Multi-axis PCB milling synchronous control method, device and equipment and storage medium

Abstract

The invention provides a multi-axis PCB milling synchronous control method, device and equipment and a storage medium. The method comprises the steps that geometric modeling is conducted on a PCB and a tool, a PCB machining model is generated, a tool path is generated based on the PCB machining model, the meshing state of the tool and the PCB is extracted, and a meshing geometric entity is obtained. And then, calculating the instantaneous undeformed chip thickness according to the meshing geometric entity, and predicting the cutting force of the cutter acting on the PCB. Based on the cutting force prediction result, the tool path data and the PCB machining model, modeling is conducted on multi-axis motion of the PCB milling machine tool, and a multi-axis motion synchronous control model is generated. Finally, according to the synchronous control model and the cutting force prediction result, self-adaptive synchronous control is conducted on multi-axis motion. According to the PCB milling method, the cutting force is predicted in real time, the multi-axis machine tool is subjected to self-adaptive synchronous control, the machining precision is improved, the service life of the tool is prolonged, and the stability and consistency of the PCB machining process are ensured.

Description

Technical Field

[0001] The present invention relates to the field of workpiece processing, and in particular to a multi-axis PCB milling synchronous control method, device, equipment and storage medium. Background Art

[0002] With the growing demand for miniaturization and high precision of electronic products, the processing accuracy and efficiency of printed circuit boards (PCBs) have become key factors affecting the development of the electronics manufacturing industry. In the PCB manufacturing process, milling technology is widely used for precision processing of PCB boards. However, traditional PCB milling control methods usually rely on fixed tool paths and preset processing parameters, which are difficult to dynamically adjust according to actual conditions during the processing process, resulting in problems such as uneven cutting force, increased tool wear and low processing accuracy. In addition, the motion synchronization of multi-axis machine tools in PCB processing has a great influence on the processing effect, but the existing control methods lack precise control of multi-axis linkage synchronization, especially in the case of complex geometric shapes and cutting force fluctuations, it is difficult to ensure high-precision processing. Summary of the invention

[0003] The main purpose of the present invention is to solve the technical problem that the existing PCB milling control method lacks precise control of multi-axis linkage synchronization under complex geometric shapes and cutting force fluctuations, and is difficult to ensure high-precision processing; A first aspect of the present invention provides a multi-axis PCB milling synchronization control method, the multi-axis PCB milling synchronization control method comprising: Performing geometric modeling on the PCB board and the tool on the PCB milling machine to obtain a PCB processing model, and generating a tool path of the tool according to the PCB processing model to obtain tool path data; Extracting the meshing state between the PCB board and the tool according to the tool path data to obtain a meshing geometric entity; Calculating the instantaneous undeformed chip thickness between the PCB board and the tool according to the meshing geometric entity, and predicting the cutting force of the tool acting on the PCB board based on the instantaneous undeformed chip thickness to obtain a cutting force prediction result; Modeling the multi-axis motion of the PCB milling machine tool according to the cutting force prediction result, the tool path data and the PCB processing model to obtain a multi-axis motion synchronization control model; According to the multi-axis motion synchronous control model and the cutting force prediction result, the multi-axis motion of the PCB milling machine tool is adaptively synchronously controlled.

[0004] Optionally, in a first implementation of the first aspect of the present invention, geometric modeling is performed on the PCB board and the tool on the PCB milling machine to obtain a PCB processing model, and a tool path of the tool is generated according to the PCB processing model, and obtaining the tool path data includes: Performing geometric modeling on a PCB board and a tool on a PCB milling machine to obtain a three-dimensional geometric model of the PCB board and the tool; According to the three-dimensional geometric models of the PCB board and the tool, a workpiece coordinate system and a tool feed coordinate system are constructed to obtain a processing coordinate system; Generate a PCB processing model according to the three-dimensional geometric model of the PCB board, the three-dimensional geometric model of the tool and the processing coordinate system; According to the PCB processing model, a rough machining tool path of the tool is generated by using a contour method, and a fine machining tool path is generated according to the rough machining tool path by using a surface matching algorithm to obtain an initial tool path; The initial tool path is subjected to multi-objective optimization processing to obtain optimized tool path data.

