Intelligent multi-axis synchronous control system and method for aluminum material machining numerical control machine tool

Abstract

The invention belongs to the field of machine tool production control, and particularly relates to an intelligent multi-axis synchronous control system and method for an aluminum material machining numerical control machine tool, the system integrates an intelligent sensing module, an error compensation module, a machining control module and an interaction module, and the intelligent sensing module monitors and preprocesses multi-axis working state data in real time through an integrated sensor; the error compensation module utilizes an error monitoring unit and an error compensation unit to predict and dynamically compensate multi-axis errors based on an error model, and the machining control module achieves accurate synchronous control of a workpiece and a cutter through three-dimensional modeling, machining track generation and feedback adjustment. The interaction module provides visual display of the processing progress and real-time monitoring and early warning of faults; the machining precision and efficiency of the five-axis numerical control machine tool on the aluminum material are effectively improved, and the intelligence and stability of the machining process are enhanced.

Description

Technical Field

[0001] The invention belongs to the field of machine tool production control, and in particular relates to an intelligent multi-axis synchronous control system and method for a numerically controlled machine tool for aluminum material processing. Background Art

[0002] In modern manufacturing, aluminum is widely used due to its light weight, high strength and good corrosion resistance, especially in the fields of aerospace, automobile manufacturing, electronic equipment, etc., which have extremely high requirements for the precision and efficiency of aluminum processing. Five-axis CNC machine tools, as an important processing tool, can achieve precision processing of aluminum. However, due to the special properties of aluminum and the demand for complex shapes, traditional CNC machine tools face many challenges in the processing process. For example, existing methods usually use post-error compensation, but post-error compensation will lead to error accumulation and reduce processing accuracy. The existing pre-error prediction compensation method can solve the error accumulation, but it is difficult to control the order of error compensation of each axis and the compensation error accuracy, resulting in the problem of asynchronous processing of each processing axis.

[0003] For example, the patent with authorization announcement number CN110018669B discloses a decoupled contour error control method for a five-axis CNC machine tool, including: first, calculating the contour error vector and the tangential tracking error vector through an online five-axis contour error estimation method; then, designing a stable normal contour error controller for each drive axis, with the contour error vector as input and the normal contour error control component of each axis as output; then, designing a stable tangential tracking error controller for each drive axis, with the tangential tracking error vector as input and the tangential tracking error control component of each axis as output; finally, directly adding the normal contour error control component and the tangential tracking error control component of each axis to obtain a total control signal to control each drive axis.

[0004] For example, the patent with publication number CN107479497A discloses a dual closed-loop compensation method for five-axis machining trajectory contour error. This method is based on model prediction and feedback correction, estimates the movement position of each physical axis at the next moment, calculates the contour errors of the tool tip point and tool axis direction at the next moment and the current moment through tangential backstepping and Newton's method, and predicts and compensates the contour error in the inner loop and performs feedback compensation in the outer loop based on the inverse Jacobian matrix.

[0005] The above existing technologies have the following problems: the current error compensation method is usually based on compensation after the error is generated, and the existing pre-compensation method only predicts the compensation error and then compensates it, but ignores the order of error compensation of each processing axis, resulting in the processing axis being out of synchronization during the processing; to solve the above problems, the present invention provides an intelligent multi-axis synchronous control system and method for aluminum processing CNC machine tools. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention proposes an intelligent multi-axis synchronous control system and method for aluminum processing CNC machine tools. The system integrates intelligent perception, error compensation, processing control and interaction modules, wherein the intelligent perception module monitors and preprocesses multi-axis working status data in real time through integrated sensors, the error compensation module uses error monitoring units and error compensation units to predict and dynamically compensate multi-axis errors based on error models, the processing control module achieves precise synchronous control of workpieces and tools through three-dimensional modeling, processing trajectory generation and feedback adjustment, and the interaction module provides a visual display of processing progress and real-time monitoring and early warning of faults. This system effectively improves the aluminum processing accuracy and efficiency of five-axis CNC machine tools and enhances the intelligence and stability of the processing process.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] Intelligent multi-axis synchronous control system for aluminum processing CNC machine tools, including: intelligent sensing module, error compensation module and processing control module;

[0009] The intelligent sensing module includes a data acquisition unit; the data acquisition unit is used to collect processing data of the processing tool and the processing workpiece in real time through an integrated sensor;

[0010] The processing control module includes a three-dimensional modeling unit, a processing trajectory generation unit and a feedback adjustment unit; the three-dimensional modeling unit is used to construct an integrated three-dimensional model of the machine tool, the processing workpiece and the processing tool through a three-dimensional modeling software according to the attribute parameters of the machine tool, the processing workpiece and the processing tool, and to construct a multi-axis coordinate system of the machine tool, the processing workpiece and the processing tool on the constructed integrated three-dimensional model according to the actual positions of the processing workpiece and the processing tool; the processing trajectory generation unit is used to generate processing trajectory parameters of the processing workpiece and the processing tool on multiple axes through a trajectory generation algorithm according to the constructed integrated three-dimensional model, processing process parameters and error compensation instructions; the feedback adjustment unit is used to obtain the trajectory position error of the processing workpiece and the processing tool in the multi-axis trajectory after error compensation in real time, and feed back the obtained error to the error compensation unit to perform secondary compensation on the position error in the multi-axis trajectory;

[0011] The error compensation module includes an error monitoring unit and an error compensation unit;

[0012] The error monitoring unit is used to predict the real-time change trend of multi-axis errors and the error priority compensation degree according to the acquired processing data of the processing tools and workpieces through the built-in error offset model and error evaluation model, and feed back the calculated real-time change trend of multi-axis errors and the error priority compensation degree to the error compensation unit; the error compensation unit is used to generate error compensation instructions according to the predicted real-time change trend of multi-axis errors and the priority compensation degree through the built-in enhanced servo compensation model, and perform priority pre-compensation for the processing tool and processing workpiece errors in the corresponding coordinate axis direction.

[0013] Specifically, the multi-axis coordinate system of the machine tool, the workpiece and the tool includes: the machine tool coordinate system M , workpiece coordinate system o W , tool coordinate system o T , among which, o M , o W and T Indicate the origin of the corresponding coordinate system in turn; establish the corresponding translation axis coordinate systems X, Y, Z and rotation axis coordinate systems A and C according to the machine tool coordinate system, workpiece coordinate system and tool coordinate system.

