Method and system for programming a machine tool functional component manufacturing process

Abstract

This invention relates to the field of machine tool control technology, specifically to a method and system for controlling the manufacturing process of machine tool functional components. The method includes acquiring ball screw data and direction of motion of the ball screw at its current position when the machine tool executes a motion command; determining the clearance deviation value corresponding to the ball screw data at the current position based on the ball screw data and direction of motion and a preset clearance error data structure; determining servo motor drive data based on the clearance deviation value and the ball screw data at the current position; and controlling the machine tool using the servo motor drive data to complete the control of the machine tool functional component manufacturing process. The purpose of this invention is to solve the problem of low precision in the existing technology for precision machining control of machine tool functional components when machining complex curved surface parts.

Description

Technical Field

[0001] This invention relates to the field of machine tool control technology, and specifically to a method and system for controlling the manufacturing process of machine tool functional components. Background Technology

[0002] The precision control of machine tool functional components relies on specialized computer-aided manufacturing (CAM) software to generate CNC machining programs. When the machine tool's CNC controller receives and executes a program with minute tangential discontinuities, the controller makes instantaneous speed or acceleration adjustments near high-frequency, minute, and non-ideal path transition points. This causes the drive servo motor to produce a minute nonlinear response within a very short time, resulting in minute non-periodic fluctuations in its current and torque output.

[0003] Existing backlash compensation methods involve setting a fixed value in the machine tool parameters to compensate for backlash in the mechanical transmission chain during motion reversal. However, when the backlash itself is a non-linear error that varies with position, the tool movement will experience undercompensation due to insufficient compensation, leading to trajectory deviation. When using existing control methods to finish-machine thin-walled complex curved surface functional components with high precision requirements, inaccurate and position-variable backlash compensation can cause the machine tool to experience slight overcutting or undercutting due to instantaneous trajectory deviations when frequently reversing or crossing areas of uneven wear, resulting in decreased machining control accuracy. This leads to unpredictable deformation of the component during subsequent surface treatment or assembly, and even performance instability during long-term operation, ultimately severely affecting the overall reliability and service life of the functional component. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for controlling the manufacturing process of machine tool functional components, which solves the problem of low precision in the existing technology for precision machining control of machine tool functional components when machining complex curved surface parts.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a method for controlling the manufacturing process of machine tool functional components, comprising the following steps:

[0006] Acquire the current position and direction of the ball screw when the machine tool executes motion commands;

[0007] Based on the lead screw data and movement direction at the current position and the preset clearance error data structure, the clearance deviation value corresponding to the lead screw data at the current position is confirmed.

[0008] Based on the gap deviation value and the lead screw data at the current position, confirm the servo motor drive data;

[0009] The machine tool is controlled by servo motor drive data to control the manufacturing process of the machine tool's functional components.

[0010] Furthermore, the step of confirming the clearance deviation value corresponding to the lead screw data at the current position based on the lead screw data at the current position, the direction of movement, and the preset clearance error data structure includes:

[0011] Using a preset gap error data structure, the lead screw data at the current position is initially matched to obtain the initial value of the gap deviation;

[0012] By using the direction of motion, the initial value of the clearance deviation is corrected to obtain the clearance deviation value corresponding to the lead screw data at the current position.

[0013] Furthermore, the step of using a preset gap error data structure to initially match the lead screw data at the current position to obtain an initial value of the gap deviation includes:

[0014] Based on the lead screw data at the current position, confirm the lead screw position and the local characteristic data of the microhardness, density, and grain orientation of the material being machined.

[0015] By using a preset gap error data structure, the local characteristic data of the lead screw position and the micro-hardness, density and grain orientation of the machine tool material are matched to obtain the initial value of the gap deviation.

[0016] Furthermore, the step of confirming the servo motor drive data based on the gap deviation value and the current position of the leadscrew includes:

[0017] Based on the lead screw data at the current position, determine the position error coefficient of the servo motor, the instantaneous fluctuation coefficient, and the micro-vibration parameters of the machine tool;

[0018] Based on the gap deviation value, the position error coefficient of the servo motor, the instantaneous fluctuation coefficient, and the micro-vibration parameters of the machine tool, the servo motor drive data is confirmed.

[0019] Furthermore, based on the lead screw data at the current position, the steps of determining the position error coefficient of the servo motor, the instantaneous fluctuation coefficient, and the micro-vibration parameters of the machine tool include:

[0020] Based on the lead screw data at the current position, the command position value of the servo motor, the drive current data, and the mechanical vibration data of the machine tool are obtained.

[0021] The position error coefficient of the servo motor is obtained by comparing the commanded position value of the servo motor with the preset position value of the servo motor.

[0022] The instantaneous fluctuation coefficient is obtained by analyzing the instantaneous change trend of the drive current data;

[0023] Spectral analysis was performed on the mechanical vibration data to obtain micro-vibration parameters related to wear or gap abnormalities.

[0024] Furthermore, after confirming the servo motor drive data based on the gap deviation value and the current position of the leadscrew data, the process further includes:

[0025] The servo motor drive data and the preset machine tool model are used to confirm the current feedback signal inside the machine tool;

[0026] The current feedback signal is analyzed and processed to determine the current movement position of the ball screw;

[0027] The current movement position is compared with the preset command position to obtain the position comparison result;

[0028] Based on the position comparison results, the servo motor drive data is adjusted to obtain the adjusted servo motor drive data.

[0029] Furthermore, in the step of confirming the clearance deviation value corresponding to the lead screw data at the current position based on the lead screw data and movement direction and the preset clearance error data structure, the step of constructing the preset clearance error data structure includes:

[0030] Acquire the ball screw's historical data, the corresponding backlash deviation value, and the initial structure of the backlash error data containing a two-dimensional array or linked list structure when the machine tool executes motion commands;

[0031] Based on the historical data of the lead screw, the corresponding gap deviation value of the historical data of the lead screw, and the initial structure of the gap error data containing a two-dimensional array or linked list structure, a preset gap error data structure is constructed.

[0032] Furthermore, the step of acquiring the ball screw's historical data, the corresponding backlash deviation value, and the initial structure of the backlash error data containing a two-dimensional array or linked list when the machine tool executes motion commands includes:

[0033] Acquire the initial historical data of the ball screw, the backlash deviation value corresponding to the initial historical data, and the initial structure of the backlash error data containing a two-dimensional array or linked list structure when the machine tool executes motion commands;

[0034] The historical initial data of the lead screw and the corresponding clearance deviation value are verified to obtain the historical initial data of the lead screw and the corresponding clearance deviation value of the historical data of the lead screw.