[0005] Optionally, in a second implementation of the first aspect of the present invention, extracting the meshing state between the PCB board and the tool according to the tool path data to obtain the meshing geometric entity includes: According to the tool path data, searching for historical tool position points adjacent to the current tool position point of the tool to obtain a local historical tool position point set; Reconstructing the local cutout material of the PCB board according to the local historical tool position point set to obtain a local cutout material geometric entity; Acquire the current tool entity of the tool and the PCB board entity of the PCB board according to the PCB processing model, and perform local Boolean operation on the current tool entity, the PCB board entity and the local cut material geometric entity to obtain an initial meshing geometric entity; Orthogonal plane projection is performed on the initial meshing geometric entity to obtain a side edge cutting state projection diagram and a bottom edge cutting state projection diagram, and two-dimensional image mapping is performed to obtain a meshing geometric entity.

[0006] Optionally, in a third implementation of the first aspect of the present invention, the instantaneous undeformed chip thickness between the PCB board and the tool is calculated according to the meshing geometric entity, and the cutting force of the tool acting on the PCB board is predicted based on the instantaneous undeformed chip thickness, and the cutting force prediction result is obtained, which includes: Decomposing the feed motion between adjacent tool position points in the tool path data to obtain translation motion components along the X-axis and Z-axis of the tool feed coordinate system and a rotation motion component around the Y-axis; Calculating the instantaneous undeformed chip thickness between the PCB and the tool according to the translational motion component, the rotational motion component, the meshing geometric entity and the material parameters of the PCB; According to the instantaneous undeformed chip thickness and the preset cutting force coefficient model, the cutting force on the side edge and the bottom edge of the tool is calculated to obtain the cutting force data in the tool coordinate system.

[0007] Optionally, in a fourth implementation of the first aspect of the present invention, the multi-axis motion of the PCB milling machine is modeled according to the cutting force prediction result, the tool path data and the PCB processing model to obtain a multi-axis motion synchronization control model, including: According to the PCB processing model and the tool path data, a kinematic analysis is performed on the feed axis and the rotation axis of the PCB milling machine tool to obtain a first kinematic model of each axis, and the first kinematic model is corrected for the influence of the cutting force according to the cutting force prediction result to obtain a second dynamic model; According to the second dynamic model, the coupling effect between the axes of the PCB milling machine tool is analyzed to obtain an inter-axis coupling model; According to the inter-axis coupling model, the multi-axis motion of the PCB milling machine tool is interpolated and designed to obtain a multi-axis coordinated motion strategy; According to the multi-axis coordinated motion strategy, the dynamic model and the inter-axis coupling model, the multi-axis motion controller of the PCB milling machine tool is parameter designed to obtain a multi-axis motion synchronization control model.

[0008] Optionally, in a fifth implementation of the first aspect of the present invention, the kinematic analysis is performed on the feed axis and the rotation axis of the PCB milling machine according to the PCB processing model and the tool path data to obtain a first kinematic model of each axis, and the first kinematic model is corrected for the cutting force influence according to the cutting force prediction result to obtain a second dynamic model including: According to the PCB processing model, the motion range of the feed axis and the rotation axis of the PCB milling machine tool is analyzed to obtain the motion constraint conditions of each axis; According to the tool path data and the motion constraint conditions, the position, velocity and acceleration of each axis are calculated to obtain the kinematic equation of each axis to form a first kinematic model; Decomposing the cutting force prediction result to obtain cutting force components acting on each axis; According to the cutting force component, the first kinematic equation of each axis in the first kinematic model is corrected to obtain a second kinematic equation, and according to the second kinematic equation, a dynamic model of each axis is established to obtain a second dynamic model.

[0009] Optionally, in a sixth implementation of the first aspect of the present invention, the adaptive synchronous control of the multi-axis motion of the PCB milling machine tool according to the multi-axis motion synchronous control model and the cutting force prediction result includes: According to the cutting force prediction result, feedforward compensation calculation is performed on each axis of the PCB milling machine tool to obtain the feedforward compensation amount of each axis; According to the multi-axis motion synchronization control model, the actual position and speed of each axis of the PCB milling machine tool are measured in real time to obtain the actual motion state data of each axis; According to the actual motion state data and the theoretical trajectory, the tracking error of each axis of the PCB milling machine tool is calculated to obtain the tracking error data of each axis; Automatically adjusting the control parameters of each axis of the PCB milling machine tool according to the tracking error data and the feedforward compensation amount to obtain updated control parameters; According to the updated control parameters, each axis of the PCB milling machine is coordinated and controlled to obtain a multi-axis synchronous motion instruction, and the multi-axis synchronous motion instruction is sent to the control system of the PCB milling machine.

