Method and system for automatically adjusting and controlling precision of numerical control machine tool

Abstract

The invention relates to the technical field of numerical control machine tool control, and provides an automatic precision adjustment control method and system for a numerical control machine tool, and the method comprises the steps: continuously judging the influence degree of a non-uniform mechanical wear error and a thermal deformation error on the current machining precision according to a non-uniform mechanical wear error feature and a thermal deformation error feature; according to the non-uniform mechanical wear error characteristics, calculating the mechanical wear compensation amount related to the motion axis position and the motion direction; according to the thermal deformation error characteristics, calculating a thermal deformation compensation amount related to the machining time length; according to the influence degree, the combination mode of the mechanical wear compensation amount and the thermal deformation compensation amount is adjusted, the mechanical wear compensation amount and the thermal deformation compensation amount are fused based on the combination mode, and a motion instruction compensation value is generated; and continuously superposing the motion instruction compensation value into an original motion instruction of the numerical control system so as to realize automatic precision adjustment and control. The method has the effect of improving the machining precision, stability and production efficiency of the numerical control machine tool.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of numerical control machine tool control, and in particular to a precision automatic adjustment control method and system for a numerical control machine tool. BACKGROUND

[0002] In the field of high-end equipment manufacturing, the machining precision of numerical control machine tools is critical to product quality. However, in long-term high-intensity operation, the internal precision components of the machine tool, such as the ball screw, will produce uneven mechanical property changes due to continuous wear, and the heat generated by long-time work will also cause the machine tool structure to deform. These factors together cause the actual machining precision of the machine tool to deviate from the expected value, especially when manufacturing parts with extremely high precision requirements, traditional error compensation methods often struggle to effectively cope with these complex and changing errors, thereby affecting product quality and production efficiency.

[0003] When the machine tool needs to perform a finishing task that requires long-term continuous operation, the high-speed rotation of the spindle and the continuous movement of the feed shaft motor generate a large amount of heat. This heat, through conduction and convection, gradually raises the temperature of the machine tool's cast iron bed, ball screw, and other key structural components, causing thermal expansion. This thermal expansion introduces new errors that change with the length of time of machining. For example, the length of the ball screw will elongate due to the rise in temperature, causing a drift between the actual position and the commanded position; the thermal deformation of the machine tool bed can also change the relative position relationship between the tool and the workpiece. Since the preset pitch error compensation table is generated based on measurement data at cold or stable temperature, it is essentially a static compensation scheme that cannot sense and respond to structural deformation and error drift caused by temperature changes in real time.

[0004] Therefore, in the complex working conditions where the long-term high-load operation of the numerical control machine tool causes the ball screw transmission system to produce non-uniform, position and motion direction related mechanical wear, and in the long-term continuous machining process, the heat generated by the spindle and feed shaft motor causes the machine tool structure to produce thermal expansion errors that change with the length of time of machining, it is a technical problem to be solved that how to realize the automatic and real-time adjustment and maintenance of the machining precision of the machine tool to accurately compensate for these multi-source, time-varying and nonlinear errors, thereby avoiding the formation of detectable microscopic defects on the surface of precision parts and ensuring the high consistency of product quality.

[0005] In view of the above problems, the existing technology needs to be improved. SUMMARY

[0006] This application discloses an automatic precision adjustment and control method and system for CNC machine tools, aiming to solve the problem of decreased machining accuracy caused by non-uniform mechanical wear of the ball screw transmission system and thermal deformation of the machine tool structure during long-term high-intensity operation of CNC machine tools, as well as the limitations of traditional error compensation methods in effectively dealing with complex and constantly changing errors.

[0007] The technical solution of this application is as follows: In a first aspect, this application discloses an automatic precision adjustment and control method for CNC machine tools, comprising the following steps: Collect multi-dimensional information on the machine tool's operating status; Based on multi-dimensional information, continuously identify the non-uniform mechanical wear error characteristics of the ball screw transmission system and the thermal deformation error characteristics of the machine tool structure; Based on the characteristics of non-uniform mechanical wear error and thermal deformation error, continuously assess the degree of influence of non-uniform mechanical wear error and thermal deformation error on the current machining accuracy; Based on the characteristics of non-uniform mechanical wear error, calculate the mechanical wear compensation amount related to the position and direction of motion of the moving axis; based on the characteristics of thermal deformation error, calculate the thermal deformation compensation amount related to the processing time. Based on the degree of impact, the combination of mechanical wear compensation and thermal deformation compensation is adjusted, and the mechanical wear compensation and thermal deformation compensation are integrated based on the combination to generate motion command compensation values; The motion command compensation value is continuously superimposed on the original motion command of the CNC system to achieve automatic precision adjustment control.

[0008] Through this technical solution, this application can identify and quantify the non-uniform mechanical wear error and thermal deformation error generated by CNC machine tools in real time and dynamically. Based on their impact on machining accuracy, the compensation strategy is intelligently adjusted to generate accurate motion command compensation values. This effectively solves the problem that traditional static compensation methods cannot cope with multi-source, time-varying and nonlinear errors, and significantly improves the machining accuracy and stability of CNC machine tools.

[0009] Secondly, this application also discloses an automatic precision adjustment and control system for CNC machine tools, used to perform automatic precision adjustment and control of CNC machine tools, including: The multi-dimensional information acquisition module is used to collect multi-dimensional information about the machine tool's operating status. The feature recognition module is used to continuously identify the non-uniform mechanical wear error characteristics of the ball screw transmission system and the thermal deformation error characteristics of the machine tool structure based on multi-dimensional information. The impact degree judgment module is used to continuously judge the impact degree of non-uniform mechanical wear error and thermal deformation error on the current machining accuracy based on the characteristics of non-uniform mechanical wear error and thermal deformation error. The compensation calculation module is used to calculate the mechanical wear compensation amount related to the position and direction of motion of the moving axis based on the characteristics of non-uniform mechanical wear error; and to calculate the thermal deformation compensation amount related to the processing time based on the characteristics of thermal deformation error. The motion compensation generation module is used to adjust the combination of mechanical wear compensation and thermal deformation compensation according to the degree of influence, and to merge the mechanical wear compensation and thermal deformation compensation based on the combination to generate motion command compensation values. The compensation superposition execution module is used to continuously superimpose motion command compensation values ​​onto the original motion commands of the CNC system to achieve automatic precision adjustment and control.

[0010] This application provides a system that can automatically adjust and control the precision of CNC machine tools through this technical solution. The system, through modular design, realizes the acquisition of machine tool operating status information, identification of error characteristics, judgment of the degree of influence, calculation of compensation amount, and generation and superposition of motion command compensation values, thereby providing reliable hardware and software support for the long-term high-precision operation of CNC machine tools.

[0011] Beneficial Effects: The automatic precision adjustment and control method for CNC machine tools disclosed in this application can comprehensively perceive the real-time working condition of the machine tool by collecting multi-dimensional information on the machine tool's operating status. Based on this, the method continuously identifies the non-uniform mechanical wear error characteristics of the ball screw transmission system and the thermal deformation error characteristics of the machine tool structure, achieving accurate capture of the two main error sources. Furthermore, the method can continuously judge the degree of influence of these two errors on the current machining accuracy, providing a decision-making basis for subsequent compensation strategies. For the identified error characteristics, the method calculates the mechanical wear compensation amount related to the position and direction of motion of the motion axis and the thermal deformation compensation amount related to the machining time, ensuring the targeted nature of the compensation. More importantly, the method can dynamically adjust the combination of mechanical wear compensation and thermal deformation compensation amounts according to the degree of error influence, and integrate the two compensation amounts based on this combination to generate motion command compensation values, thereby achieving collaborative optimization compensation for multi-source, time-varying, and nonlinear errors. Finally, the generated motion command compensation values ​​are continuously superimposed on the original motion commands of the CNC system, realizing automatic and real-time adjustment and maintenance of the machine tool's machining accuracy.