[0035] The initial historical data of the lead screw includes the historical position of the lead screw and the local characteristics of the microhardness, density and grain orientation of the machine tool processing material.

[0036] Furthermore, the step of acquiring the ball screw data of its current position and direction of motion when the machine tool executes motion commands includes:

[0037] Obtain local temperature information of the cutting area of ​​the machine tool during machining;

[0038] Based on the local temperature information, the data acquisition parameters of the data sensor are adjusted to obtain the adjusted data sensor.

[0039] Using the adjusted data sensor, the initial data of the ball screw's current position and the initial direction of movement are collected when the machine tool executes motion commands;

[0040] The initial data of the lead screw and the initial direction of motion are preprocessed to obtain the lead screw data and direction of motion at the current position.

[0041] The present invention also provides a machine tool functional component manufacturing process control system, the system comprising:

[0042] The data acquisition module is used to acquire the current position and direction of movement of the ball screw when the machine tool executes motion commands;

[0043] The difference confirmation module is used to confirm the gap deviation value corresponding to the lead screw data at the current position based on the lead screw data at the current position, the direction of movement, and a preset gap error data structure.

[0044] The data confirmation module is used to confirm the servo motor drive data based on the gap deviation value and the lead screw data at the current position.

[0045] The machine tool control module is used to control the machine tool using servo motor drive data, in order to control the manufacturing process of the machine tool's functional components.

[0046] Compared with the prior art, the machine tool functional component manufacturing process control method and system of the present invention have the following advantages:

[0047] This invention acquires the current position and direction of motion of the ball screw, and confirms the clearance deviation value corresponding to that position based on a preset clearance error data structure. This information is then used to confirm the servo motor drive data and control the machine tool. By accurately identifying and compensating for this nonlinear clearance error, this invention overcomes the limitations of fixed reverse clearance compensation methods, avoiding overcutting or undercutting during the finishing of complex curved surfaces. Therefore, the control method of this invention significantly improves the machining accuracy and surface quality of machine tools when machining high-precision and thin-walled complex curved surface functional components, effectively reducing the risk of local stress concentration and deformation of components, thereby improving the overall reliability and service life of functional components. Attached Figure Description

[0048] To more clearly illustrate the specific embodiments of the present invention, the accompanying drawings used in the specific embodiments will be briefly described below. In all the drawings, the elements or parts are not necessarily drawn to scale.

[0049] Figure 1 This is a flowchart of a machine tool functional component manufacturing process control method according to the present invention.

[0050] Figure 2 This is a structural block diagram of a machine tool functional component manufacturing process control system according to the present invention.

[0051] In the diagram: 210, data acquisition module; 220, difference confirmation module; 230, data confirmation module; 240, machine tool control module.

[0052] The implementation and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0053] The following drawings disclose several embodiments of the present invention. For clarity, many practical details will be described in the following description. However, it should be understood that these practical details are not intended to limit the invention. That is, in some embodiments of the invention, these practical details are not essential. Furthermore, for the sake of simplicity, some conventional structures and components will be shown in the drawings in a simple schematic manner.

[0054] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0055] Furthermore, in this invention, the use of terms such as "first" and "second" is for descriptive purposes only and does not specifically refer to any order or sequence, nor is it intended to limit the invention. They are merely used to distinguish components or operations described using the same technical terms, and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of the various embodiments can be combined with each other, but only if they are feasible for those skilled in the art. If a combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0056] When machining high-precision functional components with complex curved surfaces and thin-walled structures, existing machine tools suffer from low precision due to minute tangential discontinuities in the G-code control method. This leads to frequent, minute, and nonlinear responses from the servo motor. These responses are transmitted to the ball screw and nut kinematic pair via the mechanical transmission chain, causing uneven, localized wear on the ball screw raceway surface or the balls. This results in nonlinear backlash errors that vary with position. These errors cannot be precisely eliminated using existing fixed backlash compensation methods, ultimately leading to minute overcuts or undercuts by the tool during machining, severely impacting the component's precision, reliability, and lifespan.

[0057] To further understand the content, features, and effects of this invention, the following embodiments are provided, and detailed descriptions are given below in conjunction with the accompanying drawings:

[0058] Please see Figure 1 This invention provides a method for controlling the manufacturing process of machine tool functional components, comprising the following steps:

[0059] S100. Acquire the ball screw data and direction of motion of the ball screw at its current position when the machine tool executes motion commands. The ball screw data refers to various data that characterize the current position of the ball screw, such as the number of encoder pulses and the absolute position value. This data is typically acquired in real time by sensors mounted on the ball screw or servo motor. The direction of motion refers to the current direction of movement of the ball screw, such as forward or reverse feed. Backlash error may exhibit different characteristics in different directions of motion, making backlash error compensation crucial. For example, the rotation angle of the ball screw can be acquired in real time using a high-precision rotary encoder mounted on the end of the ball screw or the servo motor shaft and converted into linear displacement data as the ball screw data. Simultaneously, by analyzing the changing trends of the servo motor command signal or encoder feedback signal, the current direction of motion of the ball screw can be determined. Alternatively, this step can also directly measure the current position of the ball screw using a high-precision displacement sensor such as a laser interferometer or magnetic scale, and combine this with changes in the forward and backward positions to determine the direction of motion.

[0060] S200. Based on the screw data and movement direction at the current position, and a preset clearance error data structure, confirm the clearance deviation value corresponding to the screw data at the current position. The preset clearance error data structure is a dataset that stores and manages clearance error information of the ball screw at different positions and movement directions. It can be in the form of a lookup table, a multidimensional array, or a function model, used for quickly querying and obtaining the clearance deviation value at a specific position. The clearance deviation value refers to the difference between the actual axial clearance and the ideal clearance of the ball screw at the current position and movement direction, used for precise compensation. For example, the preset clearance error data structure can be a two-dimensional lookup table, where the row index represents different position intervals of the ball screw, and the column index represents the forward or reverse movement direction. The table stores the clearance deviation value for the corresponding position and direction. After obtaining the screw data and movement direction at the current position, locate the corresponding row in the lookup table based on the screw data, and select the corresponding column based on the movement direction to obtain the clearance deviation value. Alternatively, the preset gap error data structure can also be a mathematical model. The model is established by fitting a large amount of historical gap error data and can calculate and output the corresponding gap deviation value based on the input lead screw position and movement direction.