[0014] Specifically, the processing data includes attribute data of the machine tool, the processing tool and the processing workpiece, processing process parameters of the processing workpiece, movement position error and rotation angle error data of the processing tool and the processing workpiece, vibration data corresponding to the machine tool, processing trajectory data of the processing tool and the processing workpiece in the translation axis coordinate system and the rotation axis coordinate system, and torque information data of the processing tool;

[0015] The specific steps of the error monitoring unit obtaining the real-time change trend of multi-axis errors through the error offset model include:

[0016] A1. Obtain the historical moving position error and rotation angle error data of the corresponding machining trajectory in the translation axis coordinate system and the rotation axis coordinate system during the machining process, the vibration data of the machine tool during the machining process, and the torque information data of the machining tool; the vibration data includes the vibration intensity and vibration direction;

[0017] A2. According to the acquired moving trajectory position error and rotation angle error data and the corresponding machining trajectory data of each axis, the error change rate of the corresponding moving trajectory position error and rotation angle error on the translation axis and the rotation axis is calculated, and the calculated error change rate is aligned in time with the machine tool vibration data during the machining process;

[0018] A3. Build an error offset model based on a support vector machine, input the aligned error change rate and machine tool vibration data, the machining trajectory data on the translation axis and the rotation axis corresponding to the error change rate, and the torque information data corresponding to the machining tool into the error offset model for training, and obtain the trained error offset model. At the same time, in the error offset model, obtain the error change rate on each translation or rotation axis with the movement and rotation trajectory, the vibration intensity and vibration direction in the vibration data, and the torque information change trend formula through the kernel function fitting in the support vector machine;

[0019] A4. The trained error offset model is built into the error monitoring unit, and the vibration data of the machine tool during operation, the trajectory data on each axis generated by the machining trajectory generation unit in real time, and the torque information data corresponding to each moving trajectory calculated according to the workpiece attribute data and the machining process parameters are obtained in real time, and the predicted error change rate corresponding to the trajectory data on each axis generated by the machining trajectory generation unit is calculated;

[0020] A5. According to the predicted error change rate, the predicted error change trend corresponding to the trajectory data on each axis generated by the machining trajectory generation unit is calculated.

[0021] Specifically, the specific steps of the error monitoring unit obtaining the error priority compensation degree through the error evaluation model include:

[0022] A6, for the error change rate obtained in A2, the corresponding priority compensation degree is marked according to the change direction of the error change rate, and the marked error change rate is aligned with the corresponding current translation and rotation axis trajectory data in time;

[0023] A7. Build an error assessment model based on the random forest algorithm, and input the error change rate and trajectory data of the aligned annotation into the error assessment model for training to obtain the trained error assessment model.

[0024] A8. Input the predicted error change rate and the corresponding trajectory data corresponding to the trajectory data on each axis predicted in A4 into the error evaluation model to obtain the error priority compensation degree and the error compensation rate corresponding to the error change rate at each time point of the machining trajectory on each translational or rotational axis.

[0025] Specifically, the enhanced servo compensation model in the error compensation unit includes a compensation adjustment layer; the steps of constructing the compensation adjustment layer include:

[0026] B1. Construct the input state at the current time t based on the acquired processing data, the predicted error change trend corresponding to the trajectory data on each axis, the error priority compensation degree and the error compensation rate Among them, X t represents the processing data sequence obtained at the current time t, It indicates the predicted error change trend of the machining trajectory corresponding to the i-th translation or rotation axis. It indicates the priority compensation degree of the machining trajectory error corresponding to the predicted i-th translation or rotation axis. It represents the predicted rate of error compensation of machining trajectory corresponding to the i-th translation or rotation axis;

[0027] B2. Setting the ideal machining trajectory parameters. When the machining trajectory parameters of the machining tool and the machining workpiece on the multi-axis obtained in real time are not equal to the ideal machining trajectory parameters, the error compensation information is triggered;

[0028] B3. Construct the current moment joint execution action based on the constructed input state and error priority compensation degree and error compensation rate where a t1 Indicates whether to perform error compensation action. t1 = 0, no error compensation action is performed, a t1 =1, the error compensation action is executed and the corresponding instruction is generated; a t2 Indicates in a t1 = 1, according to the obtained error priority compensation degree, error compensation is performed first on the translation or rotation axis machining trajectory with high error priority compensation degree; a t3 Indicates in a t1 =1, according to the error compensation rate predicted by the i-th translational or rotational axis machining trajectory, the error compensation of the corresponding rate is performed on the i-th translational or rotational axis machining trajectory;

[0029] B4. Construct reward function R based on the constructed joint execution action t , specifically:

[0030]

[0031] in, It represents the error distance between the jth ideal position point in the ideal machining trajectory parameter corresponding to the i-th translation or rotation axis at time t and the position point of the machining tool or workpiece in the i-th translation or rotation axis corresponding to the actual machining trajectory parameter, I g Indicates the g-th incorrect execution of a t1 The penalty term, G represents the error execution a t1 The total number of times when an error is executed t1 When g =1, otherwise I g =0,I v Indicates the vth incorrect execution of a t2 The penalty term, V represents the error execution a t2 The total number of times when an error is executed t2 Whenv =1, otherwise I v =0, represents the difference between the error compensation rate predicted on the i-th translation or rotation axis at time t and the actual error compensation rate; k1, k2, k3, k4 represent the gain coefficients corresponding to the reward function;

[0032] B5. Construct a compensation adjustment layer based on the reinforcement learning algorithm, and input the current input state at time t, the joint execution action and the reward function into the compensation adjustment layer for training, and output the priority compensation adjustment amount and the error compensation rate adjustment amount.

[0033] Specifically, the enhanced servo compensation model in the error compensation unit also includes a compensation control layer, and the steps of constructing the compensation control layer include:

[0034] B6. Initialize the control parameters in the compensation control layer based on the acquired processing data, the predicted error change trend corresponding to the trajectory data on each axis, the error priority compensation degree and the error compensation rate, and use the acquired priority compensation adjustment amount and error compensation rate adjustment amount to calculate the error compensation instruction corresponding to the i-th translation or rotation axis. The machining trajectory parameter error in the direction of the i-th translation or rotation axis is pre-compensated first. Specifically:

[0035]

[0036] Among them, q1 means execution of a t1 Corresponding to the obtained evaluation value, a t1 =0 corresponds to q1 = 0, when a t1 =1 corresponds to q1=1, q2 and q3 respectively represent the execution of a t2 and a t3 The corresponding evaluation value is obtained when t0 represents the time length of a complete machining trajectory of a machining tool or a machining workpiece on the i-th translational or rotational axis. i Represents the priority compensation factor of the machining trajectory on the i-th translational or rotational axis. i = 1, the machining trajectory on the i-th translation or rotation axis is compensated first. i = 0, no priority compensation is performed on the machining trajectory on the i-th translation or rotation axis. p represents the proportional coefficient within the initialization control parameter, k i represents the integral time coefficient in the initialization control parameters, k d Represents the derivative time coefficient in the initialization control parameters.