[0012] Compared to existing technologies, the method in this application overcomes the limitations of traditional static compensation schemes in handling complex working conditions. Through real-time identification, quantification, and dynamic fusion compensation of non-uniform mechanical wear and thermal deformation errors, this application effectively solves the problem of decreased machining accuracy caused by the superposition of non-uniform wear and thermal expansion errors in ball screws during long-term high-load operation of CNC machine tools. This method avoids the formation of detectable micro-defects on the surface of precision parts, ensuring high consistency in product quality and significantly improving the machining accuracy, stability, and production efficiency of CNC machine tools, demonstrating significant technological advancement and practical value. Attached Figure Description

[0013] Figure 1 This is a flowchart of an automatic precision adjustment and control method for a CNC machine tool according to one embodiment of the present invention; Figure 2 This is a flowchart of an automatic precision adjustment and control method for a CNC machine tool according to another embodiment of the present invention; Figure 3 This is a system block diagram of an automatic precision adjustment and control system for a CNC machine tool according to another embodiment of the present invention; Explanation of reference numerals in the attached figures: 1. Automatic precision adjustment and control system for CNC machine tools; 11. Multi-dimensional information acquisition module; 12. Feature continuous recognition module; 13. Influence degree judgment module; 14. Compensation amount calculation module; 15. Motion compensation generation module; 16. Compensation superposition execution module. Detailed Implementation

[0014] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0015] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0016] In response, this application proposes an automatic precision adjustment and control method for CNC machine tools, combining...Figure 1 As shown, it includes the following steps: S1 collects multi-dimensional information on the machine tool's operating status; S2, based on multi-dimensional information, continuously identifies the non-uniform mechanical wear error characteristics of the ball screw transmission system and the thermal deformation error characteristics of the machine tool structure; S3, based on the characteristics of non-uniform mechanical wear error and thermal deformation error, continuously judge the degree of influence of non-uniform mechanical wear error and thermal deformation error on the current machining accuracy; S4. Based on the characteristics of non-uniform mechanical wear error, calculate the mechanical wear compensation amount related to the position and direction of motion of the moving axis; based on the characteristics of thermal deformation error, calculate the thermal deformation compensation amount related to the processing time. S5, adjust the combination of mechanical wear compensation and thermal deformation compensation according to the degree of impact, and merge the mechanical wear compensation and thermal deformation compensation based on the combination to generate motion command compensation value; S6 continuously adds motion command compensation values ​​to the original motion commands of the CNC system to achieve automatic precision adjustment and control.

[0017] "Multi-dimensional information" refers to various types of data that reflect the machine tool's operating status, such as temperature sensor data, vibration sensor data, current and voltage data, encoder feedback data, machining parameters (such as feed rate, spindle speed, and depth of cut), and environmental parameters (such as ambient temperature and humidity). This information is acquired in real time through various sensors and CNC system interfaces, providing a comprehensive data foundation for subsequent error identification and compensation. "Non-uniform mechanical wear error characteristics" refer to the error characteristics caused by the inconsistent wear exhibited by the ball screw transmission system at different positions and in different directions of motion, such as increased clearance in specific stroke segments, friction fluctuations, and backlash errors. These characteristics reflect the cumulative effect of localized wear on the ball screw during long-term use. "Thermal deformation error characteristics" refer to the error characteristics caused by changes in the geometric dimensions and shape of the machine tool structure due to thermal expansion or contraction, such as axial elongation of the ball screw, thermal bending of the bed, and vertical displacement of the spindle box. These characteristics are usually related to factors such as machining time, spindle load, and ambient temperature.

[0018] The embodiments of this application provide an automatic precision adjustment and control method for CNC machine tools.

[0019] First, it is necessary to collect multi-dimensional information on the machine tool's operating status. For example, temperature sensors, vibration sensors, and displacement sensors can be installed in key parts of the machine tool (such as the ball screw support, spindle box, and bed) to acquire real-time data on the temperature, vibration frequency, and relative displacement of various machine tool components. Simultaneously, the CNC system can provide machining parameters such as the current feed rate, spindle speed, depth of cut, and machining load, as well as the real-time position and speed information of the moving axes. Furthermore, environmental sensors can be used to acquire the temperature and humidity of the workshop environment. This data is collected into a data acquisition unit and undergoes preliminary data cleaning and preprocessing to ensure data accuracy and consistency.

[0020] Secondly, based on the collected multi-dimensional information, the non-uniform mechanical wear error characteristics of the ball screw transmission system and the thermal deformation error characteristics of the machine tool structure are continuously identified. For example, by analyzing the deviation between the encoder feedback data and the command position of the motion axis, combined with historical wear data models, the non-linear position error of the ball screw in a specific stroke segment can be identified, which may indicate non-uniform wear in that area. Simultaneously, by analyzing temperature sensor data and combining it with the machine tool's thermal model, the thermal expansion and thermal deformation trends of key structural components of the machine tool (such as the bed, spindle box, and ball screw) can be calculated in real time, thereby identifying thermal deformation error characteristics. For example, when the machine tool operates at high speed for a long time, the temperature of the spindle box will rise, causing it to thermally expand along the Z-axis direction. This expansion can be calculated using temperature data and the material's coefficient of thermal expansion.

[0021] Furthermore, based on the identified non-uniform mechanical wear error characteristics and thermal deformation error characteristics, the degree of influence of these errors on the current machining accuracy is continuously assessed. For example, an error impact assessment model can be established, which comprehensively considers the instantaneous magnitude and rate of change of wear and thermal deformation errors, as well as the accuracy requirements of the current machining task. When machining high-precision parts, even minute errors may be judged as having a high degree of impact; while in rough machining, errors of the same magnitude may be judged as having a low degree of impact. This model can be implemented based on fuzzy logic or an expert system, outputting a quantified degree of impact value according to different input error characteristics.

[0022] Then, based on the identified non-uniform mechanical wear error characteristics, the mechanical wear compensation amount related to the position and direction of motion of the motion axis is calculated; based on the identified thermal deformation error characteristics, the thermal deformation compensation amount related to the machining time is calculated. For example, for the mechanical wear compensation amount, a polynomial fitting model or lookup table can be established based on the historical wear data of the ball screw at different positions and in different directions of motion. When the motion axis moves to a specific position and moves in a specific direction, the model or lookup table will output a corresponding compensation value. For the thermal deformation compensation amount, the real-time thermal expansion of key components such as the ball screw and bed can be calculated based on the machine tool's thermal model and real-time temperature data, and converted into the displacement compensation amount of the motion axis. For example, when the ball screw elongates by 10 micrometers due to temperature rise, the thermal deformation compensation amount is -10 micrometers to offset its elongation effect.

[0023] Next, based on the assessed degree of influence, the combination of mechanical wear compensation and thermal deformation compensation is adjusted, and these two amounts are then fused together to generate a motion command compensation value. For example, when the mechanical wear error is determined to have a high impact on machining accuracy, the weight of the mechanical wear compensation can be increased; when the thermal deformation error has a high impact, the weight of the thermal deformation compensation can be increased. The combination method can be a simple linear superposition or a complex fusion based on a nonlinear model. For example, if the mechanical wear compensation is M, the thermal deformation compensation is T, and the degree of influence is I, then the final motion command compensation value C can be expressed as C = wm M+wt T, where wm and wt are weighting coefficients dynamically adjusted according to the degree of influence I, and wm+wt=1.

[0024] Finally, the generated motion command compensation values ​​are continuously superimposed onto the original motion commands of the CNC system to achieve automatic precision adjustment control. For example, after receiving the original G-code or M-code commands, the CNC system adds the calculated motion command compensation values ​​to the original motion commands in real time before executing motion control. If the original command is to move to 100.000mm on the X-axis, and the compensation value is +0.005mm, then the actual motion command will become to move to 100.005mm on the X-axis. This superposition process is continuous, ensuring that the machine tool receives real-time error compensation throughout the entire machining process, thereby maintaining high-precision machining.