[0061] S300. Based on the gap deviation value and the current position of the leadscrew data, confirm the servo motor drive data. The servo motor drive data refers to the command data used to control the movement of the servo motor, such as position commands, speed commands, and current commands. This data directly affects the machine tool's motion trajectory and accuracy. This invention is typically implemented in a CNC machine tool control system, which includes a data acquisition unit, a data processing unit, a servo drive unit, and the machine tool body. For example, after obtaining the gap deviation value, it can be used as a compensation amount and superimposed on the original servo motor position command. If the gap deviation value is positive, the command position is increased during forward movement and decreased during reverse movement; conversely, the opposite is also true. The current position of the leadscrew data can be used to determine the compensation reference point. Simultaneously, the gap deviation value can also be used to adjust the servo motor's speed or acceleration commands for fine-tuning in the gap region, ensuring the accuracy of the tool trajectory. For example, in areas with large gaps, the speed can be appropriately reduced to give the servo motor more response time for compensation.

[0062] S400: The machine tool is controlled using servo motor drive data to control the manufacturing process of its functional components. This step sends the confirmed servo motor drive data to the servo driver, which then controls the servo motor to rotate precisely, thereby driving the ball screw and achieving precise tool feed. This allows the machine tool to complete the machining of functional components according to the preset manufacturing program, taking into account and compensating for ball screw backlash errors.

[0063] This invention acquires the current position and direction of motion of the ball screw, and confirms the clearance deviation value corresponding to the current position data based on a preset clearance error data structure, enabling refined and localized identification of clearance errors. The preset clearance error data structure stores the actual clearance error information of the ball screw at different positions and directions of motion, allowing for the querying or calculation of the most accurate clearance deviation value based on real-time conditions. Subsequently, based on the precise clearance deviation value and the current position data of the ball screw, the servo motor drive data is confirmed, thereby enabling real-time and adaptive adjustments to the servo motor's motion commands. In other words, this embodiment, by introducing a preset clearance error data structure, overcomes the limitation of traditional fixed compensation values ​​in adapting to nonlinear clearance errors, achieving precise modeling and real-time querying of clearance errors. Secondly, considering the influence of the direction of motion on clearance errors makes compensation more refined. Finally, by integrating the precise clearance deviation value into the confirmation process of the servo motor drive data, adaptive control of the machine tool motion can be achieved, effectively eliminating tool trajectory deviations caused by clearance errors and significantly improving the machining accuracy and surface quality of complex functional components. This effectively solves the problem of overcutting or undercutting that occurs during the finishing process of thin-walled complex curved surface functional components, thereby improving the overall reliability and service life of the components.

[0064] In some embodiments of this application described above, the step of confirming the clearance deviation value corresponding to the lead screw data at the current position based on the lead screw data at the current position, the direction of movement, and a preset clearance error data structure includes:

[0065] Using a preset clearance error data structure, the ball screw data at the current position is initially matched to obtain an initial clearance deviation value. The preset clearance error data structure is a model or database that stores or calculates clearance error information of the ball screw under different positions and motion states. The structure can be trained and built based on a large amount of historical data; for example, by experimentally measuring the actual clearance under different screw positions, loads, and temperatures, and associating it with the corresponding screw data. Specifically, this data structure can be represented as a multidimensional lookup table, a regression model, or a machine learning model, with the aim of quickly estimating the initial clearance deviation based on the input screw data. Initial matching refers to inputting the currently acquired screw data into the preset clearance error data structure, and obtaining a preliminary clearance deviation value, i.e., the initial clearance deviation value, through the logic or algorithm within the structure. The initial value reflects the theoretical clearance deviation without considering the influence of the specific motion direction.

[0066] Using the direction of motion, the initial value of the backlash deviation is corrected to obtain a backlash deviation value corresponding to the current position of the ball screw data. Specifically, the direction of motion refers to the current direction of motion of the ball screw, such as forward or backward. Since the backlash of the ball screw (commonly referred to as backlash or hysteresis) is direction-dependent, meaning that the backlash performance may differ in different motion directions, it is necessary to correct the initial value of the backlash deviation using the current direction of motion. This position correction can be achieved by using a direction correction coefficient or a direction-dependent correction function to adjust the initial value of the backlash deviation to a value that better reflects the actual situation. For example, when the screw switches from forward to reverse motion, due to the backlash, the actual position will lag behind the commanded position, thus requiring compensation for the initial value of the backlash deviation based on the direction of motion.

[0067] In this embodiment, by decomposing the process of confirming the backlash deviation value into two stages—initial matching and position correction—the backlash problem of the ball screw can be handled more precisely. First, by using a preset backlash error data structure to perform initial matching on the screw data at the current position, an initial backlash deviation value based on historical data and model prediction can be quickly obtained, providing a foundation for subsequent precise correction. Second, considering the significant directional dependence of the ball screw backlash effect, by using the motion direction to correct the position of the initial backlash deviation value, the backlash error caused by changes in motion direction can be effectively compensated, resulting in a more accurate backlash deviation value. This step-by-step processing approach makes the identification and quantification of backlash error more precise, providing reliable input for subsequent servo motor drive data confirmation.

[0068] In some embodiments of this application described above, the step of using a preset gap error data structure to initially match the lead screw data at the current position to obtain an initial value of the gap deviation includes:

[0069] Based on the current ball screw data, the ball screw position and the local characteristics of the material being machined, including its microscopic hardness, density, and grain orientation, are confirmed. Specifically, after obtaining the ball screw's current position data when the machine executes motion commands, it is necessary to further confirm the ball screw position information related to this data. Simultaneously, to more accurately assess backlash deviation, it is necessary to obtain the microscopic characteristics of the material being machined, including but not limited to local characteristics such as the material's microscopic hardness, density, and grain orientation. This local characteristic data can be obtained, for example, through online sensors, material database queries, or prior material analysis.

