Numerical control faceting machine

Abstract

The invention provides a numerical control faceting machine, which relates to the technical field of machining equipment and comprises a base, an X-axis assembly, a Z-axis assembly, a faceting cutter main shaft, a servo driving system and a numerical control controller. The numerical control faceting machine further comprises a temperature sensor array, and the temperature sensor array comprises ball screw pairs arranged on the base, the stand column, the X-axis and the Z-axis, a Z-axis servo motor and a plurality of temperature sensors arranged on the faceting tool main shaft. A model used for representing the mapping relation between the real-time temperature value of the temperature sensor array and the thermal error in the working space of the machine tool is pre-stored in the numerical control controller. In the machining process, the numerical control controller collects the temperature value in real time, the current prediction thermal error is calculated through the model, and coordinate instructions of the X axis and the Z axis are corrected according to the prediction thermal error. Machining errors caused by the heat effect can be actively counteracted, and the machining precision and stability of the numerical control faceting machine during long-time work are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of mechanical processing equipment, in particular to a numerical control pattern making machine. Background Art

[0002] CNC engraving machines are high-precision processing equipment widely used in industries such as jewelry, watches, and molds. Their core task is to perform intricate engraving on workpiece surfaces. To achieve high finishes and complex textures, the machine's spindle typically rotates at high speeds for extended periods, while the feed system also requires frequent, high-speed reciprocating motion.

[0003] During long periods of continuous operation, the core components of the equipment, such as high-speed spindles, servo motors, and transmission mechanisms such as ball screw pairs, will inevitably generate and accumulate a large amount of heat due to motor heating and mechanical friction. This heat is transmitted along the machine tool's structural components (such as the spindle, column, and base), causing them to experience uneven thermal expansion and deformation. This thermal deformation directly changes the precise spatial position of the tool tip relative to the workpiece, resulting in a machining error that changes dynamically over time and is difficult to predict. For batch processing, which requires micron-level precision and high consistency, this thermal error is the root cause of distorted machining patterns, inconsistent depth, and reduced product qualification rates.

[0004] Therefore, it is necessary to improve the existing CNC batching equipment to overcome the defects of the prior art. Summary of the Invention

[0005] In order to overcome the problems existing in the related art, the purpose of the present invention is to provide a CNC pattern cutting machine, which sets a temperature sensor array at the key thermal sensitive position of the machine tool, and combines real-time thermal error prediction and compensation control based on a pre-stored mapping relationship model to overcome the processing error problem existing in the prior art caused by the relative position of the tool and the workpiece being offset due to thermal deformation of various components of the machine tool.

[0006] A CNC cutting machine comprises a base, an X-axis assembly mounted on the base and movable in a horizontal direction, a workbench provided on the X-axis assembly, a column fixed to the base, a Z-axis assembly mounted on the column and movable in a vertical direction, a cutting tool spindle mounted on the Z-axis assembly, a servo drive system for driving the X-axis assembly and the Z-axis assembly, and a CNC controller;

[0007] The X-axis assembly includes an X-axis servo motor, an X-axis ball screw pair driven by the X-axis servo motor, and an X-axis slide fixedly connected to the X-axis ball screw pair, and the workbench is fixedly connected to the X-axis slide;

[0008] The Z-axis assembly includes a Z-axis servo motor, a Z-axis ball screw pair driven by the Z-axis servo motor, and a Z-axis slide fixedly connected to the Z-axis ball screw pair, and the batching tool spindle is fixedly connected to the Z-axis slide;

[0009] The CNC cutting machine further includes a temperature sensor array, which includes a first temperature sensor provided on the base, a second temperature sensor provided on the column, a third temperature sensor provided on the X-axis ball screw pair, a fourth temperature sensor provided on the Z-axis ball screw pair, a fifth temperature sensor provided on the Z-axis servo motor, and a sixth temperature sensor provided on the cutting tool spindle;

[0010] The CNC controller is configured to:

[0011] Pre-storing a mapping relationship model for characterizing the real-time temperature value of the temperature sensor array and the thermal error in the working space;

[0012] During the batch processing, the temperature value of the temperature sensor array is collected in real time, and the real-time predicted thermal error is calculated based on the mapping relationship model;

[0013] The coordinate instructions of the X-axis component and the Z-axis component are corrected in real time according to the predicted thermal error to compensate for the processing error caused by thermal deformation.