[0025] Optional, combined Figure 2 As shown, the steps of S2 to continuously identify the non-uniform mechanical wear error characteristics of the ball screw drive system and the thermal deformation error characteristics of the machine tool structure include: S21, monitor the sequence of machining instructions received by the CNC system and identify the switching points of machining parameters; S22, collects the current real-time operating status information of the machine tool; S23, the set of known wear characteristics of the ball screw; S24. Based on the set of processing parameter switching points, real-time operating status information, and known wear characteristics of the ball screw, determine the transient thermal gradient region formed inside the machine tool structure and its corresponding intensity. S25, estimate the modulation of the transient thermal gradient region on the known wear characteristics of the ball screw, and obtain the modulation estimation result; S26, Generate a forward-looking compensation curve based on the modulation estimation results; S27 superimposes the compensation amount from the forward compensation curve into the original motion command of the CNC system.

[0026] Specifically, in the process of continuously identifying the non-uniform mechanical wear error characteristics of the ball screw drive system and the thermal deformation error characteristics of the machine tool structure, it is first necessary to monitor the machining command sequence received by the CNC system to identify machining parameter switching points. The machining command sequence refers to a series of instructions received by the CNC system when executing a machining task. These instructions include key machining parameters such as tool path, feed rate, spindle speed, and depth of cut. Machining parameter switching points refer to the moments during machining when any one or more of the above machining parameters undergo significant changes. By identifying these switching points, it is possible to predict potential changes in the machine tool's operating state, such as increases or decreases in cutting load or changes in the rate of heat generation.

[0027] Simultaneously, it is necessary to collect real-time operating status information of the machine tool. This real-time operating status information may include, but is not limited to, the temperature of key components of the machine tool (e.g., spindle, ball screw, bed), vibration frequency, motor load, and the instantaneous position and speed of the moving axes. This information is acquired in real time through various sensors installed on the machine tool (e.g., temperature sensors, accelerometers, force sensors, encoders, etc.) to reflect the actual working condition of the machine tool at any given moment.

[0028] In addition, a set of known wear characteristics of ball screws needs to be maintained. This set stores typical wear characteristic data of ball screws under different operating conditions and wear stages, such as clearance, coefficient of friction, torque fluctuation range, and wear rate at specific temperatures or loads at different stroke positions. These characteristics can be established and updated through historical operating data, periodic diagnostic tests, or theoretical models, providing a benchmark for subsequent error characteristic identification.

[0029] Furthermore, based on the set of machining parameter switching points, real-time operating status information, and known wear characteristics of the ball screw, the transient thermal gradient regions formed within the machine tool structure and their corresponding intensities can be determined. When machining parameters change, such as a sudden increase in cutting speed or feed rate, more heat is generated in the cutting area. This heat diffuses within the machine tool structure through heat conduction and convection, forming local temperature differences, i.e., transient thermal gradients. Combining real-time operating status information (such as local temperature increases) and known wear characteristics (such as the material's thermal expansion coefficient), the location, extent, and rate and magnitude of temperature change of these transient thermal gradient regions, i.e., their corresponding intensities, can be accurately calculated using thermodynamic models or finite element analysis.

[0030] Based on this, it is necessary to estimate the modulation of the known wear characteristics of the ball screw by the transient thermal gradient region, and obtain the modulation estimation results. The transient thermal gradient causes thermal expansion or contraction of the ball screw and its supporting structure, thereby changing the preload, axial stiffness, lubricating oil film thickness, and the contact state between the balls and the nut. These changes "modulate" or alter the original wear characteristics of the ball screw; for example, under a specific thermal gradient, the wear rate may accelerate, or the wear mode may change. By establishing a thermo-mechanical coupling model, it is possible to predict how the known wear characteristics of the ball screw (such as position error and torque fluctuation) will be changed under a specific transient thermal gradient, thus obtaining the modulation estimation results.

[0031] Based on the modulation estimation results, a forward-looking compensation curve is generated. The forward-looking compensation curve is a predictive error compensation scheme that, based on the estimation of transient thermal gradient modulation effects, anticipates potential errors in the ball screw over a future period or along a specific machining path, and the corresponding compensation amounts. This curve can be represented as a function of the motion axis position error over time or stroke. Its purpose is to counteract these predicted errors by adjusting motion commands before they actually occur.

[0032] Finally, the compensation amount from the forward-looking compensation curve is continuously superimposed onto the original motion commands of the CNC system. This means that during the actual operation of the machine tool, the original motion commands issued by the CNC system are superimposed in real time with the compensation amount from the forward-looking compensation curve to form corrected motion commands. In this way, the machine tool's motion axes can move according to the corrected commands, thereby offsetting errors caused by non-uniform mechanical wear and thermal deformation in real time during the machining process.

[0033] Optionally, the steps for determining the transient thermal gradient region and its corresponding intensity formed inside the machine tool structure based on the set of machining parameter switching points, real-time operating status information, and known wear characteristics of the ball screw include: Based on the set of processing parameter switching points, real-time operating status information, and known wear characteristics of the ball screw, the thermal response analysis process is initiated. During the thermal response analysis, the heat transfer parameters are adjusted based on the geometric characteristics and material distribution of the workpiece being processed. Continuously monitor the temperature changes in the workpiece-tool contact area and along the main heat conduction path to obtain the temperature change rate in key areas; Based on the adjusted heat conduction parameters, the transient thermal gradient region and its corresponding intensity are determined according to the temperature change rate of the key area.

[0034] Furthermore, initiating the thermal response analysis process refers to the automatic or manual activation of a computational model or simulation program specifically designed to analyze the heat distribution and transfer within the machine tool when a machining parameter switching point is received or a significant change in real-time operating status information is detected. This process aims to simulate the thermal behavior of the machine tool under different operating conditions, providing fundamental data for subsequent determination of the thermal gradient.

[0035] In the thermal response analysis process, heat transfer parameters are adjusted based on the geometric characteristics and material distribution of the workpiece being processed. Specifically, the workpiece's geometric characteristics, such as size, shape, and surface area, as well as its material distribution, such as thermal conductivity, specific heat capacity, and density, all affect the efficiency of heat transfer within the workpiece and between the workpiece and the cutting tool and fixture. By acquiring this information in real time and inputting it into the thermal response analysis model, the heat transfer parameters in the model, such as thermal conductivity and convective heat transfer coefficient, can be dynamically corrected, thus making the thermal response analysis results closer to reality.

[0036] Furthermore, continuous monitoring of temperature changes in the workpiece-tool contact area and along the main heat conduction paths yields the temperature change rate in critical regions. Specifically, the workpiece-tool contact area is where heat generation and transfer are most concentrated, while the main heat conduction paths include key structural components such as the ball screw, spindle, and bed. By deploying high-precision temperature sensors, such as thermocouples and infrared thermometers, temperature data for these critical areas can be acquired in real time and continuously. Based on this temperature data, the temperature change rate for each region can be calculated, which is a crucial indicator for assessing the formation and development of transient thermal gradients.

[0037] Therefore, based on the adjusted heat conduction parameters and the rate of temperature change in key areas, the transient thermal gradient region and its corresponding intensity are determined. Specifically, in the thermal response analysis model, by combining the adjusted heat conduction parameters and the monitored rate of temperature change in key areas, the temperature gradient at different locations within the machine tool structure can be accurately calculated. The transient thermal gradient region refers to the area where the temperature gradient changes significantly, and its intensity indicates the drastic degree of temperature change. In this way, the transient thermal gradient formed during the machining process due to uneven heat accumulation and transfer, as well as its range and extent of influence, can be accurately identified.