[0037] Specifically, the specific steps of obtaining the ideal machining trajectory parameters in B2 include:

[0038] C1. Based on the integrated three-dimensional model constructed by the three-dimensional modeling unit, the processing parameters of the workpiece and the error compensation instructions, the corresponding processing trajectory parameters are generated on each translation or rotation axis in the multi-axis coordinate system corresponding to the integrated three-dimensional model through the trajectory generation algorithm built into the virtual simulation software, and the generated processing trajectory parameters are set as ideal processing trajectory parameters;

[0039] C2. The acquired ideal machining trajectory parameters are built into the controller corresponding to the five-axis CNC machine tool, and the initial state of the error compensation instruction in the ideal machining trajectory parameters is set to a silent state. When the five-axis CNC machine tool starts working, the initial state of the error compensation instruction becomes an activated state, and the machining trajectory parameters of the corresponding machining tools and machining workpieces of the five-axis CNC machine tool are pre-compensated, so that the real-time machining trajectory parameters of the machining tools and machining workpieces in the multi-axis coordinate system are equal to the ideal machining trajectory parameters in real time.

[0040] Specifically, the error compensation rate of the machining trajectory on each translational or rotational axis at each time point is equal to the error change rate at each time point.

[0041] An intelligent multi-axis synchronous control method for aluminum material processing CNC machine tools comprises the following steps:

[0042] S1, obtaining the processing data of the processing tool and the processing workpiece, and preprocessing;

[0043] S2. Using the machine tool, machining tool and workpiece attribute data in the machining process data, construct an integrated three-dimensional model of the machine tool, machining tool and workpiece through three-dimensional modeling software, and construct a multi-axis coordinate system based on the constructed integrated three-dimensional model according to the actual position information of the machining tool and the workpiece;

[0044] S3. In the constructed multi-axis coordinate system, according to the machining process parameters in the machining process data, the ideal machining trajectory parameters of the machining tool and the machining workpiece on each translational or rotational axis are generated through a trajectory generation algorithm, and the obtained ideal machining trajectory parameters are built into the controller corresponding to the five-axis CNC machine tool;

[0045] S4. When the five-axis CNC machine tool starts working, the workpiece and the tool are controlled to perform corresponding processing through the built-in ideal processing trajectory parameters, and the error compensation instructions are generated through the built-in enhanced servo compensation model to pre-compensate the position error and rotation angle error of the workpiece and tool on the corresponding translation or rotation axis.

[0046] S5. The position errors of the workpiece and the tool in the multi-axis trajectory after compensation are acquired in real time through the feedback adjustment unit, and the acquired errors are fed back to the error compensation unit to perform secondary compensation on the position errors in the multi-axis trajectory.

[0047] A computer-readable storage medium stores computer instructions, which, when executed, execute an intelligent multi-axis synchronous control method for a numerically controlled machine tool for aluminum processing.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] The present invention strengthens the servo compensation model in combination with the predicted error change trend, the error priority compensation degree corresponding to the error change rate at each time point, and the error compensation rate, to give priority compensation to the processing trajectory on the translational or rotational axis with a fast error trend change, that is, the translational or rotational axis that first generates errors and has a fast error growth rate, so that the processing trajectory parameters on each axis are consistent with the ideal processing trajectory, thereby enhancing the consistency of the processing trajectory of each axis. At the same time, the error compensation rate obtained by calculating the error change rate on each axis is used to compensate the processing trajectory parameters on each axis, so that the processing trajectory on each axis can be synchronously restored to the corresponding ideal processing trajectory parameters, thereby enhancing the synchronization during the processing of the five-axis CNC machine tool. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a module diagram of an intelligent multi-axis synchronous control system for aluminum material processing CNC machine tools according to embodiment 1 of the present invention;

[0051] Figure 2 This is a working structure diagram of corresponding units of an intelligent multi-axis synchronous control system for aluminum material processing CNC machine tools according to Embodiment 2 of the present invention;

[0052] Figure 3 This is a flow chart of the intelligent multi-axis synchronous control method for aluminum processing CNC machine tools according to embodiment 3 of the present invention. DETAILED DESCRIPTION

[0053] Example 1

[0054] See also Figure 1 , an embodiment provided by the present invention: an intelligent multi-axis synchronous control system for aluminum processing CNC machine tools, applied to the control of aluminum processing by AC double-turntable five-axis machine tools, comprising: an intelligent sensing module, an error compensation module, a processing control module and an interactive module; the intelligent sensing module acquires multi-axis working status data of the five-axis CNC machine tool through real-time monitoring by sensors, and performs fusion preprocessing on the collected working status data; the intelligent sensing module comprises a data acquisition unit and a preprocessing fusion unit;

[0055] A data acquisition unit is used to collect processing data of the processing tool and the processing workpiece in real time through an integrated sensor; further, the processing data in this embodiment includes attribute data of the machine tool, the processing tool and the processing workpiece, processing process parameters of the processing workpiece, movement position error and rotation angle error data of the processing tool and the processing workpiece, vibration data corresponding to the machine tool, processing trajectory data of the processing tool and the processing workpiece in the translation axis coordinate system and the rotation axis coordinate system, and processing tool torque information data; further, the attribute data of the processing workpiece in this embodiment is aluminum material attribute data;

[0056] The preprocessing fusion unit is used to preprocess the collected data and integrate the preprocessed data into a unified format;

[0057] The processing control module is used for planning and synchronously controlling the motion trajectory of the workpiece and the processing tool on multiple axes; the processing control module includes a three-dimensional modeling unit, a processing trajectory generating unit and a feedback adjustment unit; the three-dimensional modeling unit is used to construct an integrated three-dimensional model of the machine tool, the processing workpiece and the processing tool through a three-dimensional modeling software according to the attribute parameters of the machine tool, the processing workpiece and the processing tool, and construct a multi-axis coordinate system of the machine tool, the processing workpiece and the processing tool on the constructed integrated three-dimensional model according to the actual positions of the processing workpiece and the processing tool; further, the specific steps of the three-dimensional modeling unit in this embodiment include:

[0058] a1. Input the attribute data of the machine tool, machining tool and workpiece in the pre-processed machining process data into the 3D modeling software to establish an integrated 3D model of the machine tool, machining tool and workpiece; further, in this embodiment, the attribute data of the machine tool, machining tool and workpiece include the travel range, speed, initial position of the machine tool, machining tool and workpiece on each axis, the geometric shape, size, material properties and other attributes of the workpiece, the type, diameter, length, blade shape and cutting parameters of the machining tool; further, the 3D modeling software includes: SolidWorks, SiemensNX and CATIA;

[0059] a2. Based on the constructed integrated three-dimensional model, a multi-axis coordinate system of the machine tool, the machine workpiece and the machining tool is constructed according to the actual positions of the machine workpiece and the machining tool; further, in this embodiment, the multi-axis coordinate system of the machine tool, the machine workpiece and the machining tool includes: the machine tool coordinate system o M , workpiece coordinate system o W , tool coordinate system o T , among which, o M , o W and T Indicate the origin of the corresponding coordinate system in turn; establish the corresponding translation axis coordinate systems X, Y, Z and rotation axis coordinate systems A and C according to the machine tool coordinate system, workpiece coordinate system and tool coordinate system.

[0060] The processing trajectory generation unit is used to generate processing trajectory parameters of the processing workpiece and the processing tool on multiple axes through a trajectory generation algorithm based on the constructed integrated three-dimensional model, processing process parameters and error compensation instructions; further, the trajectory generation algorithm in this embodiment includes a Dijkstra algorithm and an A* search algorithm.

[0061] The feedback adjustment unit is used to obtain the trajectory position errors of the processing workpiece and the processing tool in the multi-axis trajectory after error compensation in real time, and feed back the obtained errors to the error compensation unit to perform secondary compensation on the position errors in the multi-axis trajectory.

[0062] An error compensation module, used for predicting translational or rotational errors and dynamically compensating corresponding predicted errors; the error compensation module includes an error monitoring unit and an error compensation unit;

[0063] The error monitoring unit is used to predict the real-time change trend of the multi-axis error and the error priority compensation degree according to the acquired position information and movement information data of the machining tool and the workpiece through the built-in error offset model and the error evaluation model, and feed back the calculated real-time change trend of the multi-axis error and the error priority compensation degree to the error compensation unit; further, in this embodiment, the specific steps of the error monitoring unit obtaining the real-time change trend of the multi-axis error through the error offset model include:

[0064] A1. Obtain the historical moving position error and rotation angle error data of the corresponding machining trajectory in the translation axis coordinate system and the rotation axis coordinate system during the machining process, the vibration data of the machine tool during the machining process, and the torque information data of the machining tool; the vibration data includes the vibration intensity and vibration direction;

[0065] A2. According to the acquired moving trajectory position error and rotation angle error data and the corresponding machining trajectory data of each axis, the error change rate of the corresponding moving trajectory position error and rotation angle error on the translation axis and the rotation axis is calculated, and the calculated error change rate is aligned in time with the machine tool vibration data during the machining process;

[0066] A3. Build an error offset model based on support vector machine, input the aligned error change rate and machine tool vibration data, the machining trajectory data on the translation axis and rotation axis corresponding to the error change rate, and the torque information data corresponding to the machining tool into the error offset model for training, and obtain the trained error offset prediction model. At the same time, in the error offset model, obtain the error change rate on each translation or rotation axis with the movement and rotation trajectory, the vibration intensity and vibration direction in the vibration data, and the torque information change trend formula through kernel function fitting in the support vector machine;

[0067] A4. The trained error offset model is built into the error monitoring unit, and the vibration data of the machine tool during operation, the trajectory data on each axis generated by the machining trajectory generation unit in real time, and the torque information data corresponding to each moving trajectory calculated according to the workpiece attribute data and the machining process parameters are obtained in real time, and the predicted error change rate corresponding to the trajectory data on each axis generated by the machining trajectory generation unit is calculated;

[0068] A5. According to the predicted error change rate, the predicted error change trend corresponding to the trajectory data on each axis generated by the machining trajectory generation unit is calculated.

[0069] This process analyzes the position, vibration and torque data during the processing in real time, uses the trained error offset model to predict the trend of multi-axis error changes, achieves accurate error compensation, effectively improves processing accuracy and efficiency, and reduces scrap rate. At the same time, through the evaluation of error priorities, it optimizes resource allocation and enhances the intelligence level of the manufacturing system.

[0070] Furthermore, the specific steps of the error monitoring unit obtaining the error priority compensation degree through the error evaluation model include:

[0071] A6. For the error change rate obtained in A2, the corresponding priority compensation degree is marked according to the change direction of the error change rate, and the marked error change rate is aligned with the corresponding current translation and rotation axis trajectory data in time; further, the specific steps of marking the corresponding priority compensation degree in this embodiment include:

[0072] A61, dividing the error change rate obtained according to each time point, and taking 0 as the starting point of the divided error change rate, calculating the difference between the change rate and 0, and using the obtained difference as the priority compensation degree label to mark the corresponding priority compensation degree;

[0073] A7. Build an error assessment model based on the random forest algorithm, and input the error change rate and trajectory data of the aligned annotation into the error assessment model for training to obtain the trained error assessment model.

[0074] A8. Input the predicted error change rate and the corresponding trajectory data corresponding to the trajectory data on each axis predicted in A4 into the error evaluation model to obtain the error priority compensation degree and the error compensation rate corresponding to the error change rate at each time point of the machining trajectory on each translational or rotational axis.