[0070] By utilizing a preset clearance error data structure, the initial value of the clearance deviation is obtained by matching the local characteristics data of the lead screw position and the microscopic hardness, density, and grain orientation of the machine tool material. The preset clearance error data structure is a database or lookup table containing multi-dimensional mapping relationships. It not only stores the correspondence between the lead screw position and the clearance deviation but also further correlates the influence of the microscopic characteristics of different machined materials on the clearance deviation. By using the lead screw data at the current position, the lead screw position data, and the local characteristics data of the microscopic hardness, density, and grain orientation of the machine tool material as input, multi-dimensional matching is performed using this preset clearance error data structure, thereby obtaining a more accurate initial value of the clearance deviation.

[0071] Specifically, the machine tool is machining a high-hardness alloy material. First, the current position data of the ball screw is acquired. Next, based on this data, the screw position is confirmed, and simultaneously, through the material analysis module integrated into the machine tool or a preset material database, local characteristic data such as the microscopic hardness, density, and grain orientation of the high-hardness alloy material are obtained. Then, the screw position data and the local material characteristic data are input together into a preset clearance error data structure. This data structure may be a multi-dimensional lookup table containing preset clearance deviation values ​​for different combinations of screw positions and material properties. Through precise matching, an initial clearance deviation value that comprehensively considers both the current screw position and the characteristics of the high-hardness alloy material can be obtained. For example, if the high-hardness material tends to generate greater cutting forces at a specific screw position, the preset clearance error data structure will reflect the corresponding clearance increase trend, thus providing an initial clearance deviation value that better matches the actual working conditions and avoiding errors that may result from matching solely based on the screw position.

[0072] This embodiment incorporates local characteristic data of the machine tool's machining material's microscopic hardness, density, and grain orientation into the initial matching clearance deviation value, in addition to considering the screw position. The actual clearance deviation of the ball screw is influenced by a variety of factors during machine tool operation. For example, materials of different hardness may exert different reaction forces on the screw during machining, leading to slight changes in the clearance; material density and grain orientation may affect cutting forces, vibration modes, and thermal expansion, thus indirectly or directly affecting the actual clearance of the ball screw. By incorporating local characteristic data into the matching considerations of the preset clearance error data structure, the true clearance state of the ball screw under current operating conditions can be reflected more comprehensively and accurately, resulting in an initial clearance deviation value that is closer to the actual situation.

[0073] In some embodiments of this application described above, the step of confirming the servo motor drive data based on the gap deviation value and the lead screw data at the current position includes:

[0074] Based on the lead screw data at the current position, the position error coefficient of the servo motor, the instantaneous fluctuation coefficient, and the micro-vibration parameters of the machine tool are determined. Specifically, the position error coefficient of the servo motor refers to the degree of deviation between the actual position and the commanded position when the servo motor executes the commanded position. The coefficient can reflect the positioning accuracy of the servo motor under different operating states, such as systematic or random errors that may exist during acceleration, constant speed, or deceleration. The coefficient can be obtained by analyzing the historical operating data of the servo motor or by monitoring the difference between the commanded position and the feedback position of the servo motor in real time. The instantaneous fluctuation coefficient is the degree of unexpected change in the servo motor's drive current or speed over a short period. Fluctuations may be caused by various factors such as unstable power supply voltage, sudden load changes, or internal electromagnetic interference of the motor, directly affecting the smooth operation and response speed of the servo motor. The coefficient can be determined by high-frequency sampling and analysis of the servo motor's drive current or speed signal to identify abnormal instantaneous peaks or valleys. The micro-vibration parameters of the machine tool refer to the small, high-frequency mechanical vibration characteristics generated by the machine tool during operation. Micro-vibrations may originate from wear of ball screws, bearing clearances, the cutting process of cutting tools, or resonance of machine tool structures. Although the amplitude is small, they have a significant impact on machining accuracy and surface quality. Micro-vibration parameters can be collected by accelerometers or vibration sensors installed in key parts of the machine tool, and characteristic values ​​related to specific fault modes or operating states can be extracted through methods such as spectrum analysis.

[0075] Based on the gap deviation value, the position error coefficient of the servo motor, the instantaneous fluctuation coefficient, and the micro-vibration parameters of the machine tool, the servo motor drive data is confirmed.

[0076] Specifically, during precision machining on a machine tool, it is necessary to confirm the servo motor drive data. First, the current position data of the ball screw is acquired. Based on this data, the position error coefficient, instantaneous fluctuation coefficient, and micro-vibration parameters of the machine tool are further analyzed and determined. For example, the position error coefficient can be obtained by comparing the commanded position indicated by the current ball screw data with the actual position fed back by the servo motor encoder; the instantaneous fluctuation coefficient can be obtained by analyzing real-time sampling data of the servo motor drive current and identifying instantaneous current fluctuations; simultaneously, the vibration spectrum is collected and analyzed using micro-vibration sensors installed on the machine tool spindle box or worktable to extract micro-vibration parameters related to the machining process. Subsequently, the determined position error coefficient, instantaneous fluctuation coefficient, and micro-vibration parameters are combined with the previously confirmed clearance deviation value and the current position ball screw data, and a pre-set algorithm model is used for comprehensive calculation to ultimately confirm more accurate and optimized servo motor drive data. For example, if a large position error coefficient is detected, the drive data will be adjusted to increase the compensation amount; if the instantaneous fluctuation coefficient is high, the drive data may be smoothed to reduce jitter; if micro-vibration parameters show resonance at a specific frequency, the drive data may be adjusted to avoid that resonance frequency or to actively suppress it. Servo motor drive data can more accurately reflect the actual operating requirements of the machine tool, thereby achieving precise control over the manufacturing process of the machine tool's functional components.

[0077] This invention, by providing additional parameters that more comprehensively reflect the dynamic characteristics and potential error sources of a machine tool during actual operation, makes the confirmation process of servo motor drive data more refined and adaptive. Specifically, the introduction of a position error coefficient can compensate for the positioning inaccuracy of the servo motor itself; the consideration of an instantaneous fluctuation coefficient helps to cope with instantaneous changes in drive current or speed, ensuring the smooth operation of the motor; and the integration of micro-vibration parameters can identify and compensate for machining errors caused by mechanical vibration. By comprehensively considering these factors, more accurate and robust servo motor drive data can be generated, thereby effectively improving the control accuracy and machining quality of the machine tool.