[0038] Optionally, the steps for estimating the modulation of the transient thermal gradient region on the known wear characteristics of the ball screw, and obtaining the modulation estimation results, include: The parameters used to estimate the modulation are adjusted based on the duration or intensity of the transient thermal gradient in the transient thermal gradient region. When the duration or intensity of the transient thermal gradient exceeds a preset threshold, the nonlinear modulation analysis process is activated. Based on the adjusted parameters used for modulation estimation, the modulation of the transient thermal gradient region on the known wear characteristics of the ball screw is estimated, and the modulation estimation result is obtained. In the nonlinear modulation analysis, based on the wear state of the ball screw and the trend of wear characteristics change under transient thermal gradient in historical data, the estimated value of asymmetric deviation and the predicted value of torque fluctuation range in the modulation estimation results are corrected.

[0039] Specifically, "adjusting the parameters used to estimate modulation based on the duration or intensity of the transient thermal gradient in the transient thermal gradient region" means that when the duration or intensity of the transient thermal gradient region is long, its impact on the known wear characteristics of the ball screw becomes more significant and complex. Therefore, it is necessary to dynamically adjust the model parameters used for modulation estimation. For example, the weight of thermal effects in the modulation model can be increased, or the coefficients of nonlinear terms can be adjusted to more accurately reflect the influence of thermal deformation on mechanical wear characteristics. The aim is to enable the modulation estimation model to adapt to different degrees of thermal deformation influence.

[0040] The phrase "activating the nonlinear modulation analysis process when the duration or intensity of the transient thermal gradient exceeds a preset threshold" can be understood as follows: when the influence of the transient thermal gradient reaches a certain level (i.e., exceeds the preset threshold), traditional linear models may fail to accurately describe the complex coupling relationship between thermal deformation and mechanical wear. At this point, the system will automatically activate the nonlinear modulation analysis process to employ a more complex mathematical model (e.g., based on support vector machines or nonlinear regression models) to capture these nonlinear effects. The aim is to improve the estimation accuracy under extreme or complex thermal deformation conditions.

[0041] In practical applications, "in the nonlinear modulation analysis process, based on the wear state of the ball screw and the trend of wear characteristics changes under transient thermal gradients in historical data, the estimated values ​​of asymmetric deviation and the predicted values ​​of torque fluctuation range in the modulation estimation results are corrected." Specifically, the nonlinear modulation analysis process utilizes the current actual wear state data of the ball screw (e.g., position deviation, vibration spectrum, etc. collected by sensors) and historically accumulated data. Historical data contains the changing patterns of ball screw wear characteristics (such as asymmetric deviation and torque fluctuation) under different transient thermal gradients. By comparing and fusing the real-time wear state with historical trends, the estimated values ​​of asymmetric deviation and the predicted values ​​of torque fluctuation range in the modulation estimation results can be refined, thus obtaining modulation estimation results that are closer to the actual situation. The aim is to further improve the accuracy and reliability of modulation estimation, especially in predicting subtle changes in wear characteristics.

[0042] Optionally, the steps of adjusting the combination of mechanical wear compensation and thermal deformation compensation based on the degree of impact, and fusing the mechanical wear compensation and thermal deformation compensation based on the combination to generate motion command compensation values ​​include: Identify changes in processing parameters or workpiece material properties; Collect real-time operating status information of the machine tool; Assess the instantaneous intensity and trend of mechanical wear error and thermal deformation error; Based on the switching of processing parameters or workpiece material properties, real-time operating status information, instantaneous intensity and trend of mechanical wear error, and instantaneous intensity and trend of thermal deformation error, the dynamic coupling effect between mechanical wear error and thermal deformation error is inferred. Based on the dynamic coupling effect, the fusion weight and nonlinear combination relationship of mechanical wear compensation and thermal deformation compensation are adjusted; Based on the adjusted fusion weights and nonlinear combination relationships, the mechanical wear compensation and thermal deformation compensation are fused to generate motion command compensation values.

[0043] Specifically, identifying changes in machining parameters or workpiece material properties refers to the system's real-time monitoring of instructions in the CNC program, such as changes in parameters like spindle speed, feed rate, depth of cut, and tool type, or the identification of changes in the material properties (such as hardness and thermal conductivity) of the workpiece being machined through sensors. These switching points typically indicate significant changes in the internal stress and heat conditions of the machine tool, and are key triggering factors for dynamic coupling effects.

[0044] The acquisition of real-time operating status information of the machine tool can be understood as obtaining various physical quantities of the machine tool at the current moment, such as the position, speed, acceleration, spindle load, motor current, ambient temperature, and temperature of key components (such as ball screws and bearings). This information provides necessary contextual data for subsequent evaluation of the instantaneous state of errors and inference of coupling effects.

[0045] In practical applications, assessing the instantaneous intensity and trend of both mechanical wear error and thermal deformation error involves analyzing real-time acquired data. This includes using signal processing techniques (such as Fourier transform and wavelet analysis) to extract features like vibration and torque fluctuations, and combining this with historical data and models to quantify the current magnitude of mechanical wear error and its rate and direction of change over time. Simultaneously, by monitoring the temperature change rate and gradient of key components and using thermal deformation models, the instantaneous magnitude and evolution trend of thermal deformation error are assessed. The aim is to dynamically understand the current state and development trend of both types of errors.

[0046] Furthermore, based on the aforementioned switching of machining parameters or workpiece material properties, real-time operating status information, the instantaneous intensity and trend of mechanical wear error, and the instantaneous intensity and trend of thermal deformation error, the dynamic coupling effect between mechanical wear error and thermal deformation error is inferred. This can be understood as follows: when machining parameters or material properties change, the stress and heat state of the machine tool will change accordingly, thereby affecting the wear characteristics of the ball screw and the thermal deformation of the machine tool structure. For example, high cutting forces may accelerate wear and generate a large amount of heat, leading to thermal deformation; while thermal deformation may change the preload or lubrication state of the ball screw, which in turn affects wear. Inferring the dynamic coupling effect aims to quantify the degree and direction of this mutual influence.

[0047] Therefore, based on the inferred dynamic coupling effect, the fusion weights and nonlinear combination relationships of mechanical wear compensation and thermal deformation compensation are adjusted. This means that instead of using a fixed ratio or simple linear superposition, the weights of the two compensation quantities are dynamically allocated according to the strength and nature of the current coupling effect, and even nonlinear functions are introduced to more accurately describe their superposition relationship. For example, when thermal deformation has a significant impact on wear, the weight of thermal deformation compensation can be appropriately increased, and its nonlinear correction to wear compensation can be considered.

[0048] Finally, based on the adjusted fusion weights and nonlinear combination relationships, the mechanical wear compensation and thermal deformation compensation are fused to generate a motion command compensation value. This compensation value, which comprehensively considers the two errors and their dynamic coupling effects, is the final correction amount and will be superimposed on the original motion command of the CNC system.

[0049] Optionally, the steps for inferring the dynamic coupling effect between mechanical wear error and thermal deformation error include: Monitor the motion commands issued by the CNC system, identify emergency stop or acceleration points in the machining path, and determine whether the emergency stop or acceleration points are located in the known wear area of ​​the ball screw. When an emergency stop or rapid acceleration occurs at a point in the known wear zone of the ball screw, the instantaneous acceleration, vibration frequency, and impact torque data of the moving shaft are collected. Based on instantaneous acceleration, vibration frequency, and impact torque data, the transient impact effect of sudden stop or rapid acceleration on the ball screw is evaluated and quantified as transient impact characteristic values. Based on the switching of processing parameters or workpiece material properties, real-time operating status information, instantaneous intensity and trend of mechanical wear error, and instantaneous intensity and trend of thermal deformation error, the modulation effect of thermal deformation on the wear characteristics of ball screw is inferred and quantified into thermal modulation characteristic values. By comparing the transient impact characteristic value and the thermal modulation characteristic value, if the transient impact characteristic value is higher than the thermal modulation characteristic value, the current error is mainly attributed to the transient impact effect; otherwise, by combining the transient impact characteristic value and the thermal modulation characteristic value, the dynamic coupling effect between mechanical wear error and thermal deformation error is inferred.