[0075] In this embodiment, according to the obtained error priority compensation degree, it is determined that the trajectory with the highest priority compensation degree is given priority error compensation, so that the movement trajectory of each axis is consistent. For example, when the translation axis X has an error, and the translation axes Y and Z do not have errors, the translation axis X can be given priority compensation according to the error priority compensation degree. For another example, when the translation axis X, the translation axis Y and the translation axis Z are in motion, according to the calculated error priority compensation, the one with the largest error priority compensation is given priority compensation, that is, the translation axis with the fastest error change is given priority compensation, so as to further ensure the synchronous operation of the movement trajectory of each axis, and the same is true for the rotation axes A and C. Further, in this embodiment, The error compensation rate of the processing trajectory on each translational or rotational axis at each time point is equal to the error change rate at each time point; further, this embodiment obtains the error compensation rate of each translational or rotational axis through predictive calculation, and compensates the error of the corresponding translational or rotational axis at a corresponding rate according to the obtained error compensation rate. This avoids the situation where the error compensation on some translational or rotational axes is not in place or exceeds the limit at the same compensation rate, so that the processing trajectories on all translational or rotational axes can be restored to the ideal processing trajectory at the same time, so that the processing processes on each translational or rotational axis can be kept consistent, thereby enhancing the control accuracy and processing accuracy.

[0076] This process quantifies the priority of error compensation through an error evaluation model, ensuring that critical errors are corrected in a timely manner and maintaining the consistency of motion of each axis, significantly enhancing the stability of the machining process and the quality of the finished product. Especially in complex and changing machining environments, this dynamic error management strategy greatly improves production efficiency and part accuracy.

[0077] The error compensation unit is used to generate error compensation instructions based on the predicted real-time change trend of multi-axis errors and the priority compensation degree through the built-in enhanced servo compensation model, and perform priority pre-compensation on the errors of the machining tool and the machining workpiece in the corresponding coordinate axis direction; further, the enhanced servo compensation model in the error compensation unit in this embodiment includes a compensation adjustment layer and a compensation control layer; the steps of constructing the compensation adjustment layer and the compensation control layer include:

[0078] B1. Construct the input state at the current time t based on the acquired processing data, the predicted error change trend corresponding to the trajectory data on each axis, the error priority compensation degree and the error compensation rate Among them, X t represents the processing data sequence obtained at the current time t, It indicates the predicted error change trend of the machining trajectory corresponding to the i-th translation or rotation axis. It indicates the priority compensation degree of the machining trajectory error corresponding to the predicted i-th translation or rotation axis. It represents the predicted rate of error compensation of machining trajectory corresponding to the i-th translation or rotation axis;

[0079] B2. Setting the ideal machining trajectory parameters. When the machining trajectory parameters of the machining tool and the machining workpiece on the multi-axis obtained in real time are not equal to the ideal machining trajectory parameters, the error compensation information is triggered;

[0080] B3. Construct the current moment joint execution action based on the constructed input state and error priority compensation degree and error compensation rate where a t1 Indicates whether to perform error compensation action. t1 = 0, no error compensation action is performed, a t1 =1, the error compensation action is executed and the corresponding instruction is generated; a t2 Indicates in a t1 = 1, according to the obtained error priority compensation degree, error compensation is performed first on the translation or rotation axis machining trajectory with high error priority compensation degree; a t3 Indicates in a t1 =1, according to the error compensation rate predicted by the i-th translational or rotational axis machining trajectory, the error compensation of the corresponding rate is performed on the i-th translational or rotational axis machining trajectory;

[0081] B4. Construct reward function R based on the constructed joint execution action t , specifically:

[0082]

[0083] in, It represents the error distance between the jth ideal position point in the ideal machining trajectory parameter corresponding to the i-th translation or rotation axis at time t and the position point of the machining tool or workpiece in the i-th translation or rotation axis corresponding to the actual machining trajectory parameter, I g Indicates the g-th incorrect execution of a t1 The penalty term, G represents the error execution a t1 The total number of times when an error is executed t1 When g =1, otherwise I g =0,I v Indicates the vth incorrect execution of a t2 The penalty term, V represents the error execution a t2 The total number of times when an error is executed t2 When v =1, otherwise I v =0, represents the difference between the error compensation rate predicted on the i-th translational or rotational axis at time t and the actual error compensation rate; k1, k2, k3, k4 represent the gain coefficients corresponding to the reward function; further, in this embodiment, rewards are given by the error distance of the machining trajectory parameter position point, the difference between the error compensation rate and the actual error compensation rate, the error execution error compensation and the error execution priority compensation. The smaller the error and the number of execution errors, the greater the reward given, so that the enhanced servo compensation model can more accurately avoid the occurrence of errors and execution errors, and further improve the control accuracy of the enhanced servo compensation model;

[0084] B5. Construct a compensation adjustment layer based on the reinforcement learning algorithm, and input the current input state at time t, the joint execution action and the reward function into the compensation adjustment layer for training, and output the priority compensation adjustment amount and the error compensation rate adjustment amount;

[0085] B6. Initialize the control parameters in the compensation control layer based on the acquired processing data, the predicted error change trend corresponding to the trajectory data on each axis, the error priority compensation degree and the error compensation rate, and use the acquired priority compensation adjustment amount and error compensation rate adjustment amount to calculate the error compensation instruction corresponding to the i-th translation or rotation axis. The machining trajectory parameter error in the direction of the i-th translation or rotation axis is pre-compensated first. Specifically, Specifically:

[0086]

[0087] Among them, q1 means execution of a t1 Corresponding to the obtained evaluation value, a t1 =0 corresponds to q1 = 0, when a t1 =1 corresponds to q1=1, q2 and q3 respectively represent the execution of a t2 and a t3 The corresponding evaluation value is obtained when t0 represents the time length of a complete machining trajectory of a machining tool or a machining workpiece on the i-th translational or rotational axis. i Represents the priority compensation factor of the machining trajectory on the i-th translational or rotational axis. i = 1, the machining trajectory on the i-th translation or rotation axis is compensated first. i = 0, no priority compensation is performed on the machining trajectory on the i-th translation or rotation axis. p represents the proportional coefficient within the initialization control parameter, k i represents the integral time coefficient in the initialization control parameters, k d Represents the derivative time coefficient in the initialization control parameters.

[0088] This process realizes dynamic error management during machining by intelligently analyzing and predicting error trends and error priority compensation. It can not only accurately identify key axes that need priority compensation according to real-time error trends, but also optimize compensation strategies through reinforcement learning to ensure machining accuracy and efficiency, effectively reduce cumulative errors, and improve the consistency and surface quality of complex workpieces. At the same time, by adaptively adjusting the compensation rate and priority, it can flexibly respond to different material properties and machining conditions, so that the machining process on each translational or rotational axis is in real time in accordance with the ideal machining trajectory and maintained in a synchronized state, making the machining process more accurate. In addition, in this embodiment, the synchronization of the machining process is achieved only by compensating for the machining errors of each axis during the machining process, eliminating the transformation relationship between the axes, further reducing the complexity of the control method, and improving the practicability of the control system.

