminal error E caused by the deformation of the transmission mechanism tmWhen superimposed, the pattern becomes more obvious. As shown in Fig. 5(c), the influence of the feed axis slider following error on the terminal is mainly in the Y direction. When facing other application examples, similar arrangements based on the method for detecting the errors of a five-axis machine tool provided in the embodiments of the present application can be attempted. The feed axis following error, static error, and actuator deformation in Figs. 5(c), 5(d), and 5(e) are superimposed to obtain the final terminal dynamic error, as shown in Fig. 5(f). The terminal dynamic error in Fig. 5(f) is decomposed into the feed axis following error, static error, and actuator deformation in Figs. 5(c), 5(d), and 5(e), realizing the detection of static and dynamic errors, especially the detection of actuator deformation.

[0125] Based on the error compensation method provided in the embodiments of the present application and combined with the detection results, the terminal error E caused by the motor following error can be obtained m and the terminal error E caused by the deformation of the transmission mechanism tm When superimposed, the pattern becomes more obvious. According to the modeling and analysis of the feed system, it can be known that its error is related to the acceleration. The proportionality coefficient λ is related to the characteristics of the feed system. By calibrating its coefficient through experiments, the prediction of the error of the feed system can be completed. The terminal static error can be obtained by differentiating the measurement results. According to the experimental results, it can be seen that the actuator deformation mainly occurs in the acceleration and deceleration stages of the machine tool, that is, it satisfies formula (2). By performing acceleration and deceleration experiments at multiple positions in the working space, the distribution of the six coefficients in formula (2) in the working space can be determined.

[0126]

[0127] In formula (2), the motor error E em represents the influence of the actuator deformation error on the terminal. It is a 3×1 vector, including the errors of the machine tool terminal in the X, Y, and Z directions: The coefficient matrix Each coefficient C ij represents the influence weight of the angular accelerations of the rotary axes A and B on the terminal errors in the X, Y, and Z directions. Inputting an appropriate amount in, represents the angular acceleration of axis A, represents the angular acceleration of axis B. In the acceleration and deceleration stages, the angular acceleration is an important parameter affecting the actuator deformation error. Through the matrix multiplication shown in formula (2), the motor errors of the terminal in the X, Y, and Z directions under specific angular accelerations can be calculated.

[0128] According to formula (2), the actuator deformation error is directly related to the angular acceleration The C in the coefficient matrix ijreflects the dynamic response characteristics of the actuator. Each C in the coefficient matrix ij needs to be calibrated through experiments: measure the terminal error E under a known angular acceleration em , and fit to obtain the value of C ij . The calibrated coefficient can predict the deformation error of the actuator under different angular accelerations. The deformation of the actuator mainly occurs in the acceleration and deceleration stages because the inertial force changes most violently in these stages. At different positions in the workspace, the value of C ij in the coefficient matrix may change. By performing acceleration and deceleration experiments at multiple positions in the workspace, the distribution of C ij in the workspace can be determined.

[0129] This application also provides a computer-readable storage medium storing computer-executable instructions for executing the method for realizing five-axis machine tool error processing described in any one of the above.

[0130] This application further provides a computer device including a memory and a processor, where the memory stores the following instructions executable by the processor: steps for executing the method for realizing five-axis machine tool error processing described in any one of the above.

[0131] Figure 10 is a schematic structural diagram of the device for realizing five-axis machine tool error processing in the embodiments of this application. As Figure 10 shown, it may include: a modeling module, a first detection module, a second detection module, and an analysis module; where

[0132] The modeling module is configured to establish a kinematic model of the machine tool according to the structure of the machine tool and obtain an error transfer model J;

[0133] The first detection module is configured to detect the terminal static error in the working space of the machine tool;

[0134] The second detection module is configured to use the trajectory of the machine tool to detect the terminal dynamic error of the machine tool and the error of the feed axis;

[0135] The analysis module is configured to analyze the multi-source errors of the machine tool according to the obtained terminal static error and terminal dynamic error, in combination with the established kinematic model and error transfer model J;

[0136] The embodiments of this application clarify the error sources through measurement and transfer calculation, providing a basis for optimization design. Further, according to the terminal error results, a compensation strategy can be designed to reduce the influence of errors on machining accuracy.

[0137] In an exemplary example, it may further include a compensation module for:

[0138] Through the detection of errors and the analysis of multi-source errors of the machine tool, combined with the established kinematic model and error transfer model J of the machine tool, pre-compensation is performed on the multi-source static and dynamic errors of the machine tool.

[0139] Through the pre-compensation provided by the embodiments of the present application, various static errors and dynamic errors are processed simultaneously, improving the terminal precision of the machine tool; compensation is performed before the occurrence of errors, avoiding the delay problem of real-time compensation; through filtering, unstable factors in the compensation process are reduced. The embodiments of the present application solve the problem that it is difficult to detect and compensate for the deformation of the actuator. Through the proposed detection and compensation method, the detection and compensation of multi-source errors are realized, and the motion precision of the machine tool is improved.

[0140] Although the disclosed embodiments of the present application are as above, the content described is only an embodiment adopted for the convenience of understanding the present application and is not used to limit the present application. Any person skilled in the art within the scope of the present application can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed by the present application. However, the scope of patent protection of the present application shall still be subject to the scope defined by the appended claims.