[0014] Furthermore, the mapping relationship model is a multivariate polynomial regression model.

[0015] The thermal deformation process of machine tools is not a simple linear relationship, but a complex nonlinear process driven by the combined effects of multiple heat sources. The multivariate polynomial regression model effectively fits this nonlinear relationship. Its computational process is deterministic and relatively computationally efficient, making it suitable for efficient operation in resource-limited real-time CNC controllers. Compared to complex and difficult-to-verify black-box models (such as neural networks), this model not only ensures high-precision prediction of thermal errors, but also ensures stable compensation and reduces the computing power requirements of the controller.

[0016] Furthermore, the multivariate polynomial regression model is a second-order polynomial regression model, which includes linear and interactive influence terms of each temperature value of the temperature sensor array.

[0017] The linear terms in the model characterize the direct, independent impact of a single heat source (such as spindle heating) on ​​the error; the interaction terms capture the coupled effects between different heat sources, such as the complex influence of spindle heating and column temperature on the final Z-axis deformation. By introducing the interaction terms, the real, multi-physics thermal deformation of the machine tool can be more accurately described than a simple first-order linear model, thereby improving the accuracy of thermal error prediction.

[0018] Furthermore, the mapping relationship model is established through an offline modeling process, and the offline modeling process includes the following steps:

[0019] Under a controlled environment, the CNC cutting machine is operated from a cold state to a thermally stable state;

[0020] During operation, a temperature value sequence of the temperature sensor array and a corresponding spatial thermal error sequence measured by an external laser interferometer are synchronously collected;

[0021] Based on the collected temperature value sequence and the thermal error sequence, the mapping relationship model is fitted through a regression analysis algorithm.

[0022] By running the batching machine from cold to a thermally stable state, while simultaneously collecting its own temperature data and actual thermal error data measured by high-precision external instruments, the model established is not a general theoretical model, but rather a customized model tailored to the structure, assembly, and material properties of this specific machine tool. This offline modeling process ensures the correspondence between the model and the actual machine tool, improving the model's predictive accuracy and reliability in actual application on the batching machine.

[0023] Furthermore, the third temperature sensor is specifically arranged on the nut seat of the X-axis ball screw pair;

[0024] The fourth temperature sensor is specifically arranged on the nut seat of the Z-axis ball screw pair;

[0025] The sixth temperature sensor is specifically arranged on the front end cover of the trimming tool spindle.

[0026] The nut housing is the component in the screw drive where frictional heat generation is most concentrated, while the spindle front cover, located closest to the front bearing, is the most direct point of thermal expansion. The sensor can capture changes in the core heat source that most impacts positioning accuracy with minimal latency and maximum relevance, ensuring the timeliness of input data and improving compensation response speed and accuracy.

[0027] Furthermore, the numerical control controller is configured to perform temperature acquisition, thermal error calculation and coordinate instruction correction in a preset time period.

[0028] Thermal deformation of machine tools is a relatively slow physical process, with a frequency far lower than that of servo control. Setting an execution cycle ensures that the compensation value updates quickly enough to keep pace with thermal drift while also avoiding unnecessary, high-frequency computational overhead on the controller. While ensuring effective thermal compensation, this optimizes control resource allocation, freeing up computing power for more critical tasks such as path interpolation and servo control.

[0029] Furthermore, the CNC cutting machine also includes a PID controller;

[0030] The numerical control controller is further configured to perform adaptive feed control, including:

[0031] Acquire the load signal of the X-axis servo motor or the Z-axis servo motor in real time;

[0032] calculating a net cutting load according to the load signal;

[0033] Comparing the net cutting load with a preset ideal load target value, and calculating a feed rate adjustment coefficient by the PID controller;

[0034] The target feed rate is adjusted using the feed rate adjustment factor.