[0010] A second aspect of the present invention provides a multi-axis PCB milling synchronous control device, the multi-axis PCB milling synchronous control device comprising: A processing modeling module is used to perform geometric modeling on a PCB board and a tool on a PCB milling machine to obtain a PCB processing model, and to generate a tool path of the tool according to the PCB processing model to obtain tool path data; An entity extraction module, used for extracting the meshing state between the PCB board and the tool according to the tool path data, and obtaining a meshing geometric entity; A cutting force prediction module, used for calculating the instantaneous undeformed chip thickness between the PCB board and the tool according to the meshing geometric entity, and predicting the cutting force of the tool acting on the PCB board based on the instantaneous undeformed chip thickness to obtain a cutting force prediction result; A motion modeling module, used for modeling the multi-axis motion of the PCB milling machine according to the cutting force prediction result, the tool path data and the PCB processing model, to obtain a multi-axis motion synchronization control model; The control module is used to perform adaptive synchronous control on the multi-axis motion of the PCB milling machine according to the multi-axis motion synchronous control model and the cutting force prediction result.

[0011] The third aspect of the present invention provides a multi-axis PCB milling synchronous control device, comprising: a memory and at least one processor, wherein instructions are stored in the memory, and the memory and the at least one processor are interconnected through lines; the at least one processor calls the instructions in the memory so that the multi-axis PCB milling synchronous control device executes the steps of the above-mentioned multi-axis PCB milling synchronous control method.

[0012] A fourth aspect of the present invention provides a computer-readable storage medium, in which instructions are stored, which, when executed on a computer, enable the computer to execute the steps of the above-mentioned multi-axis PCB milling synchronization control method.

[0013] The above-mentioned multi-axis PCB milling synchronous control method, device, equipment and storage medium generate a PCB processing model by geometrically modeling the PCB board and the tool, and generate a tool path based on this, extract the meshing state of the tool and the PCB board, and obtain the meshing geometric entity. Subsequently, the instantaneous undeformed chip thickness is calculated according to the meshing geometric entity, and the cutting force of the tool acting on the PCB board is predicted. Based on the cutting force prediction results, tool path data and PCB processing model, the multi-axis motion of the PCB milling machine is modeled to generate a multi-axis motion synchronous control model. Finally, according to the synchronous control model and the cutting force prediction results, the multi-axis motion is adaptively synchronously controlled. The PCB milling method of the present invention predicts the cutting force in real time and performs adaptive synchronous control on the multi-axis machine tool to improve the processing accuracy, extend the tool life, and ensure the stability and consistency of the PCB processing process.

[0014] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0015] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of a first embodiment of a multi-axis PCB milling synchronization control method according to an embodiment of the present invention; Figure 2 A schematic diagram of an embodiment of a multi-axis PCB milling synchronization control device in an embodiment of the present invention; Figure 3 It is a schematic diagram of an embodiment of a multi-axis PCB milling synchronization control device in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] The terms "including" and "having" and any variations thereof mentioned in the embodiments of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device end including a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or device ends.

[0019] To facilitate understanding of this embodiment, a multi-axis PCB milling synchronization control method disclosed in an embodiment of the present invention is first introduced in detail. Figure 1 As shown, the method comprises the following steps: 101. Performing geometric modeling on a PCB board and a tool on a PCB milling machine to obtain a PCB processing model, and generating a tool path of the tool according to the PCB processing model to obtain tool path data; In one embodiment of the present invention, geometric modeling of a PCB board and a tool on a PCB milling machine to obtain a PCB processing model, and generating a tool path of the tool according to the PCB processing model to obtain tool path data includes: geometric modeling of a PCB board and a tool on a PCB milling machine to obtain a three-dimensional geometric model of the PCB board and the tool; constructing a workpiece coordinate system and a tool feed coordinate system according to the three-dimensional geometric models of the PCB board and the tool to obtain a processing coordinate system; generating a PCB processing model according to the three-dimensional geometric model of the PCB board, the three-dimensional geometric model of the tool and the processing coordinate system; generating a rough machining tool path of the tool according to the PCB processing model using a contour method, and generating a fine machining tool path according to the rough machining tool path using a surface matching algorithm to obtain an initial tool path; performing multi-objective optimization processing on the initial tool path to obtain optimized tool path data.