[0089] Furthermore, in this embodiment, the specific steps of obtaining the ideal processing trajectory parameters in B2 include:

[0090] C1. Based on the integrated three-dimensional model constructed by the three-dimensional modeling unit, the processing parameters of the workpiece and the error compensation instructions, the corresponding processing trajectory parameters are generated on each translation or rotation axis in the multi-axis coordinate system corresponding to the integrated three-dimensional model through the trajectory generation algorithm built into the virtual simulation software, and the generated processing trajectory parameters are set as ideal processing trajectory parameters;

[0091] C2. The acquired ideal machining trajectory parameters are built into the controller corresponding to the five-axis CNC machine tool, and the initial state of the error compensation instruction in the ideal machining trajectory parameters is set to a silent state. When the five-axis CNC machine tool starts working, the initial state of the error compensation instruction becomes an activated state, and the machining trajectory parameters of the corresponding machining tools and machining workpieces of the five-axis CNC machine tool are pre-compensated, so that the real-time machining trajectory parameters of the machining tools and machining workpieces in the multi-axis coordinate system are equal to the ideal machining trajectory parameters in real time.

[0092] The interactive module is used for real-time display of the processing progress of the workpiece and monitoring and early warning of processing failures; the interactive module includes a visualization unit and a processing early warning unit;

[0093] The visualization unit is used to display the integrated three-dimensional model constructed during the processing, the processing trajectory parameters corresponding to each translation or rotation axis, and the processing progress in real time; the processing warning unit is used to monitor the abnormalities and faults in the processing process in real time through the fault monitoring algorithm, and to issue real-time warnings for the monitored abnormalities and faults through the interactive interface. Furthermore, the fault monitoring algorithm in this embodiment includes a random forest algorithm and a support vector machine algorithm.

[0094] Example 2

[0095] See also Figure 2 Another embodiment provided by the present invention: the corresponding unit workflow of the intelligent multi-axis synchronous control system for aluminum processing CNC machine tools includes:

[0096] First, the data acquisition unit collects the processing data of the machining tool and the workpiece in real time, and the preprocessing and fusion unit preprocesses the collected data and integrates them in a unified format;

[0097] Second, based on the attribute data in the acquired machining process data, an integrated three-dimensional model of the machining workpiece and the machining tool is constructed through a three-dimensional modeling unit, and on the constructed integrated three-dimensional model, a multi-axis coordinate system of the machining workpiece and the machining tool is constructed according to the actual positions of the machining workpiece and the machining tool. At the same time, based on the constructed integrated three-dimensional model and the machining process data in the acquired machining process data, on each coordinate axis of the integrated three-dimensional model corresponding to the multi-axis coordinate system, a machining trajectory generating unit is used to generate machining trajectory parameters of the machining workpiece and the machining tool on each coordinate axis in the multi-axis coordinate system;

[0098] Third, the error monitoring unit predicts the error change trend, error priority compensation degree and error compensation amount according to the processing data obtained in real time; the error compensation unit generates the error compensation instruction in real time according to the predicted error change trend, error priority compensation degree, error compensation amount and processing data;

[0099] Fourth, when the five-axis CNC machine tool starts working, the generated error compensation instructions are used to perform real-time priority pre-compensation on the machining trajectory of the workpiece and the machining tool on each translation or rotation axis according to the acquired machining trajectory parameters. At the same time, the position errors of the workpiece and the machining tool in the multi-axis trajectory after compensation are obtained in real time through the feedback adjustment unit, and the obtained errors are fed back to the error compensation unit to perform secondary compensation on the position errors in the multi-axis trajectory.

[0100] Sixth, the integrated three-dimensional model, processing path and processing progress in the above-mentioned first to fifth processes are displayed in real time through the visualization unit. At the same time, the processing early warning unit is used to monitor the abnormalities and faults in the first to sixth processes in real time, and a real-time early warning is issued when the monitoring reaches the abnormality or fault.

[0101] Example 3

[0102] See also Figure 3 Another embodiment provided by the present invention is an intelligent multi-axis synchronous control method for aluminum material processing CNC machine tools, the steps comprising:

[0103] S1, obtaining the processing data of the processing tool and the processing workpiece, and preprocessing;

[0104] S2. Using the machine tool, machining tool and workpiece attribute data in the machining process data, construct an integrated three-dimensional model of the machine tool, machining tool and workpiece through three-dimensional modeling software, and construct a multi-axis coordinate system based on the constructed integrated three-dimensional model according to the actual position information of the machining tool and the workpiece;

[0105] S3. In the constructed multi-axis coordinate system, according to the machining process parameters in the machining process data, the ideal machining trajectory parameters of the machining tool and the machining workpiece on each translational or rotational axis are generated through a trajectory generation algorithm, and the obtained ideal machining trajectory parameters are built into the controller corresponding to the five-axis CNC machine tool;

[0106] S4. When the five-axis CNC machine tool starts working, the workpiece and the tool are controlled to perform corresponding processing through the built-in ideal processing trajectory parameters, and the error compensation instruction is generated through the built-in enhanced servo compensation model to pre-compensate the movement position error and rotation angle error of the workpiece and the tool on the corresponding translation or rotation axis in priority, so that the real-time processing trajectory parameters of the tool and the workpiece in the multi-axis coordinate system are equal to the ideal processing trajectory parameters in real time;

[0107] S5, obtaining the position errors of the workpiece and the machining tool in the multi-axis trajectory after compensation in real time through the feedback adjustment unit, and feeding back the obtained errors to the error compensation unit to perform secondary compensation on the position errors in the multi-axis trajectory;

[0108] S6. The processing of processes S1 to S5 is monitored in real time through a fault monitoring algorithm, and real-time warnings are issued for monitored anomalies and faults through an interactive interface.

[0109] Example 4

[0110] A computer-readable storage medium stores computer instructions, which, when executed, execute an intelligent multi-axis synchronous control method for a numerically controlled machine tool for aluminum processing.

[0111] An electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements an intelligent multi-axis synchronous control method for a numerically controlled machine tool for aluminum processing when executing the computer program.

[0112] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in the field may also change, modify, replace and modify the above-mentioned embodiments without departing from the scope of protection of the purpose of the present invention and the claims, and all of these are within the protection of the present invention.