[0035] By monitoring the cutting load in real time and dynamically adjusting the feed rate using a PID controller, the system automatically increases the feed when the cutting allowance is small and automatically reduces the feed when the allowance is large, so that the cutting process is always carried out under the set ideal load. This shortens the processing time by maximizing the material removal rate and protects the cutting tool by avoiding overload.

[0036] Furthermore, the numerical control controller pre-stores a lookup table recording no-load friction load values ​​of the servo motor at different speeds;

[0037] The net cutting load is obtained by subtracting the no-load friction load value at the corresponding speed found in the lookup table from the load signal acquired in real time.

[0038] The total load on a servo motor is the sum of the cutting load and the friction load, which varies with speed. By pre-calibrating and storing a lookup table, the controller can remove the interference of the friction load based on the current speed during real-time calculations. This ensures that the input signal used by the PID controller is the net cutting load, allowing feed rate adjustments to be based entirely on the actual cutting conditions, avoiding misjudgments caused by changes in friction and improving the accuracy and stability of adaptive control.

[0039] Furthermore, the numerical control controller is further configured to:

[0040] monitoring the magnitude of the predicted thermal error or its rate of change;

[0041] When the magnitude of the predicted thermal error or its rate of change exceeds a preset stability threshold, the preset ideal load target value is lowered to suppress the temperature rise rate of the machine tool.

[0042] When the thermal error or its rate of change exceeds a threshold, indicating runaway heat in the machine tool, the system moves beyond passive compensation and proactively reduces the target load. This enables the PID controller to automatically reduce machining intensity, thereby reducing heat generation at the source. This effectively prevents the machine tool from entering a state of thermal instability, ensuring stability during long-term, high-intensity machining.

[0043] Furthermore, the numerical control controller is further configured to execute a preheating program;

[0044] The preheating procedure includes:

[0045] The machine tool is driven to execute a preset no-load or light-load motion sequence, and the predicted thermal error is continuously calculated through the mapping relationship model during the process. Preheating is completed when the stability of the predicted thermal error changes less than a preset stability threshold within a predetermined time.

[0046] Leveraging an established thermal error mapping model, the thermal stability of the machine tool is determined by real-time calculation of the predicted rate of change of thermal error. A sufficiently low rate of change indicates that the temperatures of the machine tool components have reached equilibrium. By transforming the preheating process from a time-based control to a dynamic, closed-loop state-based control system, the machine tool is in an optimal, predictable thermal state at the start of each formal machining operation. Preheating time is optimized based on the actual environment and the machine tool's initial state, improving overall equipment efficiency.

[0047] The beneficial effects of the present invention are:

[0048] The present invention provides a CNC cutting machine, which can capture the temperature of the entire machine in real time and in multiple dimensions when it is working by arranging temperature sensor arrays on the core heat source and key structural parts of the machine tool, including the base, column, X / Z axis ball screw pair, Z axis motor and cutting tool spindle. Comprehensive monitoring of the thermal state of the entire structural transmission chain that affects the final processing accuracy. A mapping relationship model is pre-stored in the CNC controller, and the multi-point real-time temperature values ​​collected in the first step are used as input. Through mathematical operations, it can be calculated how much spatial error these temperature distributions will cause the tool tip to produce in the working space at the current moment. After obtaining the predicted thermal error value, the CNC controller performs real-time correction operations on the coordinate instructions before issuing motion instructions to the servo system. It can reduce the interference of thermal deformation on the processing trajectory and ensure the processing accuracy during long-term continuous processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the CNC batching machine provided in this application;

[0050] Figure 2 It is a schematic diagram of the Z-axis assembly of the CNC flower batching machine provided in this application;

[0051] Figure 3 This is a schematic diagram of the Z-axis assembly of the CNC cutting machine provided in this application after removing the cutting tool spindle and the Z-axis slide;

[0052] Figure 4 This is a schematic diagram of the X-axis assembly provided in this application after removing the X-axis slide;

[0053] Figure 5 is a side view of the X-axis assembly provided in this application.