[0020] Specifically, in the process of geometrically modeling the PCB board and the tool on the PCB milling machine to obtain the three-dimensional geometric model of the PCB board and the tool, the PCB board is first modeled using a parametric modeling method. This includes defining the outer contour, thickness, hole layout and copper foil distribution of the PCB board. Using computer-aided design (CAD) software, a two-dimensional drawing of the PCB board is scanned or drawn, and then stretched into a three-dimensional model. For complex PCB board structures, Boolean operations may be required to add or remove specific geometric features. For the modeling of the tool, it is necessary to use parametric modeling technology to build a geometric model of the tool based on the actual parameters of the tool, such as diameter, number of blades, helix angle, tip arc radius, etc. This usually includes creating a contour curve of the tool and then generating a three-dimensional entity through rotation or scanning operations. For complex tool geometries, advanced surface modeling techniques, such as NURBS surfaces, may be required to accurately capture the geometric features of the tool.

[0021] Specifically, in the process of obtaining the machining coordinate system, first, select a feature point on the PCB board model as the origin of the workpiece coordinate system, usually a corner point of the PCB board. Then, define the X-axis and Y-axis of the workpiece coordinate system so that they are aligned with the main edges of the PCB board, and the Z-axis is perpendicular to the surface of the PCB board. For the tool feed coordinate system, the center point of the tool is selected as the origin, the axial direction of the tool is defined as the Z-axis, and the X-axis and Y-axis are determined according to the rotation direction of the tool. After defining these two coordinate systems, establish a transformation relationship between them, which usually involves the calculation of the rotation matrix and the translation vector. In addition, the mechanical structure of the machine tool needs to be considered to ensure that the defined coordinate system corresponds to the actual motion axis of the machine tool. Finally, integrate these coordinate system information into a mathematical model to form a complete machining coordinate system.

[0022] Specifically, the process of generating a PCB processing model first converts the geometric information of the PCB board and the tool into a unified processing coordinate system. Then, according to the characteristics of the PCB board material (such as hardness, thermal conductivity) and the parameters of the tool (such as material, coating), select appropriate cutting parameters, including cutting speed, feed rate and cutting depth. These parameters are usually obtained by querying the processing database or using empirical formulas. Next, according to the geometric characteristics and processing requirements of the PCB board, the processing area is divided to determine the range of rough processing and fine processing. At the same time, considering the performance limitations of the machine tool, such as the maximum spindle speed, maximum feed rate, etc., the processing parameters are adjusted. Finally, all this information is integrated into a data structure to form a complete PCB processing model.

[0023] Specifically, according to the PCB processing model, the rough machining tool path of the tool is generated by the contour method, and the finishing tool path is generated according to the rough machining tool path using the surface matching algorithm. In the process of obtaining the initial tool path, based on the three-dimensional model of the PCB board, a series of parallel planes are generated at fixed intervals in the Z-axis direction, and the intersection lines of these planes and the surface of the PCB board form contour lines. Then, these contour lines are converted into the trajectory of the tool center point to form a rough machining path. For the finishing path, a surface matching algorithm, such as the equal parameter method or the equal pitch method of the spherical milling cutter, is used to generate a tool path that can ensure machining accuracy according to the curvature change of the PCB board surface. This process involves complex mathematical calculations, including the calculation of the surface normal vector, the contact analysis between the tool and the workpiece surface, etc. Finally, the rough machining and finishing paths are combined to form a complete initial tool path. The initial tool path is subjected to multi-objective optimization processing, and the process of obtaining the optimized tool path data involves the balance of multiple optimization objectives. First, an optimization model is established, including objective functions (such as minimizing machining time, maximizing surface quality, minimizing tool wear) and constraints (such as machining accuracy requirements, machine tool performance limitations).

[0024] 102. Extracting the meshing state between the PCB board and the tool according to the tool path data to obtain a meshing geometric entity; In one embodiment of the present invention, extracting the meshing state between the PCB board and the tool according to the tool path data to obtain the meshing geometric entity includes: searching for historical tool position points adjacent to the current tool position point of the tool according to the tool path data to obtain a local historical tool position point set; reconstructing the local excision material of the PCB board according to the local historical tool position point set to obtain a local excision material geometric entity; acquiring the current tool entity of the tool and the PCB board entity of the PCB board according to the PCB processing model, and performing local Boolean operations on the current tool entity, the PCB board entity and the local excision material geometric entity to obtain an initial meshing geometric entity; performing orthogonal plane projection on the initial meshing geometric entity to obtain a side edge cutting state projection diagram and a bottom edge cutting state projection diagram, and performing two-dimensional image mapping to obtain a meshing geometric entity.