[0078] In some embodiments of this application described above, the steps of determining the position error coefficient of the servo motor, the instantaneous fluctuation coefficient, and the micro-vibration parameters of the machine tool based on the lead screw data at the current position include:

[0079] Based on the current position data of the ball screw, the commanded position value of the servo motor, the drive current data, and the mechanical vibration data of the machine tool are obtained. Specifically, after obtaining the current position data of the ball screw when the machine tool executes motion commands, the commanded position value of the servo motor, the drive current data, and the mechanical vibration data of the machine tool can be further extracted or correlated from this ball screw data. The commanded position value of the servo motor refers to the desired position command issued by the control system to the servo motor; the drive current data refers to the actual current consumed by the servo motor when responding to the command; and the mechanical vibration data of the machine tool reflects the mechanical vibration generated by the machine tool during operation.

[0080] The position error coefficient of the servo motor is obtained by comparing the commanded position value with the preset position value. The preset position value can be understood as the theoretical position that the servo motor should reach under a specific command in an ideal, error-free state. By comparing the difference between the commanded position value and the preset position value, the degree of deviation in position control of the servo motor can be quantified, thus obtaining the position error coefficient.

[0081] The instantaneous fluctuation coefficient is obtained by analyzing the instantaneous variation trend of the drive current data. The instantaneous variation trend of the drive current reflects the load changes, friction fluctuations, or control response stability of the servo motor during operation. For example, abnormal spikes or severe fluctuations in the drive current may indicate the presence of instantaneous impacts or instability factors. The instantaneous fluctuation coefficient can be obtained by quantitatively analyzing the instantaneous changes.

[0082] Spectral analysis is performed on the mechanical vibration data to obtain micro-vibration parameters related to wear or clearance abnormalities. Mechanical vibration data typically contains multiple frequency components, some of which are closely related to wear of machine tool parts, clearance abnormalities in ball screws, or bearing failures. By performing spectral analysis methods such as Fourier transform on the mechanical vibration data, complex vibration signals can be decomposed into components of different frequencies, and characteristic frequencies and amplitudes corresponding to potential fault modes can be identified, thereby obtaining micro-vibration parameters.

[0083] In this embodiment, by refining the determination process of the servo motor's position error coefficient, instantaneous fluctuation coefficient, and the machine tool's micro-vibration parameters, the machine tool's operating status can be evaluated more comprehensively and accurately. Specifically, by acquiring the servo motor's command position value, drive current data, and the machine tool's mechanical vibration data, and performing comparative trend analysis and spectrum analysis, the key parameters affecting the machine tool's accuracy are quantified from multiple dimensions, including position control accuracy, dynamic response stability, and mechanical health. The accurate acquisition of these key parameters provides a more reliable and refined input for subsequent confirmation of the servo motor drive data based on the backlash deviation value and the current position's lead screw data. This allows for more precise compensation of various error sources when adjusting the servo motor drive data, thereby improving the overall control accuracy of the machine tool.

[0084] In some embodiments of this application described above, after confirming the servo motor drive data based on the gap deviation value and the lead screw data at the current position, the method further includes:

[0085] The servo motor drive data and the preset machine tool model are used to confirm the current feedback signal inside the machine tool. Specifically, before using the servo motor drive data for machine tool control, the servo motor drive data is first combined with the preset machine tool model to confirm the current feedback signal inside the machine tool. The preset machine tool model can be understood as a mathematical or simulation model describing the machine tool's mechanical structure, dynamic characteristics, and sensor responses. Its purpose is to predict or analyze the machine tool's expected response or actual state based on the given drive data. The current feedback signal can be data collected in real time by sensors (such as encoders or displacement sensors) installed in key parts of the machine tool (such as ball screws or worktables), reflecting the machine tool's actual operating state after receiving the servo motor drive data.

[0086] The current feedback signal is processed by position analysis to determine the current movement position of the ball screw. This position analysis may include steps such as signal filtering, noise removal, and data conversion, aiming to accurately extract the actual spatial coordinates or displacement information of the ball screw from the original feedback signal. For example, if the feedback signal is an encoder pulse, the rotation angle of the ball screw can be obtained by counting and conversion, thereby determining its linear displacement.

[0087] The current movement position is compared with the preset commanded position to obtain a position comparison result. The preset commanded position refers to the ideal position that the ball screw should reach, as planned in the machine tool functional component manufacturing program. The position comparison result can be an error value, representing the deviation between the actual position and the commanded position.

[0088] Based on the position comparison results, the servo motor drive data is adjusted to obtain the adjusted servo motor drive data. Specifically, this adjustment process can employ various control algorithms, such as proportional, integral, derivative (PID) control, fuzzy control, or adaptive control. The purpose is to correct the servo motor drive command in real time based on the detected position deviation, so as to reduce or eliminate the deviation and make the actual movement of the ball screw more accurately follow the preset command.

[0089] Specifically, in the manufacturing process of machine tool functional components, the ball screw needs to move from position one to position two. First, based on the acquired screw data at the current position, the direction of movement, and the preset clearance error data structure, the initial servo motor drive data is confirmed. However, after the servo motor starts driving the ball screw, its position information is collected in real time by a high-precision encoder mounted on the ball screw, serving as the current feedback signal within the machine tool. This encoder data is sent to a position analysis module for processing to determine the current position of the ball screw. For example, when the ball screw should theoretically reach a position of 100 micrometers, the position analysis module detects that its actual position is 95 micrometers, a deviation of 5 micrometers. This 5-micrometer position comparison result is then sent to a PID controller. Based on this deviation, the PID controller determines the correction amount for the servo motor drive data, such as increasing the drive current or the number of pulses, thereby adjusting the servo motor drive data. The adjusted servo motor drive data is sent to the servo motor to accelerate or decelerate, correcting the 5-micrometer deviation and bringing the actual position of the ball screw closer to the preset command position as quickly as possible. By continuously adjusting the feedback loop until the ball screw precisely reaches the target position two, the manufacturing precision of the machine tool functional components is ensured.