[0050] Specifically, "monitoring motion commands issued by the CNC system, identifying emergency stop or acceleration points in the machining path, and determining whether these points are located within the known wear area of ​​the ball screw" refers to analyzing the G-codes or motion control command sequences output by the CNC system to detect in real time whether there are operations such as G00 (rapid positioning), M00 / M01 (program pause), or drastic changes in feed rate or spindle speed. Here, "emergency stop or acceleration points" specifically refer to the execution time or location of these commands that cause instantaneous and drastic changes in motion. "The known wear area of ​​the ball screw" refers to specific stroke segments on the ball screw that are highly worn or prone to wear, determined through historical data, preset models, or diagnostic procedures. Information about these areas is usually stored in the machine tool's maintenance database. Its purpose is to accurately capture critical operations that may cause significant transient effects and their locations.

[0051] The phrase "collecting instantaneous acceleration, vibration frequency, and impact torque data of the motion axis when a sudden stop or acceleration occurs within a known wear area of ​​the ball screw" refers to immediately initiating high-frequency data acquisition upon identifying a critical operation occurring within a known wear area. Specifically, "instantaneous acceleration" can be obtained using an acceleration sensor mounted on the motion axis; "vibration frequency" can be obtained using a vibration sensor combined with spectrum analysis technology; and "impact torque data" can be estimated by monitoring current or torque sensor data from the servo motor. The aim is to acquire direct, real-time dynamic response data of these transient operations on the mechanical system.

[0052] In practical applications, "evaluating the transient impact effect of sudden stops or accelerations on ball screws based on instantaneous acceleration, vibration frequency, and impact torque data, and quantifying it as transient impact characteristic values" refers to processing and analyzing the collected instantaneous acceleration, vibration frequency, and impact torque data to quantify the impact degree caused by these transient operations on the ball screw. The "transient impact effect" can be understood as short-term, high-amplitude mechanical stress, impact load, or vibration caused by sudden stops or accelerations. "Quantifying it as transient impact characteristic values" means integrating these multidimensional data into one or more values ​​representing the severity of the impact, such as peak acceleration, vibration energy, and maximum torque deviation, which can be achieved through statistical analysis, signal processing, or machine learning models. The purpose is to provide a comparable quantitative indicator for subsequent error attribution.

[0053] Furthermore, "inferring the modulation effect of thermal deformation on the wear characteristics of ball screws based on machining parameter switching or workpiece material characteristic switching, real-time operating status information, instantaneous intensity and trend of mechanical wear error, and instantaneous intensity and trend of thermal deformation error, and quantifying it as a thermal modulation characteristic value" refers to evaluating how thermal deformation affects the wear characteristics of ball screws based on the current operating status and error trend of the machine tool. The "modulation effect of thermal deformation on the wear characteristics of ball screws" can be understood as the influence of temperature changes, thermal expansion, or thermal gradients on wear-related parameters such as ball screw lubrication state, contact stress distribution, or material hardness. Quantifying this as a thermal modulation characteristic value typically involves correlating thermal deformation-related parameters (such as temperature and thermal gradient) with changes in wear characteristics (such as friction coefficient and wear rate) based on thermodynamic models, empirical formulas, or data-driven models to generate a numerical value representing the degree of thermal influence. Its purpose is to provide a quantitative index to measure the indirect impact of thermal deformation on mechanical wear.

[0054] Optionally, the steps of evaluating the transient impact effect of sudden stop or acceleration on the ball screw and quantifying it as a transient impact characteristic value include: Collect friction coefficient data and lubricating oil film thickness data for key parts of the ball screw; Based on friction coefficient data and lubricating oil film thickness data, identify whether there is an instantaneous change in lubrication state and obtain information on changes in lubrication state; Based on information on changes in lubrication conditions, the degree of influence on instantaneous acceleration, vibration frequency, and impact torque data is quantified. The influence of lubrication state changes on instantaneous acceleration, vibration frequency, and impact torque data is separated from the instantaneous acceleration, vibration frequency, and impact torque data to obtain the separated instantaneous acceleration, vibration frequency, and impact torque data. Based on the instantaneous acceleration, vibration frequency, and impact torque data after separation, the transient impact effect of sudden stop or rapid acceleration on the ball screw is evaluated and quantified as transient impact characteristic values.

[0055] The acquisition of friction coefficient and lubricating oil film thickness data from key components of the ball screw involves deploying miniature friction sensors, ultrasonic sensors, or capacitive sensors in critical areas such as easily worn areas, high-load areas, or areas with frequent start-stop cycles. This allows for the real-time or near-real-time acquisition of direct physical quantities reflecting the lubrication status. For example, friction sensors can measure the frictional force or coefficient between the balls and the screw, while capacitive sensors can measure the thickness of the lubricating oil film. These data provide direct evidence of whether the lubrication status has changed.

[0056] Furthermore, based on friction coefficient data and lubricating oil film thickness data, identifying whether a sudden change in lubrication state has occurred and obtaining lubrication state change information involves comparing the collected friction coefficient data and lubricating oil film thickness data with a preset normal operating baseline or historical data. When these data significantly deviate from the baseline, exceed safety thresholds, or exhibit abnormal fluctuation trends within a short period of time, it can be determined that a sudden change in lubrication state has occurred. For example, a sudden drop in lubricating oil film thickness below a critical value, or a sharp increase in the friction coefficient, can both be identified as a sudden change in lubrication state. From this, lubrication state change information containing details such as the type, degree, and timing of the change can be generated.

[0057] Specifically, quantifying the impact of changes in lubrication conditions on instantaneous acceleration, vibration frequency, and impact torque data involves analyzing and calculating the extent to which these changes affect the collected instantaneous acceleration, vibration frequency, and impact torque data, based on identified lubrication condition changes and through the establishment of physical, empirical, or data-driven models (such as regression analysis). For example, a 10% decrease in lubricating oil film thickness may lead to a 5% increase in vibration frequency and an 8% increase in impact torque. This quantification helps to accurately isolate the influence of lubrication factors from the raw data.

[0058] Based on this, the influence of lubrication state changes on instantaneous acceleration, vibration frequency, and impact torque data is separated from the instantaneous acceleration, vibration frequency, and impact torque data to obtain separated instantaneous acceleration, vibration frequency, and impact torque data. This involves using signal processing techniques (such as adaptive filtering and noise cancellation algorithms) or model compensation methods to subtract or remove the quantified influence of lubrication state from the original instantaneous acceleration, vibration frequency, and impact torque data. The aim is to obtain a set of "clean" data that more accurately reflects the mechanical impact experienced by the ball screw under sudden stop or acceleration operations, while eliminating interference from lubrication state changes.

[0059] Finally, based on the separated instantaneous acceleration, vibration frequency, and impact torque data, the transient impact effect of sudden stop or acceleration on the ball screw is evaluated and quantified as transient impact characteristic values. This means calculating characteristic values ​​that characterize the transient impact effect using the separated instantaneous acceleration, vibration frequency, and impact torque data. For example, the peak value, root mean square (RMS), energy spectral density, or vibration amplitude within a specific frequency range of these separated data can be calculated. These characteristic values ​​will more accurately reflect the actual mechanical impact intensity and characteristics experienced by the ball screw under sudden stop or acceleration operations.