[0025] Specifically, when searching for historical tool position points adjacent to the current tool position point based on the tool path data, it is first necessary to traverse the entire tool path data and set a search radius with the current tool position point as the center. This search radius is usually twice the tool diameter to ensure that all historical position points that may affect the current cutting state are captured. During the search process, the Euclidean distance from each historical position point to the current position point is calculated, while considering the angle of the tool axial vector. If the distance is less than the search radius and the axial angle is less than the preset threshold, the historical position point is added to the local historical tool position point set. In addition, the displacement of the tool in the Z-axis direction needs to be considered to ensure that the selected historical position point has an impact on the current cutting state in the Z direction. Finally, the screened position points are sorted in chronological order to form a complete local historical tool position point set.

[0026] Specifically, the local cut material of the PCB board is reconstructed based on the set of local historical tool position points. This process first requires converting each historical tool position point into a corresponding tool swept volume. For each position point, a cylinder or a more complex geometry is generated based on the geometric model and position information of the tool to represent the cutting range of the tool at that position. Then, these swept volumes are Booleaned to obtain a composite geometry representing all historical cutting areas. This process involves complex computational geometry algorithms, such as constructive solid geometry (CSG) or boundary representation (B-rep) technology. During the reconstruction process, attention should be paid to handling overlapping areas and boundary transitions to ensure that the generated geometry can accurately represent the cut material. Finally, this composite geometry is Boolean subtracted from the original model of the PCB board to obtain a local cut material geometry entity, which represents the shape of the material cut by the tool in the local area of ​​the PCB board.

[0027] Specifically, the current tool entity and PCB board entity are obtained according to the PCB processing model, and local Boolean operations are performed on the current tool entity, PCB board entity and local cut material geometric entity. First, the geometric information and position information of the current tool are extracted from the PCB processing model to construct the current tool entity. At the same time, the latest geometric model of the PCB board is obtained as the PCB board entity. Then, a series of Boolean operations are performed: first, the PCB board entity is Boolean subtracted from the local cut material geometric entity to obtain the updated PCB board entity; then, the updated PCB board entity is Boolean intersected with the current tool entity. This process requires the use of efficient computational geometry algorithms, such as octree decomposition or space partitioning technology, to accelerate the Boolean operation process. The result of the operation is the initial meshing geometric entity, which accurately represents the interaction area between the tool and the PCB board at the current moment.

[0028] Specifically, the initial meshing geometric entity is projected on an orthogonal plane to obtain the projection diagram of the side cutting state and the bottom cutting state, and two-dimensional image mapping is performed. First, two orthogonal planes are selected: one is parallel to the tool axis to obtain the side cutting state; the other is perpendicular to the tool axis to obtain the bottom cutting state. The initial meshing geometric entity is projected onto these two planes to obtain two two-dimensional projection diagrams. Then, the two projection diagrams are rasterized to convert continuous geometric shapes into discrete pixel matrices. In the rasterization process, an appropriate resolution needs to be selected to balance computational efficiency and accuracy. Next, the rasterized image is binarized, and the meshing area is marked as 1 and the non-meshing area is marked as 0. Finally, based on these two binary images, the meshing state of each cutting point on the tool is calculated using an interpolation algorithm to form a complete meshing geometric entity description. This process can not only quickly obtain meshing state information, but also provide necessary input data for subsequent cutting force calculations.

[0029] 103. Calculating the instantaneous undeformed chip thickness between the PCB board and the tool according to the meshing geometric entity, and predicting the cutting force of the tool acting on the PCB board based on the instantaneous undeformed chip thickness to obtain a cutting force prediction result; In one embodiment of the present invention, the instantaneous undeformed chip thickness between the PCB board and the tool is calculated according to the meshing geometric entity based on the cutting force prediction result, and the cutting force of the tool acting on the PCB board is predicted based on the instantaneous undeformed chip thickness, and obtaining the cutting force prediction result includes: decomposing the feed motion between adjacent tool position points in the tool path data to obtain the translational motion components along the X-axis and Z-axis of the tool feed coordinate system and the rotational motion components around the Y-axis; calculating the instantaneous undeformed chip thickness between the PCB board and the tool according to the translational motion components, the rotational motion components, the meshing geometric entity and the material parameters of the PCB board; calculating the cutting force on the side edge and the bottom edge of the tool according to the instantaneous undeformed chip thickness and a preset cutting force coefficient model to obtain the cutting force data in the tool coordinate system.