[0054] Reference numerals:

[0055] 100, base;

[0056] 200, pillar;

[0057] 300, X-axis assembly; 310, X-axis servo motor; 320, X-axis ball screw pair; 330, X-axis slide;

[0058] 400, workbench;

[0059] 500, Z-axis assembly; 510, Z-axis servo motor; 520, Z-axis ball screw pair; 530, Z-axis slide;

[0060] 600, batching tool spindle;

[0061] 710 , first temperature sensor; 720 , second temperature sensor; 730 , third temperature sensor; 740 , fourth temperature sensor; 750 , fifth temperature sensor; 760 , sixth temperature sensor. DETAILED DESCRIPTION

[0062] The preferred embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although preferred embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. Rather, these embodiments are provided to make the present invention more thorough and complete and to fully convey the scope of the present invention to those skilled in the art.

[0063] Example

[0064] like Figures 1 to 5As shown, this embodiment provides a CNC batching machine, which includes a base 100 serving as the foundation of the entire machine, an X-axis assembly 300 movable in the horizontal X direction on the base 100, and a rigid column 200 fixed to the base 100. A workbench 400 for fixing a workpiece is mounted on the X-axis assembly 300. A Z-axis assembly 500 movable in the vertical Z direction is mounted on the column 200. A batching tool spindle 600 is mounted on the Z-axis assembly 500, and a processing tool is mounted at the front end of the batching tool spindle 600, which processes the workpiece on the workbench 400.

[0065] Specifically, the X-axis assembly 300 includes an X-axis servo motor 310 and an X-axis ball screw assembly 320 driven by the motor. The ball screw assembly's nut is fixedly connected to an X-axis slide 330, upon which the worktable 400 is mounted. Similarly, the Z-axis assembly 500 also includes a Z-axis servo motor 510, a Z-axis ball screw assembly 520, and a Z-axis slide 530, upon which the cutter spindle 600 is ultimately secured.

[0066] The movement of the entire machine is centrally controlled by a CNC controller, which sends instructions to the servo motors of the X and Z axes and receives feedback signals through the servo drive system.

[0067] The CNC batching machine also includes a temperature sensor array to fully sense the thermal status of the machine tool. The temperature sensor array includes:

[0068] The first temperature sensor 710, mounted on the thick casting of the base 100, away from any direct heat source, is used to measure the overall reference temperature of the machine tool.

[0069] The second temperature sensor 720 is installed in the middle of the column 200 and is used to monitor the overall temperature rise and thermal deformation trend of the column 200 as a Z-axis movement reference.

[0070] The third temperature sensor 730 is mounted on the nut seat of the X-axis ball screw pair 320. This is the main friction heat source of the X-axis transmission chain, and its temperature is directly related to the thermal expansion of the X-axis screw.

[0071] The fourth temperature sensor 740 is mounted on the nut seat of the Z-axis ball screw pair 520. Similarly, this is the core heat source of the Z-axis transmission chain.

[0072] The fifth temperature sensor 750 is mounted on the housing of the Z-axis servo motor 510 and is used to monitor the heating condition of the Z-axis drive unit.

[0073] The sixth temperature sensor 760 is mounted on the front cover of the cutting tool spindle 600, near the front bearing. This is the largest heat source in the entire machine, causing significant thermal expansion of the spindle and being the most critical factor affecting Z-axis accuracy.

[0074] The specific locations of the third temperature sensor 730, the fourth temperature sensor 740 and the sixth temperature sensor 760 are selected based on a layout of heat source analysis. The third temperature sensor 730 and the fourth temperature sensor 740 directly monitor the friction heat of the transmission chain, and the sixth temperature sensor 760 directly monitors the heat generated by the high-speed rotation of the main shaft. These are the most direct and critical sources of thermal errors.

[0075] One of the core functions of a CNC controller is to perform thermal error compensation, which has a pre-stored mapping relationship model.