Claims

1. A method for implementing error processing of a five-axis machine tool, characterized in that: include: Establish the kinematic model of the machine tool according to its structure and obtain the error transmission model; Detect terminal static errors within the machine tool workspace; Using the machine tool to move along a preset trajectory, the terminal dynamic error of the machine tool and the error of the feed axis are detected; According to the obtained terminal static error and terminal dynamic error, combined with the established kinematic model and error transfer model, the multi-source error of the machine tool is analyzed.

2. The method according to claim 1, further comprising: By means of the detection of errors and the analysis of multi-source errors of a machine tool, combined with the kinematic model of the machine tool and the error transfer model, pre-compensation is performed on multi-source static and dynamic errors of the machine tool.

3. The method according to claim 1 or 2, wherein: R-test detection equipment is used to detect the terminal static error in the working space of the detection machine tool.

4. The method according to claim 1 or 2, wherein: The motion trajectory includes: a trajectory in which the machine tool successively swings around the tool tip point in different directions.

5. The method according to claim 1 or 2, wherein: The terminal dynamic error of the detection machine tool comprises: The machine tool records the dynamic motion state while moving along the trajectory, and uses R-test detection equipment to measure the terminal dynamic error of the machine tool.

6. The method according to claim 1 or 2, wherein: The error of the feed shaft includes the error of the feed shaft end and the error of the feed shaft motor; When the machine tool moves along the trajectory, a feed shaft grating ruler is used to measure the end error of the feed shaft; and a feed shaft encoder is used to measure the motor error of the feed shaft.

7. The method according to claim 1 or 2, wherein: The analysis of multi-source errors of the machine tool includes: According to the terminal static error, by analyzing the static error of each position, the measurement values ​​at different positions in the workspace are processed to obtain the distribution law of the error in space; The actual position of the motor is measured by the motor encoder, and compared with the command position to obtain the motor following error; according to the motor following error and the terminal detection result, the influence of the motor following error on the terminal position is analyzed, and the terminal error caused by the motor following error is calculated using the error transfer model; The actual displacement of the feed shaft is measured by a grating ruler, and the theoretical value is compared with the actual value to calculate the deformation error of the transmission mechanism. According to the deformation error of the transmission mechanism and the terminal detection result, the contribution of the deformation error of the transmission mechanism to the terminal error is analyzed, and the terminal error caused by the deformation error of the transmission mechanism is calculated using the error transfer model; Based on the terminal dynamic error, the terminal static error, the terminal error caused by the motor following error, and the terminal error caused by the transmission mechanism deformation error are eliminated, and the terminal error caused by the actuator deformation is calculated to analyze the deformation characteristics of the actuator in the acceleration and deceleration stages; Comprehensively analyze the rules after the superposition of the above error sources.

8. The method according to claim 2, wherein: The pre-compensation of multi-source static and dynamic errors of the machine tool includes: According to the detected error results, the rules of the errors of each part are revealed by classification; the machine tool error is predicted by using the classified error rules in combination with the timing numerical control instructions of the machine tool; the compensation value is processed by filtering and superimposed with the original numerical control instructions, finally realizing the pre-compensation of the error.

9. The method according to claim 8, wherein: The pre-compensation includes: The static error and dynamic error data of the machine tool obtained through experimental measurement are used to analyze the error laws under different positions and working conditions; The error is divided into static error and dynamic error, and the variation law of each error with position, speed and acceleration is analyzed to establish a mathematical model; Using the above rules and models, combined with sequential CNC instructions, the error of the motion process is predicted; Filter the predicted dynamic error to generate a smooth compensation signal; The compensation signal is superimposed on the original CNC instruction to generate a new control instruction to drive the machine tool to move and realize pre-compensation of the error.

10. The method according to claim 8 or 9, wherein: The error result includes the static error and the dynamic error; The dynamic error includes one of the following or any combination thereof: a dynamic following error of the motor, an elastic deformation error of the transmission mechanism, and a dynamic deformation error of the actuator.

11. A computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute the method for implementing error processing of a five-axis machine tool according to any one of claims 1 to 10.

12. A computer device comprising a memory and a processor, wherein: The memory stores the following instructions executable by the processor: used to execute the steps of the method for implementing error processing of a five-axis machine tool as described in any one of claims 1-10.

13. A device for implementing error processing of a five-axis machine tool, characterized in that: include: Establishing module, first detection module, second detection module, and analysis module; wherein, A modeling module, used to establish a kinematic model of the machine tool and obtain an error transmission model according to the structure of the machine tool; The first detection module is used to detect the terminal static error in the machine tool working space; The second detection module is used to detect the terminal dynamic error of the machine tool and the error of the feed axis by using the machine tool to move according to a preset trajectory; The analysis module is used to analyze the multi-source errors of the machine tool according to the obtained terminal static error and terminal dynamic error in combination with the established kinematic model and error transfer model.

14. The apparatus according to claim 13, further comprising a compensation module, configured to: By means of the detection of errors and the analysis of multi-source errors of a machine tool, combined with the kinematic model of the machine tool and the error transfer model, pre-compensation is performed on multi-source static and dynamic errors of the machine tool.

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