[0030] Specifically, when decomposing the feed motion between adjacent tool position points in the tool path data, it is first necessary to extract two consecutive tool position points and their corresponding tool axial vectors from the tool path data. Then, the displacement vector between the two position points is calculated and projected onto the X-axis and Z-axis of the tool feed coordinate system to obtain the translational motion component. This process involves dot product and cross product operations of vectors. At the same time, by calculating the angle between the tool axial vectors at the two position points, the rotation angle around the Y-axis is obtained, thereby determining the rotational motion component. For five-axis machining, changes in tool posture also need to be considered, involving more complex coordinate transformations and rotation matrix calculations. Finally, these motion components are expressed as functions of time to facilitate subsequent calculations of the instantaneous undeformed chip thickness.

[0031] Specifically, when calculating the instantaneous undeformed chip thickness between the PCB board and the tool based on the translational motion component, the rotational motion component, the meshing geometric entity and the material parameters of the PCB board, the meshing geometric entity needs to be discretized into a series of cutting points first. For each cutting point, according to its position on the tool, the motion component obtained by the previous decomposition is used to calculate the motion trajectory of the point within a tooth cycle. Then, this trajectory is compared with the current surface of the PCB board to calculate the distance between the cutting point and the workpiece surface. This distance is the instantaneous undeformed chip thickness. In the calculation process, the characteristics of the PCB board material, such as elastic deformation and plastic deformation, need to be considered, which may affect the actual cutting thickness. For complex PCB board surfaces, numerical integration methods may be required to accurately calculate the chip thickness. In addition, the geometric characteristics of the tool, such as the helix angle and the radius of the tool tip arc, also need to be considered, which will affect the actual cutting thickness distribution.

[0032] Specifically, according to the instantaneous undeformed chip thickness and the preset cutting force coefficient model, the cutting force on the side edge and bottom edge of the tool is calculated to obtain the cutting force data in the tool coordinate system. This process first requires the selection of an appropriate cutting force model, such as a mechanical cutting force model or an empirical cutting force model. For PCB milling, a piecewise linear cutting force model is usually used, which divides the cutting force into a cutting component and a plowing component. Then, for each discrete cutting point, the tangential force, radial force and axial force are calculated according to its instantaneous undeformed chip thickness and cutting force coefficient. The calculation of these forces needs to consider the characteristics of the PCB material and the geometric parameters of the tool. For the side edge of the tool, the tangential force and radial force are mainly considered; for the bottom edge, the axial force needs to be additionally considered. The calculated forces on each cutting point need to be vector superimposed to obtain the resultant force acting on the entire tool. Finally, these forces are converted from the cutting coordinate system to the tool coordinate system to obtain the final cutting force data.

[0033] 104. Modeling the multi-axis motion of the PCB milling machine tool according to the cutting force prediction result, the tool path data and the PCB processing model to obtain a multi-axis motion synchronization control model; In one embodiment of the present invention, the multi-axis motion of the PCB milling machine is modeled according to the cutting force prediction result, the tool path data and the PCB processing model to obtain a multi-axis motion synchronization control model, including: performing kinematic analysis on the feed axis and the rotation axis of the PCB milling machine according to the PCB processing model and the tool path data to obtain a first kinematic model of each axis, and performing cutting force influence correction on the first kinematic model according to the cutting force prediction result to obtain a second dynamic model; analyzing the coupling effect between the axes of the PCB milling machine according to the second dynamic model to obtain an inter-axis coupling model; performing interpolation design on the multi-axis motion of the PCB milling machine according to the inter-axis coupling model to obtain a multi-axis coordinated motion strategy; performing parameter design on the multi-axis motion controller of the PCB milling machine according to the multi-axis coordinated motion strategy, the dynamic model and the inter-axis coupling model to obtain a multi-axis motion synchronization control model.