[0076] In this embodiment, the mapping relationship model is a second-order multivariate polynomial regression model. This model can accurately characterize the nonlinear relationship between the six temperature sensor readings (T1, T2, T3, T4, T5, T6) and the thermal errors (ΔX, ΔZ) of the tool tip in the X and Z directions:

[0077] ΔX=c0+Σ(c i ×T i )+Σ(d ij ×T i ×T j )

[0078] ΔZ=g0+Σ(g i ×T i )+Σ(h ij ×T i ×T j )

[0079] The values ​​of i and j are both integers ranging from 1 to 6, corresponding to the first temperature sensor 710 , the second temperature sensor 720 , the third temperature sensor 730 , the fourth temperature sensor 740 , the fifth temperature sensor 750 , and the sixth temperature sensor 760 .

[0080] In ΔX=c0+Σ(c i ×T i )+Σ(d ij ×T i ×T j ), ΔX represents the X-axis position error of the tool tip relative to the worktable, as predicted by the CNC controller under the current thermal state. The unit is microns. This value is the final result calculated by the model.

[0081] c0 is a constant term that represents the inherent systematic deviation of the system when all temperature sensors theoretically read the reference zero temperature during modeling. It represents the initial position error of the machine tool in the reference state.

[0082] Σ(c i ×T i ) is the independent, linear effect of each temperature sensor reading change on the X-axis thermal error. i Represents the real-time temperature reading of the i-th temperature sensor. For example, T1 is the value of the first temperature sensor, and T6 is the value of the sixth temperature sensor. i Indicates the linear effect of each unit temperature increase (e.g., 1 degree Celsius) of the i-th temperature sensor on the X-axis thermal error ΔX. For example, if c3 = 0.2, it means that each 1°C increase in the temperature of the X-axis screw nut seat (T3) will cause a 0.2μm thermal error in the X-axis. Coefficient c i The sign of represents the direction of the effect (positive or negative error).

[0083] Σ(d ij ×T i ×T j ) represents the nonlinear effect produced by the interaction of different temperature points, that is, the temperature change of one point may change the effect of the temperature of another point on the total error.

[0084] T i ×T j is the interaction term of temperature. When i=j, this term is T i 2 (Temperature squared term). Indicates the nonlinear (acceleration or deceleration) effect on thermal error caused by an increase in the temperature of the i-th temperature point itself.

[0085] When i≠j, this term is T i ×T j (Temperature product term). This term represents the coupled or synergistic effect that occurs when the i-th and j-th temperatures change simultaneously. For example, if heat from the spindle (T6) heats column 200 (T2), the term T2 × T6 captures the combined deformation effect of one heat source on another structural component, an effect that cannot be fully described by the linear terms of T2 and T6 alone.

[0086] d ij is a constant term that indicates the strength and direction of the above interaction effect.

[0087] ΔZ of the Z axis=g0+Σ(g i ×T i )+Σ(h ij ×T i ×Tj The meaning of each item in ) can be determined by referring to the meaning of the X-axis.

[0088] The coefficients (c i 、g i d ij 、h ij ) is established through an offline modeling process, which is as follows:

[0089] A laser interferometer is installed on the machine tool table as an external measuring instrument to accurately measure the position of the tool tip in the X and Z directions;

[0090] In a controlled constant temperature workshop, the CNC batching machine is started from a cold state to execute a program simulating typical processing (such as the spindle rotates at 8000 rpm and the X / Z axis reciprocates at a medium speed), and continues to run until the thermal state is basically stable;

[0091] During operation, six readings (T1...T6) from the temperature sensor array and the X- and Z-direction spatial thermal errors (ΔX, ΔZ) measured by the laser interferometer were synchronously recorded every 5 minutes;

[0092] The collected data sets were imported into statistical analysis software and regression analysis was performed using the least squares method to calculate the (c i 、g i d ij 、h ij );

[0093] The finalized model and its coefficients are stored in the CNC controller.

[0094] During the actual batch processing process, the CNC controller performs compensation tasks in the background at a preset time interval (for example, 10 seconds), collecting temperature values ​​from T1 to T6 in real time. These six temperature values ​​are substituted into a solidified second-order regression model to calculate the current predicted thermal error. The CNC controller then corrects this error before issuing the final coordinate command to the servo system.