[0060] Optionally, the steps for inferring the dynamic coupling effect between mechanical wear error and thermal deformation error include: Monitor the cumulative running time of the machine tool, and trigger the wear status adaptive update process when the cumulative running time reaches a preset threshold; After triggering the wear condition adaptive update process, the preset diagnostic path is executed under the no-load or low-load operation state of the machine tool to collect the position deviation, torque fluctuation and vibration spectrum data of the ball screw at different stroke positions and motion directions. Based on position deviation, torque fluctuation, and vibration spectrum data, identify the evolution characteristics of the current wear state of the ball screw; Update the set of known wear characteristics of the ball screw based on the evolution characteristics; When switching processing parameters or workpiece material properties, the machine tool's current real-time operating status information is collected; Based on the updated set of known wear characteristics of the ball screw, the switching of machining parameters or workpiece material properties, and real-time operating status information, we infer the modulation of the current wear state of the ball screw by thermal deformation, and the new dynamic coupling effect between the mechanical wear error and the thermal deformation error generated by the modulation.

[0061] Specifically, the cumulative operating time of a machine tool refers to the total operating time continuously recorded by the system since the machine tool was put into use. This time can be accumulated in units such as hours, days, or machining cycles. The preset threshold is a point in time determined based on experience, manufacturer recommendations, or historical data analysis. When the cumulative operating time reaches this threshold, it indicates that the machine tool may have entered a stage requiring reassessment of its wear condition, thus automatically triggering a wear condition adaptive update process. This process aims to periodically or under specific conditions reassess and recalibrate the wear condition of key machine tool components.

[0062] After triggering the wear condition adaptive update process, a preset diagnostic path is executed when the machine tool is running under no-load or low-load conditions. No-load or low-load operation refers to the state when the machine tool is not performing actual machining or only minor machining tasks. In this state, external interference is minimal, which is beneficial for accurately collecting internal mechanical condition data. The preset diagnostic path refers to a series of pre-programmed motion trajectories and test actions used to comprehensively test the performance of the ball screw, such as reciprocating motion and variable speed motion throughout the entire stroke range. During this process, position deviation, torque fluctuation, and vibration spectrum data of the ball screw at different stroke positions and in different directions of motion are collected. Position deviation data reflects the difference between the actual position and the commanded position of the ball screw at a specific location; torque fluctuation data reflects the change in the required driving torque of the ball screw during movement, indicating abnormalities such as friction and resistance; vibration spectrum data reveals the wear or damage of components such as bearings and nuts by analyzing the frequency components of the vibration signal.

[0063] Based on position deviation, torque fluctuation, and vibration spectrum data, the evolution characteristics of the current wear state of the ball screw are identified. This typically involves signal processing and feature extraction of the acquired data, such as using Fourier transform, wavelet analysis, and other methods to extract wear-related characteristic parameters from the raw data, such as vibration amplitude at a specific frequency and periodicity of torque fluctuation. Evolution characteristics refer to the trends of these parameters over time or operating conditions, such as increased clearance and friction due to wear.

[0064] Based on the evolution characteristics, the set of known wear characteristics for the ball screw is updated. This set of known wear characteristics is a database or model that stores typical characteristic parameters and behavioral patterns of the ball screw at different wear stages. By identifying the evolution characteristics, this set can be modified or supplemented to more accurately reflect the current actual wear state of the ball screw. For example, if a new wear pattern or increased wear is detected, the corresponding parameters or model in the set are updated.

[0065] When switching machining parameters or workpiece material properties, the machine tool's current real-time operating status information is collected. This is independent of the update process described above, but the collected real-time information will be used in conjunction with the updated wear characteristic set. Real-time operating status information includes, but is not limited to, spindle speed, feed rate, depth of cut, and ambient temperature.

[0066] Based on the updated set of known wear characteristics of the ball screw, changes in machining parameters or workpiece material properties, and real-time operating status information, this study infers the modulation of the current wear state of the ball screw by thermal deformation, and the new dynamic coupling effect between the mechanical wear error and the thermal deformation error resulting from this modulation. This means that when considering the impact of thermal deformation on mechanical wear, the study no longer relies solely on an initial or static wear model, but incorporates adaptively updated, more realistic wear characteristics. This modulation effect refers to how thermal deformation alters or exacerbates the mechanical wear characteristics of the ball screw; for example, high temperatures may lead to lubrication failure and material softening, thereby accelerating wear. The new dynamic coupling effect describes the specific ways and intensity of the interaction and mutual influence between mechanical wear error and thermal deformation error under this updated wear state.

[0067] Optionally, the steps for identifying the evolution characteristics of the current wear state of the ball screw based on position deviation, torque fluctuation, and vibration spectrum data include: Multi-scale feature extraction was performed on position deviation, torque fluctuation and vibration spectrum data to obtain wear characteristics at different frequencies and time scales; Wear characteristics are separated to distinguish between characteristics caused by a single wear mode and characteristics caused by a combined wear mode; The features caused by a single wear mode and the features caused by a combined wear mode are matched with a preset wear mode feature library to identify the evolution characteristics of the current wear state of the ball screw.

[0068] This study involves multi-scale feature extraction of position deviation, torque fluctuation, and vibration spectrum data to extract wear-related information from the raw data across different time scales and frequency ranges. For example, signal processing techniques such as wavelet transform, empirical mode decomposition (EMD), or Fourier transform can be used to analyze the energy distribution, amplitude variations, and phase information of the data at different frequency bands, thereby obtaining fine-grained features reflecting the degree, type, and location of wear. These features may include, but are not limited to, high-frequency vibration components, low-frequency drift trends, and intensity variations of specific harmonic components, each corresponding to the unique performance of the ball screw under different wear stages or mechanisms.

[0069] Furthermore, feature separation is performed on the wear characteristics to decouple the extracted complex wear features, distinguishing between features caused by a single wear mode (e.g., uniform wear, localized pitting, surface spalling, etc.) and composite wear features caused by the simultaneous action of multiple wear modes (e.g., coexistence of abrasive wear and fatigue wear). This step can be achieved through data dimensionality reduction and separation techniques such as Principal Component Analysis (PCA), Independent Component Analysis (ICA), or Non-negative Matrix Factorization (NMF) to improve the accuracy of subsequent wear mode identification. Feature separation avoids mutual interference between different wear modes, making the identification of each wear mode clearer and more independent.

[0070] Therefore, features caused by a single wear mode and features caused by a combined wear mode are matched with a pre-defined wear mode feature library. The purpose is to accurately identify the current wear state and its evolution trend of the ball screw by comparing it with feature templates of known wear modes. The pre-defined wear mode feature library is usually built based on a large amount of experimental data, simulation models, or expert experience, and contains feature fingerprints of various typical wear modes (such as early wear, intermediate wear, severe wear, etc.). The matching process can use machine learning algorithms, such as support vector machines (SVM), decision trees, or distance-based classifiers, to determine the best-matching wear mode by calculating the similarity or distance between the current feature and the features in the library, thereby identifying the evolution characteristics of the current wear state of the ball screw.

[0071] This application also discloses a precision automatic adjustment and control system for CNC machine tools, used to perform automatic precision adjustment and control of CNC machine tools, combined with... Figure 3 As shown, the CNC machine tool's precision automatic adjustment and control system 1 includes: The multi-dimensional information acquisition module 11 is used to collect multi-dimensional information about the machine tool's operating status; The feature recognition module 12 is used to continuously recognize the non-uniform mechanical wear error characteristics of the ball screw transmission system and the thermal deformation error characteristics of the machine tool structure based on multi-dimensional information. The influence degree judgment module 13 is used to continuously judge the influence degree of non-uniform mechanical wear error and thermal deformation error on the current machining accuracy based on the characteristics of non-uniform mechanical wear error and thermal deformation error. The compensation calculation module 14 is used to calculate the mechanical wear compensation amount related to the position and direction of motion of the motion axis based on the characteristics of non-uniform mechanical wear error; and to calculate the thermal deformation compensation amount related to the processing time based on the characteristics of thermal deformation error. The motion compensation generation module 15 is used to adjust the combination of mechanical wear compensation and thermal deformation compensation according to the degree of influence, and to merge the mechanical wear compensation and thermal deformation compensation based on the combination to generate motion command compensation value. The compensation superposition execution module 16 is used to continuously superimpose the motion command compensation value onto the original motion command of the CNC system in order to achieve automatic precision adjustment control.