Claims

1. Intelligent multi-axis synchronous control system for aluminum processing CNC machine tools, characterized in that: include: Intelligent sensing module, error compensation module and processing control module; The intelligent sensing module includes a data acquisition unit; the data acquisition unit is used to collect processing data of the processing tool and the processing workpiece in real time through an integrated sensor; The processing control module includes a three-dimensional modeling unit, a processing trajectory generating unit and a feedback adjustment unit; the three-dimensional modeling unit is used to construct an integrated three-dimensional model of the machine tool, the processing workpiece and the processing tool through a three-dimensional modeling software according to the attribute parameters of the machine tool, the processing workpiece and the processing tool, and construct a multi-axis coordinate system of the machine tool, the processing workpiece and the processing tool on the constructed integrated three-dimensional model according to the actual positions of the processing workpiece and the processing tool; the processing trajectory generating unit is used to generate processing trajectory parameters of the processing workpiece and the processing tool on multiple axes through a trajectory generating algorithm according to the constructed integrated three-dimensional model, processing process parameters and error compensation instructions; the feedback adjustment unit is used to obtain the trajectory position error of the processing workpiece and the processing tool in the multi-axis trajectory after error compensation in real time, and feed back the obtained error to the error compensation unit to perform secondary compensation on the position error in the multi-axis trajectory; The error compensation module includes an error monitoring unit and an error compensation unit; The error monitoring unit is used to predict the real-time change trend of multi-axis errors and the error priority compensation degree according to the acquired processing data of the processing tool and the processing workpiece through the built-in error offset model and the error evaluation model, and feed back the calculated real-time change trend of multi-axis errors and the error priority compensation degree to the error compensation unit; the error compensation unit is used to generate error compensation instructions according to the predicted real-time change trend of multi-axis errors and the priority compensation degree through the built-in enhanced servo compensation model, and perform priority pre-compensation for the processing tool and processing workpiece errors in the corresponding coordinate axis direction.

2. The intelligent multi-axis synchronous control system for aluminum processing CNC machine tools according to claim 1, characterized in that: The multi-axis coordinate system of the machine tool, the workpiece and the tool comprises: a machine tool coordinate system M , workpiece coordinate system o W , tool coordinate system o T , among which, o M , o W and T Indicate the origin of the corresponding coordinate system in turn; according to the machine tool coordinate system, the workpiece coordinate system and the tool coordinate system, establish their corresponding translation axis coordinate systems X, Y, Z and rotation axis coordinate systems A and C.

3. The intelligent multi-axis synchronous control system for aluminum processing CNC machine tools according to claim 2, characterized in that: The processing data includes attribute data of the machine tool, the processing tool and the processing workpiece, processing parameters of the processing workpiece, movement position error and rotation angle error data of the processing tool and the processing workpiece, vibration data corresponding to the machine tool, processing trajectory data of the processing tool and the processing workpiece in the translation axis coordinate system and the rotation axis coordinate system, and torque information data of the processing tool; The specific steps of the error monitoring unit obtaining the real-time variation trend of the multi-axis error through the error offset model include: A1. Obtain historical moving position error and rotation angle error data of the corresponding machining trajectory in the translation axis coordinate system and the rotation axis coordinate system during the machining process, vibration data corresponding to the machine tool during the machining process, and torque information data corresponding to the machining tool; the vibration data includes vibration intensity and vibration direction; A2. According to the acquired moving trajectory position error and rotation angle error data and the corresponding machining trajectory data of each axis, the error change rate of the corresponding moving trajectory position error and rotation angle error on the translation axis and the rotation axis is calculated, and the calculated error change rate is aligned in time with the machine tool vibration data during the machining process; A3. Build an error offset model based on a support vector machine, input the aligned error change rate and machine tool vibration data, the machining trajectory data on the translation axis and the rotation axis corresponding to the error change rate, and the torque information data corresponding to the machining tool into the error offset model for training, and obtain the trained error offset model. At the same time, in the error offset model, obtain the error change rate on each translation or rotation axis with the movement and rotation trajectory, the vibration intensity and vibration direction in the vibration data, and the torque information change trend formula through the kernel function fitting in the support vector machine; A4. The trained error offset model is built into the error monitoring unit, and the vibration data of the machine tool during operation, the trajectory data on each axis generated by the machining trajectory generation unit in real time, and the torque information data corresponding to each moving trajectory calculated according to the workpiece attribute data and the machining process parameters are obtained in real time, and the predicted error change rate corresponding to the trajectory data on each axis generated by the machining trajectory generation unit is calculated; A5. According to the predicted error change rate, the predicted error change trend corresponding to the trajectory data on each axis generated by the machining trajectory generation unit is calculated.

4. The intelligent multi-axis synchronous control system for aluminum processing CNC machine tools according to claim 3, characterized in that: The specific steps of the error monitoring unit obtaining the error priority compensation degree through the error evaluation model include: A6, for the error change rate obtained in A2, the corresponding priority compensation degree is marked according to the change direction of the error change rate, and the marked error change rate is aligned with the corresponding current translation and rotation axis trajectory data in time; A7. Build an error assessment model based on the random forest algorithm, and input the error change rate and trajectory data of the aligned annotation into the error assessment model for training to obtain the trained error assessment model. A8. Input the predicted error change rate and the corresponding trajectory data corresponding to the trajectory data on each axis predicted in A4 into the error evaluation model to obtain the error priority compensation degree and the error compensation rate corresponding to the error change rate at each time point of the machining trajectory on each translational or rotational axis.