[0090] In this embodiment, by introducing a real-time feedback and correction mechanism, the insufficient accuracy caused by relying solely on pre-confirmed servo motor drive data for open-loop control is effectively avoided. Specifically, after the servo motor drive data is confirmed, it is not directly used for control, but rather combined with a preset machine tool model to confirm the current feedback signal inside the machine tool. The feedback signal can accurately reflect the actual operating state of the machine tool under the action of the current drive data. Subsequently, by performing position analysis processing on the feedback signal, the current movement position of the ball screw can be accurately obtained, thereby achieving real-time monitoring of the actual state of the machine tool. By comparing the current movement position with the preset command position, the deviation between the actual operation of the machine tool and the ideal path can be quantified, i.e., the position comparison result. It is based on the real-time quantified deviation information that the servo motor drive data can be dynamically adjusted. This allows the machine tool to self-correct according to the actual operating conditions, ensuring that the movement trajectory of the ball screw can more closely follow the preset command, thereby significantly improving the manufacturing accuracy and stability of the machine tool functional components.

[0091] In some embodiments of this application described above, the step of confirming the clearance deviation value corresponding to the lead screw data at the current position based on the lead screw data at the current position, the direction of movement, and a preset clearance error data structure, includes the following steps in constructing the preset clearance error data structure:

[0092] This process acquires the ball screw's historical data, corresponding backlash deviation values, and an initial structure for backlash error data containing a two-dimensional array or linked list when the machine tool executes motion commands. The historical ball screw data refers to the actual position data of the ball screw at different points, collected periodically or continuously by sensors or other monitoring equipment during long-term machine tool operation. This data reflects the ball screw's running trajectory and position information under different working conditions and is the basis for analyzing its motion characteristics. The backlash deviation value corresponding to the historical ball screw data refers to the actual backlash deviation measured or determined at each historical position point of the ball screw using high-precision measuring equipment or a specific calibration procedure while acquiring the historical data. The deviation value is typically obtained through forward and reverse motion tests, recording the nonlinear displacement generated by the ball screw during commutation, and is used to quantify the mechanical backlash of the ball screw.

[0093] Based on the historical data of the lead screw, the corresponding gap deviation values, and the initial structure of the gap error data containing a two-dimensional array or linked list, a preset gap error data structure is constructed. Specifically, the initial structure of the gap error data containing a two-dimensional array or linked list can be understood as a predefined data model for storing and organizing gap error data. For example, a two-dimensional array can be used to store the mapping relationship between the lead screw position and the corresponding gap deviation value, where one row or column represents the lead screw position and the other row or column represents the gap deviation value. The linked list structure can be used to dynamically add, delete, or modify gap error data, which is particularly suitable for scenarios with large data volumes or frequent updates. Its purpose is to provide a flexible and efficient data storage framework for subsequent data filling and structured processing. Specifically, the process of constructing the preset gap error data structure involves filling and organizing the acquired historical data of the lead screw and its corresponding gap deviation values ​​according to the preset two-dimensional array or linked list structure. For example, the historical data of the lead screw can be used as an index or key, and the corresponding gap deviation values ​​can be used as storage content to form a data table or data set that can be queried and matched. This construction process aims to transform discrete historical measurement data into a structured and queryable gap error model, providing a data foundation for subsequent confirmation of gap deviation values.

[0094] In this embodiment, by acquiring a large amount of historical ball screw data and its corresponding backlash deviation values, and storing them in a structured manner in a preset backlash error data structure, reliable data support is provided for accurately confirming the backlash deviation value based on the current position of the ball screw and the direction of movement when the machine tool executes motion commands. This allows for quick and accurate retrieval of the backlash deviation information that best matches the current ball screw position, avoiding the overhead of real-time measurement or complex calculations, and improving the efficiency and accuracy of backlash compensation. Through the pre-established backlash error model, the machine tool control system can better understand and predict the backlash characteristics of the ball screw under different positions and directions of movement, laying the foundation for subsequent servo motor drive data confirmation.

[0095] In some embodiments of this application described above, the step of obtaining the ball screw's historical data, the corresponding backlash deviation value, and the initial structure of the backlash error data containing a two-dimensional array or linked list when the machine tool executes motion commands includes:

[0096] This step involves acquiring the initial historical data of the ball screw, the corresponding backlash deviation value, and the initial data structure for backlash error (containing a two-dimensional array or linked list) when the machine tool executes motion commands. Specifically, this step involves collecting historical position data of the ball screw under different motion commands, corresponding actual backlash deviation measurements, and the initial data structure for storing the data, using sensors or data recording systems. The initial historical data not only includes the historical position of the ball screw but also further includes historical data on the local characteristics of the machined material, such as microscopic hardness, density, and grain orientation. This local characteristic data is crucial for understanding and predicting the formation mechanism of backlash error, as the physical properties of the material directly affect factors such as wear, deformation, and thermal expansion, thus influencing the ball screw backlash.

[0097] The initial historical data of the leadscrew and the corresponding gap deviation values ​​are verified to obtain the initial historical data of the leadscrew and the corresponding gap deviation values. The purpose of this step is to ensure the accuracy and reliability of the collected historical data. The verification process includes data integrity checks, such as detecting missing values; data consistency checks, such as comparing data from different sources or different time points to see if they contradict each other; outlier detection, such as identifying and processing data points that significantly deviate from the normal range; and data format and type verification to ensure that the data meets the preset storage requirements. Through verification, unqualified data can be eliminated or corrected, thereby obtaining high-quality historical data of the leadscrew and the corresponding gap deviation values, providing a reliable foundation for the subsequent construction of the preset gap error data structure.

[0098] The initial historical data of the lead screw includes the historical position of the lead screw and the local characteristics of the microhardness, density and grain orientation of the machine tool processing material.

[0099] Specifically, in the manufacturing process of machine tool functional components, a high-precision preset clearance error data structure needs to be constructed. First, using high-precision displacement and force sensors, the ball screw's historical initial position data, drive current data, and environmental parameters such as local temperature and vibration in the machine tool's machining area are collected as the machine tool executes a series of preset motion commands. Simultaneously, material analysis equipment is used to measure the microscopic hardness, density, and grain orientation of the processed material in real time or periodically, and the historical data of local characteristics is correlated with the ball screw's historical initial position data to form complete ball screw historical initial data. After acquiring the data, the ball screw's historical initial data and the corresponding initial clearance deviation values ​​are verified. For example, thresholds are set to detect abrupt changes or jumps in the ball screw position data, statistical analysis methods are used to identify outliers in the initial clearance deviation values, or cross-validation of data from different sensors is used to check consistency. If data anomalies are found, they are marked, corrected, or removed. For example, if the ball screw position data at a certain point in time has a significant discontinuity with the data points before and after it, it may be judged as abnormal data and interpolated for correction. After verification, high-quality ball screw historical data and corresponding clearance deviation values ​​are obtained. The data is then used to construct a preset clearance error data structure containing a two-dimensional array or linked list structure, thereby ensuring that the data structure can accurately reflect the clearance error law of the ball screw under different working conditions and material properties.