[0072] A multi-dimensional information acquisition module is used to collect multi-dimensional information about the machine tool's operating status. Specifically, this module can consist of various sensors and data interfaces, such as temperature sensors, vibration sensors, displacement sensors, current and voltage sensors, encoders, and CNC system interfaces. These sensors and interfaces are configured in key parts of the machine tool, such as the ball screw support, spindle box, and bed, to acquire real-time data on the temperature, vibration frequency, relative displacement, machining parameters (such as feed rate, spindle speed, and depth of cut), and environmental parameters (such as ambient temperature and humidity) of various machine tool components. This data is collected by the module's data processing unit and undergoes preliminary data cleaning and preprocessing to ensure data accuracy and consistency. The specific methods for acquiring multi-dimensional information have been described in the above embodiments and will not be repeated here.

[0073] A feature recognition module is used to continuously identify the non-uniform mechanical wear error characteristics of the ball screw transmission system and the thermal deformation error characteristics of the machine tool structure based on multi-dimensional information. This module can consist of one or more processors, a memory, and a preset algorithm model. The processor is configured to receive data output from the multi-dimensional information acquisition module and run the preset algorithm model, such as a polynomial fitting algorithm or machine learning algorithm based on historical wear data models, to analyze the deviation between the encoder feedback data and the command position of the motion axis, thereby identifying the non-linear position error of the ball screw in a specific stroke segment, i.e., the non-uniform mechanical wear error characteristic. Simultaneously, this module is also configured to combine the machine tool's thermal model to calculate the thermal expansion and thermal deformation trends of key structural components of the machine tool (such as the bed, spindle box, and ball screw) in real time, thereby identifying the thermal deformation error characteristics. The specific identification method of the error characteristics has been described in the above embodiments and will not be repeated here.

[0074] The impact degree judgment module is used to continuously judge the impact degree of non-uniform mechanical wear error and thermal deformation error on the current machining accuracy based on the characteristics of non-uniform mechanical wear error and thermal deformation error. This module can consist of one or more processors and a memory, where the memory stores the error impact assessment model. The processor is configured to receive the error features output by the feature continuous recognition module and run the error impact assessment model, which can be implemented based on fuzzy logic or an expert system. This model comprehensively considers the instantaneous magnitude and rate of change of wear error and thermal deformation error, as well as the accuracy requirements of the current machining task, and outputs a quantified impact degree value. The specific method for judging the impact degree has been described in the above embodiments and will not be repeated here.

[0075] The compensation calculation module is used to calculate the mechanical wear compensation amount related to the position and direction of motion of the moving axis based on the non-uniform mechanical wear error characteristics; and to calculate the thermal deformation compensation amount related to the machining time based on the thermal deformation error characteristics. This module can consist of one or more processors and a memory, wherein the memory stores a model or lookup table for calculating the compensation amount. The processor is configured to receive the error characteristics output by the feature continuous identification module and calculate the mechanical wear compensation amount using a polynomial fitting model or lookup table based on historical wear data of the ball screw at different positions and in different directions of motion. Simultaneously, this module is also configured to calculate the real-time thermal expansion of key components such as the ball screw and bed based on the machine tool's thermal model and real-time temperature data, and convert it into the displacement compensation amount of the moving axis, i.e., the thermal deformation compensation amount. The specific calculation method for the compensation amount has been described in the above embodiments and will not be repeated here.

[0076] A motion compensation generation module is used to adjust the combination of mechanical wear compensation and thermal deformation compensation based on the degree of influence, and to fuse the mechanical wear compensation and thermal deformation compensation based on the combination method to generate motion command compensation values. This module can consist of one or more processors and a memory, where the memory stores algorithms for adjusting the combination method and fusing compensation amounts. The processor is configured to receive the degree of influence output by the degree of influence judgment module and the mechanical wear compensation and thermal deformation compensation amounts output by the compensation amount calculation module. Based on the determined degree of influence, this module is configured to dynamically adjust the fusion weights and nonlinear combination relationships of the mechanical wear compensation and thermal deformation compensation amounts. For example, when the degree of influence of mechanical wear error on machining accuracy is determined to be high, the weight of the mechanical wear compensation amount can be increased; when the degree of influence of thermal deformation error is high, the weight of the thermal deformation compensation amount can be increased. The combination method can be a simple linear superposition or a complex fusion based on a nonlinear model. Finally, this module generates motion command compensation values. The specific adjustment and fusion methods of the compensation amount combination method have been described in the above embodiments and will not be repeated here.

[0077] The compensation superposition execution module is used to continuously superimpose motion command compensation values ​​onto the original motion commands of the CNC system to achieve automatic precision adjustment control. This module can be implemented by the motion controller inside the CNC system or by a separate interface unit. This module is configured to receive motion command compensation values ​​output by the motion compensation generation module and, after the CNC system receives the original G-code or M-code commands, add the calculated motion command compensation values ​​to the original motion commands in real time before executing motion control. For example, if the original command is to move to 100.000mm on the X-axis, and the compensation value is +0.005mm, the actual motion command will become to move to 100.005mm on the X-axis. This superposition process is continuous, ensuring that the machine tool receives real-time error compensation throughout the entire machining process, thereby maintaining high-precision machining. The specific superposition method of motion command compensation values ​​has been described in the above embodiments and will not be repeated here.

[0078] The above are merely embodiments of this application and are not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for automatically adjusting and controlling the precision of a CNC machine tool, characterized in that, Includes the following steps: Collect multi-dimensional information on the machine tool's operating status; Based on the multi-dimensional information, the non-uniform mechanical wear error characteristics of the ball screw transmission system and the thermal deformation error characteristics of the machine tool structure are continuously identified. Based on the non-uniform mechanical wear error characteristics and the thermal deformation error characteristics, continuously determine the degree of influence of non-uniform mechanical wear error and thermal deformation error on the current machining accuracy; Based on the non-uniform mechanical wear error characteristics, calculate the mechanical wear compensation amount related to the position and direction of motion of the moving axis; based on the thermal deformation error characteristics, calculate the thermal deformation compensation amount related to the processing time. Based on the degree of influence, the combination of the mechanical wear compensation and the thermal deformation compensation is adjusted, and the mechanical wear compensation and the thermal deformation compensation are fused based on the combination to generate a motion command compensation value; The motion command compensation value is continuously superimposed on the original motion command of the CNC system to achieve automatic precision adjustment and control.

2. The method for automatic precision adjustment and control of a CNC machine tool according to claim 1, characterized in that, The steps for continuously identifying the non-uniform mechanical wear error characteristics of the ball screw transmission system and the thermal deformation error characteristics of the machine tool structure include: Monitor the sequence of machining instructions received by the CNC system and identify the switching points of machining parameters; Collect real-time operating status information of the machine tool; The set of known wear characteristics for maintaining ball screws; Based on the processing parameter switching points, the real-time operating status information, and the known wear characteristics of the ball screw, the transient thermal gradient region formed inside the machine tool structure and its corresponding intensity are determined. The modulation of the transient thermal gradient region on the known wear characteristics of the ball screw is estimated, and the modulation estimation result is obtained; Based on the modulation estimation results, a forward-looking compensation curve is generated; The compensation amount in the forward-looking compensation curve is superimposed on the original motion command of the CNC system.