5. The intelligent multi-axis synchronous control system for aluminum material processing CNC machine tools according to claim 4, characterized in that: The enhanced servo compensation model in the error compensation unit includes a compensation adjustment layer; the steps of constructing the compensation adjustment layer include: B1. Construct the input state at the current time t based on the acquired processing data, the predicted error change trend corresponding to the trajectory data on each axis, the error priority compensation degree and the error compensation rate Among them, Xt represents the processing data sequence obtained at the current time t, It indicates the predicted error change trend of the machining trajectory corresponding to the i-th translation or rotation axis. It indicates the priority compensation degree of the machining trajectory error corresponding to the predicted i-th translation or rotation axis. It represents the predicted rate of error compensation of machining trajectory corresponding to the i-th translation or rotation axis; B2. Setting the ideal machining trajectory parameters. When the machining trajectory parameters of the machining tool and the machining workpiece on the multi-axis obtained in real time are not equal to the ideal machining trajectory parameters, the error compensation information is triggered; B3. Construct the current moment joint execution action based on the constructed input state and error priority compensation degree and error compensation rate Wherein, at1 indicates whether to execute the error compensation action. When at1=0, the error compensation action is not executed. When at1=1, the error compensation action is executed and the corresponding instruction is generated. At2 indicates that under the premise of at1=1, according to the error priority compensation degree obtained, the error compensation is preferentially executed for the translation or rotation axis machining trajectory with a high error priority compensation degree. At3 indicates that under the premise of at1=1, according to the error compensation rate predicted for the i-th translation or rotation axis machining trajectory, the error compensation of the corresponding rate is executed for the i-th translation or rotation axis machining trajectory. B4. Construct a reward function Rt based on the constructed joint execution action, specifically: in, It represents the error distance between the jth ideal position point in the ideal machining trajectory parameters corresponding to the i-th translation or rotation axis at time t and the position point of the machining tool or the workpiece in the i-th translation or rotation axis corresponding to the actual machining trajectory parameters. Ig represents the penalty item for the g-th incorrect execution of at1. G represents the total number of incorrect executions of at1. When at1 is executed incorrectly, Ig=1, otherwise Ig=0. Iv represents the penalty item for the v-th incorrect execution of at2. V represents the total number of incorrect executions of at2. When at2 is executed incorrectly, Iv=1, otherwise Iv=0. represents the difference between the error compensation rate predicted on the i-th translation or rotation axis at time t and the actual error compensation rate; k1, k2, k3, k4 represent the gain coefficients corresponding to the reward function; B5. Construct a compensation adjustment layer based on the reinforcement learning algorithm, and input the current input state at time t, the joint execution action and the reward function into the compensation adjustment layer for training, and output the priority compensation adjustment amount and the error compensation rate adjustment amount.

6. The intelligent multi-axis synchronous control system for aluminum material processing CNC machine tools according to claim 5, characterized in that: The enhanced servo compensation model in the error compensation unit further includes a compensation control layer, and the steps of constructing the compensation control layer include: B6. Initialize the control parameters in the compensation control layer based on the acquired processing data, the predicted error change trend corresponding to the trajectory data on each axis, the error priority compensation degree and the error compensation rate, and use the acquired priority compensation adjustment amount and error compensation rate adjustment amount to calculate the error compensation instruction corresponding to the i-th translation or rotation axis. The machining trajectory parameter error in the direction of the i-th translation or rotation axis is pre-compensated first. Specifically: Among them, q1 represents the evaluation value obtained when executing at1, when at1=0, q1=0 corresponds to q1, when at1=1, q2 and q3 represent the evaluation values ​​obtained when executing at2 and at3 respectively, t0 represents the time length for the machining tool or the machining workpiece to move a complete machining trajectory on the i-th translational or rotational axis, Ii represents the priority compensation factor of the machining trajectory on the i-th translational or rotational axis, when Ii=1, the machining trajectory on the i-th translational or rotational axis is compensated first, and when Ii=0, the machining trajectory on the i-th translational or rotational axis is not compensated first, kp represents the proportional coefficient in the initialization control parameters, ki represents the integral time coefficient in the initialization control parameters, and kd represents the differential time coefficient in the initialization control parameters.

7. The intelligent multi-axis synchronous control system for aluminum material processing CNC machine tools according to claim 6, characterized in that: The specific steps of obtaining the ideal machining trajectory parameters in B2 include: C1. According to the integrated three-dimensional model constructed by the three-dimensional modeling unit, the processing parameters of the workpiece and the error compensation instructions, the corresponding processing trajectory parameters are generated on each translation or rotation axis in the multi-axis coordinate system corresponding to the integrated three-dimensional model through the trajectory generation algorithm built into the virtual simulation software, and the generated processing trajectory parameters are set as ideal processing trajectory parameters; C2. The acquired ideal machining trajectory parameters are built into the controller corresponding to the five-axis CNC machine tool, and the initial state of the error compensation instruction in the ideal machining trajectory parameters is set to a silent state. When the five-axis CNC machine tool starts working, the initial state of the error compensation instruction becomes an activated state, and the machining trajectory parameters of the corresponding machining tools and machining workpieces of the five-axis CNC machine tool are pre-compensated, so that the real-time machining trajectory parameters of the machining tools and machining workpieces in the multi-axis coordinate system are equal to the ideal machining trajectory parameters in real time.

8. The intelligent multi-axis synchronous control system for aluminum material processing CNC machine tools according to claim 7, characterized in that: The error compensation rate of the machining trajectory on each translational or rotational axis at each time point is equal to the error change rate at each time point.

9. An intelligent multi-axis synchronous control method for aluminum processing CNC machine tools, which is implemented based on the intelligent multi-axis synchronous control system for aluminum processing CNC machine tools according to any one of claims 1 to 8, characterized in that the steps include: S1, obtaining the processing data of the processing tool and the processing workpiece, and preprocessing; S2, using the machine tool, machining tool and workpiece attribute data in the machining process data, constructing an integrated three-dimensional model of the machine tool, machining tool and workpiece through three-dimensional modeling software, and constructing a multi-axis coordinate system on the constructed integrated three-dimensional model according to the actual position information of the machining tool and the workpiece; S3. In the constructed multi-axis coordinate system, according to the machining process parameters in the machining process data, the ideal machining trajectory parameters of the machining tool and the machining workpiece on each translational or rotational axis are generated through the trajectory generation algorithm, and the obtained ideal machining trajectory parameters are built into the controller corresponding to the five-axis CNC machine tool; S4. When the five-axis CNC machine tool starts working, the workpiece and the tool are controlled to perform corresponding processing through the built-in ideal processing trajectory parameters, and the error compensation instructions are generated through the built-in enhanced servo compensation model to pre-compensate the position error and rotation angle error of the workpiece and tool on the corresponding translation or rotation axis. S5. The position errors of the workpiece and the tool in the multi-axis trajectory after compensation are acquired in real time through the feedback adjustment unit, and the acquired errors are fed back to the error compensation unit to perform secondary compensation on the position errors in the multi-axis trajectory.

10. A computer-readable storage medium, characterized in that: Computer instructions are stored thereon, and when the computer instructions are executed, the intelligent multi-axis synchronous control method for aluminum processing CNC machine tools described in claim 9 is executed.

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