[0095] To further improve efficiency, the CNC controller also integrates an adaptive feed control module, the core of which is a PID controller.

[0096] The CNC controller obtains the current value of the X-axis servo motor 310 or the Z-axis servo motor 510 (depending on the current main cutting motion axis) in real time through the high-speed bus. The current value is proportional to the total load output by the motor.

[0097] A lookup table corresponding to each servo motor is pre-stored in the controller. The lookup table records the no-load friction load values ​​of the X-axis servo motor 310 and the Z-axis servo motor 510 at different speeds.

[0098] The net cutting load is equal to the total load minus the friction load corresponding to the current speed found in the lookup table.

[0099] The PID controller compares the calculated net cutting load with the ideal load target value set by the operator and calculates a feed rate adjustment factor k (range between 0.5-1.5).

[0100] The current target feed rate is adjusted according to the coefficient k, so that the final actual feed rate can be dynamically optimized.

[0101] The CNC controller not only performs compensation, but also monitors the size of the predicted thermal error or its rate of change. For example, when the CNC controller detects that the rate of change of the predicted thermal error in the Z direction has exceeded the preset stability threshold (such as 0.5μm / min) in the last minute, it indicates that the machine tool is in a stage of rapid temperature rise. At this time, the CNC controller will automatically temporarily lower the ideal load target value in the adaptive feed control module from 70% to 50%, so that the adaptive feed control module automatically reduces the processing feed rate and reduces the cutting force, thereby reducing the heat generation power of the machine tool, actively suppressing the temperature rise rate of the machine tool, giving priority to ensuring thermal stability, and then restoring the ideal load after the thermal change rate drops.

[0102] In order to better control the thermal performance of the CNC batch machine, the CNC batch machine can be preheated by executing the preheating program before processing. When executing the preheating program, the CNC controller controls the CNC batch machine to execute a set of preset no-load or light-load motion sequences (such as the spindle rotating at medium speed, and each axis reciprocating within the full stroke). During this process, the predicted thermal error is continuously calculated. The CNC controller monitors the stability of the predicted thermal error. For example, when the change in the predicted thermal error in the Z direction is lower than the preset stability threshold within 3 consecutive minutes, the system determines that the machine tool has reached a thermally stable state and prompts "Preheating is complete, and precision processing can begin" on the human-computer interaction interface. Compared with traditional fixed-time preheating, it is more efficient and reliable.

[0103] Unless otherwise specifically stated, the relative arrangement, numerical expression and numerical value of the parts and steps set forth in these embodiments do not limit the scope of the application. In all examples shown and discussed here, any specific value should be interpreted as merely exemplary, rather than as a restriction. Therefore, other examples of exemplary embodiments can have different values. It should be noted that: similar reference numerals and letters represent similar items in the accompanying drawings below, and therefore, once a certain item is defined in an accompanying drawing, it does not need to be further discussed in the accompanying drawings subsequently.

[0104] In addition, it should be noted that the use of terms such as "first" and "second" for limitation is only for the convenience of distinction. Unless otherwise stated, the above terms have no special meaning and therefore cannot be understood as limiting the scope of protection of this application.