3. The method for automatic precision adjustment and control of a CNC machine tool according to claim 2, characterized in that, The step of determining the transient thermal gradient region and its corresponding intensity formed inside the machine tool structure based on the processing parameter switching point, the real-time operating status information, and the known wear characteristics of the ball screw includes: Based on the processing parameter switching point, the real-time operating status information, and the known wear characteristics of the ball screw, the thermal response analysis process is initiated. During the thermal response analysis, the heat transfer parameters are adjusted based on the geometric characteristics and material distribution of the workpiece being processed. Continuously monitor the temperature changes in the workpiece-tool contact area and along the main heat conduction path to obtain the temperature change rate in key areas; Based on the adjusted heat conduction parameters, the transient thermal gradient region and its corresponding intensity are determined according to the temperature change rate of the key area.

4. The method for automatic precision adjustment and control of a CNC machine tool according to claim 2, characterized in that, The step of estimating the modulation of the transient thermal gradient region on the known wear characteristics of the ball screw, and obtaining the modulation estimation result, includes: The parameters used to estimate the modulation are adjusted based on the duration or intensity of the transient thermal gradient in the transient thermal gradient region. When the duration or intensity of the transient thermal gradient exceeds a preset threshold, the nonlinear modulation analysis process is activated. Based on the adjusted parameters used for modulation estimation, the modulation of the transient thermal gradient region on the known wear characteristics of the ball screw is estimated, and the modulation estimation result is obtained. In the nonlinear modulation analysis, based on the wear state of the ball screw and the trend of wear characteristics change under transient thermal gradient in historical data, the estimated value of asymmetric deviation and the predicted value of torque fluctuation range in the modulation estimation results are corrected.

5. The method for automatic precision adjustment and control of a CNC machine tool according to claim 1, characterized in that, The step of adjusting the combination of the mechanical wear compensation and the thermal deformation compensation based on the degree of influence, and fusing the mechanical wear compensation and the thermal deformation compensation based on the combination to generate a motion command compensation value includes: Identify changes in processing parameters or workpiece material properties; Collect real-time operating status information of the machine tool; Assess the instantaneous intensity and trend of mechanical wear error and thermal deformation error; Based on the switching of processing parameters or the switching of workpiece material properties, the real-time operating status information, the instantaneous intensity and trend of mechanical wear error, and the instantaneous intensity and trend of thermal deformation error, the dynamic coupling effect between the mechanical wear error and the thermal deformation error is inferred. Based on the dynamic coupling effect, the fusion weight and nonlinear combination relationship of the mechanical wear compensation and the thermal deformation compensation are adjusted. Based on the adjusted fusion weights and the nonlinear combination relationship, the mechanical wear compensation amount and the thermal deformation compensation amount are fused to generate motion command compensation values.

6. The method for automatic precision adjustment and control of a CNC machine tool according to claim 5, characterized in that, The step of inferring the dynamic coupling effect between the mechanical wear error and the thermal deformation error includes: Monitor the motion commands issued by the CNC system, identify emergency stop or acceleration points in the machining path, and determine whether the emergency stop or acceleration points are located in the known wear area of ​​the ball screw. When an emergency stop or rapid acceleration occurs at a point in the known wear zone of the ball screw, the instantaneous acceleration, vibration frequency, and impact torque data of the moving shaft are collected. Based on the instantaneous acceleration, vibration frequency, and impact torque data, the transient impact effect of sudden stop or rapid acceleration on the ball screw is evaluated and quantified as transient impact characteristic values. Based on the switching of processing parameters or the switching of workpiece material properties, the real-time operating status information, the instantaneous intensity and trend of mechanical wear error, and the instantaneous intensity and trend of thermal deformation error, the modulation effect of thermal deformation on the wear characteristics of ball screw is inferred and quantified as thermal modulation characteristic value. By comparing the transient impact characteristic value and the thermal modulation characteristic value, if the transient impact characteristic value is higher than the thermal modulation characteristic value, the current error is mainly attributed to the transient impact effect; otherwise, by combining the transient impact characteristic value and the thermal modulation characteristic value, the dynamic coupling effect between the mechanical wear error and the thermal deformation error is inferred.

7. The method for automatic precision adjustment and control of a CNC machine tool according to claim 6, characterized in that, The step of evaluating the transient impact effect of sudden stop or acceleration on the ball screw and quantifying it as a transient impact characteristic value includes: Collect friction coefficient data and lubricating oil film thickness data for key parts of the ball screw; Based on the friction coefficient data and the lubricating oil film thickness data, identify whether the lubrication state has undergone an instantaneous change, and obtain information on the change in lubrication state; Based on the information on changes in lubrication state, the degree of influence on the instantaneous acceleration, the vibration frequency, and the impact torque data is quantified; The degree of influence of the lubrication state change information on the instantaneous acceleration, vibration frequency, and impact torque data is separated from the instantaneous acceleration, vibration frequency, and impact torque data to obtain the separated instantaneous acceleration, vibration frequency, and impact torque data; Based on the instantaneous acceleration, vibration frequency, and impact torque data after separation, the transient impact effect of sudden stop or rapid acceleration on the ball screw is evaluated and quantified as transient impact characteristic values.

8. The method for automatic precision adjustment and control of a CNC machine tool according to claim 5, characterized in that, The step of inferring the dynamic coupling effect between the mechanical wear error and the thermal deformation error includes: Monitor the cumulative running time of the machine tool, and when the cumulative running time reaches a preset threshold, trigger the wear status adaptive update process; After triggering the wear state adaptive update process, the preset diagnostic path is executed under the no-load or low-load operation state of the machine tool to collect the position deviation, torque fluctuation and vibration spectrum data of the ball screw at different stroke positions and motion directions. Based on the position deviation, torque fluctuation, and vibration spectrum data, the evolution characteristics of the current wear state of the ball screw are identified; Update the set of known wear characteristics of the ball screw based on the aforementioned evolution characteristics; When switching processing parameters or workpiece material properties, the machine tool's current real-time operating status information is collected; Based on the updated set of known wear characteristics of the ball screw, the switching of processing parameters or the switching of workpiece material properties, and the real-time operating status information, the modulation of the current wear state of the ball screw by thermal deformation is inferred, as well as the new dynamic coupling effect between the mechanical wear error and the thermal deformation error generated by the modulation.

9. The method for automatic precision adjustment and control of a CNC machine tool according to claim 8, characterized in that, The step of identifying the evolution characteristics of the current wear state of the ball screw based on the position deviation, torque fluctuation, and vibration spectrum data includes: Multi-scale feature extraction is performed on the position deviation, torque fluctuation and vibration spectrum data to obtain wear characteristics at different frequencies and time scales; The wear characteristics are separated to distinguish between features caused by a single wear mode and features caused by a combined wear mode; The features caused by a single wear mode and the features caused by a combined wear mode are matched with a preset wear mode feature library to identify the evolution characteristics of the current wear state of the ball screw.

10. An automatic precision adjustment and control system for a CNC machine tool, used to perform automatic precision adjustment and control of the CNC machine tool, characterized in that, include: The multi-dimensional information acquisition module is used to collect multi-dimensional information about the machine tool's operating status. The feature recognition module is used to continuously recognize the non-uniform mechanical wear error characteristics of the ball screw transmission system and the thermal deformation error characteristics of the machine tool structure based on the multi-dimensional information. The influence degree judgment module is used to continuously judge the influence degree of non-uniform mechanical wear error and thermal deformation error on the current machining accuracy based on the non-uniform mechanical wear error characteristics and the thermal deformation error characteristics. The compensation calculation module is used to calculate the mechanical wear compensation amount related to the position and direction of motion of the moving axis based on the non-uniform mechanical wear error characteristics; and to calculate the thermal deformation compensation amount related to the processing time based on the thermal deformation error characteristics. The motion compensation generation module is used to adjust the combination of the mechanical wear compensation amount and the thermal deformation compensation amount according to the degree of influence, and to fuse the mechanical wear compensation amount and the thermal deformation compensation amount based on the combination to generate a motion command compensation value; The compensation superposition execution module is used to continuously superimpose the motion command compensation value onto the original motion command of the CNC system to achieve automatic precision adjustment and control.

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