[0100] In this embodiment, by introducing a verification step during the acquisition of historical data and clearance deviation values ​​of the leadscrew, and by explicitly including historical data on the local characteristics of the machine tool's material microstructure (hardness, density, and grain orientation) in the initial historical data of the leadscrew, the accuracy of the preset clearance error data structure is effectively avoided due to poor quality or incomplete information in the historical data. The verification step filters out abnormal or inaccurate historical data, ensuring the reliability of the data source used to construct the clearance error data structure. Simultaneously, incorporating local characteristic data such as the hardness, density, and grain orientation of the machine tool's material microstructure into the initial historical data of the leadscrew allows the constructed preset clearance error data structure to more comprehensively consider the physical factors affecting clearance error, thereby enabling the clearance error data structure to more accurately reflect the clearance variation patterns under different working conditions and material properties. Due to the dual optimization of historical data quality and information dimensions, the subsequently confirmed clearance deviation values ​​are more accurate, thereby improving the overall accuracy and stability of the machine tool functional component manufacturing program control.

[0101] In some embodiments of this application described above, the step of obtaining the ball screw data of its current position and direction of motion when the machine tool executes a motion command includes:

[0102] Acquire local temperature information of the cutting area of ​​the machine tool during machining. This step involves monitoring the temperature changes in this area in real time using temperature sensors placed near the cutting area. During machining, the friction between the tool and the workpiece generates heat, leading to a rise in local temperature, which may affect the physical properties of the material and the accuracy of the measuring equipment. Therefore, obtaining accurate local temperature information is fundamental for subsequent data acquisition and processing.

[0103] Based on the local temperature information, the data acquisition parameters of the data sensor are adjusted to obtain the adjusted data sensor. Specifically, when the local temperature information shows a temperature exceeding a preset range, the data acquisition parameters of the data sensor, such as sampling frequency, gain, and filtering parameters, can be dynamically adjusted. For example, in high-temperature environments, the sensor's sensitivity may decrease. In this case, the gain can be appropriately increased or the sampling frequency adjusted to compensate for the effect of temperature on measurement accuracy. In this way, it can be ensured that the data sensor maintains optimal acquisition performance under different operating temperatures, thereby obtaining more reliable measurement data.

[0104] Using an adjusted data sensor, the initial data of the ball screw's current position and initial direction of motion are acquired in real time when the machine tool executes motion commands. The adjusted data sensor can obtain the precise position information (initial ball screw data) and its current direction of motion (initial direction of motion) of the ball screw with higher accuracy and reliability. The initial data are raw measurements without any correction.

[0105] The initial data and initial direction of motion of the leadscrew are preprocessed to obtain the leadscrew data and direction of motion at the current position. Specifically, the preprocessing steps may include, but are not limited to, noise filtering, data smoothing, outlier removal, and unit conversion. For example, Kalman filtering or moving average filtering can be used to process the initial data of the leadscrew to eliminate measurement noise; logical judgment or pattern recognition can be performed on the initial direction of motion to ensure the accuracy of the direction information. Through preprocessing, interference and errors in the original data can be removed, thereby obtaining more accurate and reliable leadscrew data and direction of motion at the current position, providing high-quality input for subsequent confirmation of clearance deviation values.

[0106] In this embodiment, by introducing the acquisition of local temperature information in the cutting area of ​​the machine tool, and dynamically adjusting the data acquisition parameters of the data sensor based on this temperature information, the process of acquiring ball screw data and motion direction at the current position is optimized. Data acquisition may be performed under fixed parameters, ignoring the impact of temperature changes during machining on sensor performance and measurement accuracy. However, machine tool machining is a dynamic heating process, and temperature fluctuations directly affect the measurement accuracy of the sensor. By monitoring the local temperature in real time and adjusting the sensor parameters accordingly, the sensor can adapt to different working environments and always acquire data in the optimal state. Subsequently, the acquired initial ball screw data and initial motion direction are preprocessed to further eliminate measurement noise and potential errors, ensuring the accuracy and reliability of the final ball screw data and motion direction.

[0107] Based on any of the above embodiments, a machine tool functional component manufacturing process control method is described. Please refer to [link to relevant documentation]. Figure 2 The present invention also provides a machine tool functional component manufacturing program control system, which includes a data acquisition module 210, a difference confirmation module 220, a data confirmation module 230 and a machine tool control module 240.

[0108] The data acquisition module 210 is used to acquire the current position data and movement direction of the ball screw when the machine tool executes motion commands.

[0109] The difference confirmation module 220 is used to confirm the gap deviation value corresponding to the lead screw data at the current position based on the lead screw data at the current position, the direction of movement, and the preset gap error data structure.

[0110] The data confirmation module 230 is used to confirm the servo motor drive data based on the gap deviation value and the lead screw data at the current position.

[0111] The machine tool control module 240 is used to control the machine tool using servo motor drive data in order to control the manufacturing process of the machine tool functional components.

[0112] In this embodiment, the data acquisition module 210 collects the current position and direction of movement of the ball screw in real time, and the difference confirmation module 220 confirms the clearance deviation value corresponding to the current position ball screw data based on a preset clearance error data structure, thus achieving refined and localized identification of clearance errors. The preset clearance error data structure stores the actual clearance error information of the ball screw at different positions and directions of movement, enabling the system to query or calculate the most accurate clearance deviation value based on the real-time status. Subsequently, the data confirmation module 230 confirms the servo motor drive data based on this precise clearance deviation value and the current position ball screw data, thereby making real-time and adaptive adjustments to the motion commands of the servo motor. Finally, the machine tool control module 240 uses these adjusted drive data to achieve precise control of the machine tool movement.

[0113] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the present invention specification.