[0105] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A CNC batching machine, characterized in that: The invention comprises a base (100), an X-axis assembly (300) mounted on the base (100) and movable in a horizontal direction, a workbench (400) arranged on the X-axis assembly (300), a column (200) fixed on the base (100), a Z-axis assembly (500) mounted on the column (200) and movable in a vertical direction, a cutting tool spindle (600) mounted on the Z-axis assembly (500), a servo drive system for driving the X-axis assembly (300) and the Z-axis assembly (500), and a numerical control controller; The X-axis assembly (300) comprises an X-axis servo motor (310), an X-axis ball screw pair (320) driven by the X-axis servo motor (310), and an X-axis slide (330) fixedly connected to the X-axis ball screw pair (320); the workbench (400) is fixedly connected to the X-axis slide (330); The Z-axis assembly (500) comprises a Z-axis servo motor (510), a Z-axis ball screw pair (520) driven by the Z-axis servo motor (510), and a Z-axis slide (530) fixedly connected to the Z-axis ball screw pair (520); the pattern cutting tool spindle (600) is fixedly connected to the Z-axis slide (530); The CNC cutting machine further comprises a temperature sensor array, the temperature sensor array comprising a first temperature sensor (710) provided on the base (100), a second temperature sensor (720) provided on the column (200), a third temperature sensor (730) provided on the X-axis ball screw pair (320), a fourth temperature sensor (740) provided on the Z-axis ball screw pair (520), a fifth temperature sensor (750) provided on the Z-axis servo motor (510), and a sixth temperature sensor (760) provided on the cutting tool spindle (600); The CNC controller is configured to: Pre-storing a mapping relationship model for characterizing the real-time temperature value of the temperature sensor array and the thermal error in the working space; During the batch processing, the temperature value of the temperature sensor array is collected in real time, and the real-time predicted thermal error is calculated based on the mapping relationship model; The coordinate instructions of the X-axis component (300) and the Z-axis component (500) are corrected in real time according to the predicted thermal error to compensate for the processing error caused by thermal deformation.

2. The CNC cutting machine according to claim 1, characterized in that: The mapping relationship model is a multivariate polynomial regression model.

3. The CNC cutting machine according to claim 2, characterized in that: The multivariate polynomial regression model is a second-order polynomial regression model, which includes linear and interactive influence terms of each temperature value of the temperature sensor array.

4. The CNC cutting machine according to claim 1, characterized in that: The mapping relationship model is established through an offline modeling process, which includes the following steps: Under a controlled environment, the CNC cutting machine is operated from a cold state to a thermally stable state; During operation, a temperature value sequence of the temperature sensor array and a corresponding spatial thermal error sequence measured by an external laser interferometer are synchronously collected; Based on the collected temperature value sequence and the thermal error sequence, the mapping relationship model is fitted through a regression analysis algorithm.

5. The CNC cutting machine according to claim 1, characterized in that: The third temperature sensor (730) is specifically arranged on the nut seat of the X-axis ball screw pair (320); The fourth temperature sensor (740) is specifically arranged on the nut seat of the Z-axis ball screw pair (520); The sixth temperature sensor (760) is specifically arranged on the front end cover of the cutting tool spindle (600).

6. The CNC cutting machine according to claim 1, characterized in that: The numerical control controller is configured to perform temperature acquisition, thermal error calculation and coordinate instruction correction in a preset time period.

7. The CNC cutting machine according to claim 1, characterized in that: The numerical control batching machine also includes a PID controller; The numerical control controller is further configured to perform adaptive feed control, including: Acquiring a load signal of the X-axis servo motor (310) or the Z-axis servo motor (510) in real time; calculating a net cutting load according to the load signal; Comparing the net cutting load with a preset ideal load target value, and calculating a feed rate adjustment coefficient by the PID controller; The target feed rate is adjusted using the feed rate adjustment factor.

8. The CNC crimping machine according to claim 7, characterized in that: The numerical control controller pre-stores a lookup table recording no-load friction load values ​​of the servo motor at different speeds; The net cutting load is obtained by subtracting the no-load friction load value at the corresponding speed found in the lookup table from the load signal acquired in real time.

9. The CNC cutting machine according to claim 7, characterized in that: The numerical control controller is further configured to: monitoring the magnitude of the predicted thermal error or its rate of change; When the magnitude of the predicted thermal error or its rate of change exceeds a preset stability threshold, the preset ideal load target value is lowered to suppress the temperature rise rate of the machine tool.

10. The CNC cutting machine according to claim 1, characterized in that: The CNC controller is further configured to execute a preheating procedure; The preheating procedure includes: The machine tool is driven to execute a preset no-load or light-load motion sequence, and the predicted thermal error is continuously calculated through the mapping relationship model during the process. Preheating is completed when the stability of the predicted thermal error changes less than a preset stability threshold within a predetermined time.

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