Claims

1. A method for controlling the manufacturing process of machine tool functional components, characterized in that, Includes the following steps: Acquire the current position and direction of the ball screw when the machine tool executes motion commands; Based on the lead screw data and movement direction at the current position and the preset clearance error data structure, the clearance deviation value corresponding to the lead screw data at the current position is confirmed. Based on the gap deviation value and the lead screw data at the current position, confirm the servo motor drive data; The machine tool is controlled by using servo motor drive data to control the manufacturing process of the machine tool's functional components. The step of confirming the clearance deviation value corresponding to the lead screw data at the current position based on the lead screw data at the current position, the direction of motion, and the preset clearance error data structure includes: Using a preset gap error data structure, the lead screw data at the current position is initially matched to obtain the initial value of the gap deviation; Using the direction of motion, the initial value of the clearance deviation is corrected to obtain the clearance deviation value corresponding to the lead screw data at the current position; The step of using a preset gap error data structure to initially match the lead screw data at the current position to obtain an initial value of the gap deviation includes: Based on the lead screw data at the current position, confirm the lead screw position and the local characteristic data of the microhardness, density, and grain orientation of the material being machined. By using a preset gap error data structure, the local characteristic data of the lead screw position and the micro-hardness, density and grain orientation of the machine tool material are matched to obtain the initial value of the gap deviation. In the step of confirming the clearance deviation value corresponding to the lead screw data at the current position based on the lead screw data and motion direction and a preset clearance error data structure, the step of constructing the preset clearance error data structure includes: Acquire the ball screw's historical data, the corresponding backlash deviation value, and the initial structure of the backlash error data containing a two-dimensional array or linked list structure when the machine tool executes motion commands; Based on the historical data of the lead screw, the corresponding gap deviation value of the historical data of the lead screw, and the initial structure of the gap error data containing a two-dimensional array or linked list structure, a preset gap error data structure is constructed.

2. The machine tool functional component manufacturing program control method according to claim 1, characterized in that, Based on the gap deviation value and the current position of the leadscrew data, the steps for confirming the servo motor drive data include: Based on the lead screw data at the current position, determine the position error coefficient of the servo motor, the instantaneous fluctuation coefficient, and the micro-vibration parameters of the machine tool; Based on the gap deviation value, the position error coefficient of the servo motor, the instantaneous fluctuation coefficient, and the micro-vibration parameters of the machine tool, the servo motor drive data is confirmed.

3. The machine tool functional component manufacturing program control method according to claim 2, characterized in that, The steps for determining the position error coefficient, instantaneous fluctuation coefficient, and micro-vibration parameters of the servo motor based on the current position of the leadscrew data include: Based on the lead screw data at the current position, the command position value of the servo motor, the drive current data, and the mechanical vibration data of the machine tool are obtained. The position error coefficient of the servo motor is obtained by comparing the commanded position value of the servo motor with the preset position value of the servo motor. The instantaneous fluctuation coefficient is obtained by analyzing the instantaneous change trend of the drive current data; Spectral analysis was performed on the mechanical vibration data to obtain micro-vibration parameters related to wear or gap abnormalities.

4. The machine tool functional component manufacturing program control method according to claim 1, characterized in that, After confirming the servo motor drive data based on the gap deviation value and the current position of the leadscrew data, the process further includes: The servo motor drive data and the preset machine tool model are used to confirm the current feedback signal inside the machine tool; The current feedback signal is analyzed and processed to determine the current movement position of the ball screw; The current movement position is compared with the preset command position to obtain the position comparison result; Based on the position comparison results, the servo motor drive data is adjusted to obtain the adjusted servo motor drive data.

5. The machine tool functional component manufacturing program control method according to claim 1, characterized in that, The steps of acquiring the ball screw's historical data, the corresponding backlash deviation value, and the initial structure of the backlash error data containing a two-dimensional array or linked list when the machine tool executes motion commands include: Acquire the initial historical data of the ball screw, the backlash deviation value corresponding to the initial historical data, and the initial structure of the backlash error data containing a two-dimensional array or linked list structure when the machine tool executes motion commands; The historical initial data of the lead screw and the corresponding clearance deviation value are verified to obtain the historical initial data of the lead screw and the corresponding clearance deviation value of the historical data of the lead screw. The initial historical data of the lead screw includes the historical position of the lead screw and the local characteristics of the microhardness, density and grain orientation of the machine tool processing material.

6. The machine tool functional component manufacturing program control method according to claim 1, characterized in that, The steps of acquiring the ball screw's current position and direction of motion data when the machine tool executes motion commands include: Obtain local temperature information of the cutting area of ​​the machine tool during machining; Based on the local temperature information, the data acquisition parameters of the data sensor are adjusted to obtain the adjusted data sensor. Using the adjusted data sensor, the initial data of the ball screw's current position and the initial direction of movement are collected when the machine tool executes motion commands; The initial data of the lead screw and the initial direction of motion are preprocessed to obtain the lead screw data and direction of motion at the current position.

7. A machine tool functional component manufacturing program control system, characterized in that, The system includes: The data acquisition module is used to acquire the current position and direction of movement of the ball screw when the machine tool executes motion commands; The difference confirmation module is used to confirm the gap deviation value corresponding to the lead screw data at the current position based on the lead screw data at the current position, the direction of movement, and a preset gap error data structure. The data confirmation module is used to confirm the servo motor drive data based on the gap deviation value and the lead screw data at the current position. The machine tool control module is used to control the machine tool using servo motor drive data in order to control the manufacturing process of the machine tool's functional components. The difference confirmation module is also used for: Using a preset gap error data structure, the lead screw data at the current position is initially matched to obtain the initial value of the gap deviation; Using the direction of motion, the initial value of the clearance deviation is corrected to obtain the clearance deviation value corresponding to the lead screw data at the current position; The step of using a preset gap error data structure to initially match the lead screw data at the current position to obtain an initial value of the gap deviation includes: Based on the lead screw data at the current position, confirm the lead screw position and the local characteristic data of the microhardness, density, and grain orientation of the material being machined. By using a preset gap error data structure, the local characteristic data of the lead screw position and the micro-hardness, density and grain orientation of the machine tool material are matched to obtain the initial value of the gap deviation. In the step of confirming the clearance deviation value corresponding to the lead screw data at the current position based on the lead screw data and motion direction and a preset clearance error data structure, the step of constructing the preset clearance error data structure includes: Acquire the ball screw's historical data, the corresponding backlash deviation value, and the initial structure of the backlash error data containing a two-dimensional array or linked list structure when the machine tool executes motion commands; Based on the historical data of the lead screw, the corresponding gap deviation value of the historical data of the lead screw, and the initial structure of the gap error data containing a two-dimensional array or linked list structure, a preset gap error data structure is constructed.

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