[0034] Specifically, when performing kinematic analysis on the feed axis and rotary axis of a PCB milling machine tool based on the PCB processing model and tool path data, it is first necessary to establish a geometric model of the machine tool, including the range of motion, limit and initial position of each axis. Then, based on the tool path data, calculate the position, velocity and acceleration of each axis at each time point. This process involves complex coordinate transformations and needs to consider the kinematic structure of the machine tool, such as the series or parallel structure. For five-axis machine tools, it is also necessary to solve the inverse problem, that is, to reverse the motion parameters of each axis from the tool position and posture. After obtaining the motion parameters of each axis, mathematical equations describing the motion of each axis are established, and these equations constitute the first kinematic model. Next, the first kinematic model is corrected according to the cutting force prediction results. This step needs to consider the influence of cutting force on the motion of each axis, including static deformation and dynamic response. By converting the cutting force into equivalent force and torque on each axis, and then using the stiffness and damping characteristics of the machine tool structure, the displacement and vibration response of each axis are calculated. These responses are integrated into the kinematic equation to form a second dynamic model that considers the influence of cutting force.

[0035] Specifically, when analyzing the coupling effect between the axes of the PCB milling machine tool according to the second dynamic model, it is necessary to consider two aspects: geometric coupling and dynamic coupling. Geometric coupling mainly originates from the kinematic structure of the machine tool. For example, the movement of the rotating axis in a five-axis machine tool will cause the position change of the linear axis. This coupling can be described by establishing a mathematical model of the position relationship between the axes. Dynamic coupling originates from the force and vibration transmission during the cutting process, as well as the elastic deformation of the machine tool structure. In order to analyze the dynamic coupling, it is necessary to establish a finite element model of the machine tool structure or a simplified mass-spring-damper model, and then determine the dynamic interaction between the axes through modal analysis and frequency response function analysis. On this basis, a mathematical model describing the coupling relationship between axes is established. This model usually contains a series of differential equations or state space equations. Finally, the effects of geometric coupling and dynamic coupling are combined to form a complete inter-axis coupling model.

[0036] Specifically, when interpolating the multi-axis motion of the PCB milling machine tool according to the inter-axis coupling model, it is first necessary to determine the interpolation target point based on the tool path data. Then, considering the inter-axis coupling effect, a suitable interpolation algorithm is designed. For linear interpolation, the improved digital differential analysis (DDA) algorithm or the Bresenham algorithm can be used; for curve interpolation, parameter interpolation or spline interpolation can be used. During the interpolation process, it is necessary to consider the motion characteristics of each axis, such as the maximum speed, acceleration and jerk limits, as well as the mutual influence caused by the inter-axis coupling. At the same time, it is also necessary to design a speed planning algorithm to ensure the smoothness and accuracy of the motion. For five-axis machining, it is also necessary to consider the change of tool posture, which involves advanced technologies such as NURBS interpolation or rotation matrix interpolation. Finally, the interpolation algorithm and the speed planning algorithm are combined to form a complete multi-axis coordinated motion strategy.

[0037] Specifically, when designing the parameters of the multi-axis motion controller of the PCB milling machine tool according to the multi-axis coordinated motion strategy, dynamic model and inter-axis coupling model, it is necessary to first determine the structure of the controller. Commonly used controllers include PID controller, feedforward controller and adaptive controller. Then, according to the dynamic model and inter-axis coupling model, the parameter tuning method of the controller is designed. For the PID controller, the Ziegler-Nichols method or the pole configuration method can be used for preliminary tuning, and then optimized through simulation and experiment. For the feedforward controller, it is necessary to design the velocity feedforward and acceleration feedforward according to the dynamic model. The adaptive controller needs to design an automatic parameter adjustment mechanism to adapt to changes in cutting conditions. In the parameter design process, it is necessary to consider the stability, response speed and anti-interference ability of the system. At the same time, it is also necessary to design an inter-axis coordinated control strategy to reduce the synchronization error. Finally, the various controller modules are integrated to form a complete multi-axis motion synchronization control model, which should be able to achieve high-precision and high-efficiency PCB milling processing.

[0038] Furthermore, the kinematic analysis of the feed axis and the rotating axis of the PCB milling machine is performed according to the PCB processing model and the tool path data to obtain a first kinematic model of each axis, and the first kinematic model is corrected for the influence of the cutting force according to the cutting force prediction result to obtain a second dynamic model, including: analyzing the motion range of the feed axis and the rotating axis of the PCB milling machine according to the PCB processing model to obtain the motion constraint conditions of each axis; calculating the position, speed and acceleration of each axis according to the tool path data and the motion constraint conditions to obtain the kinematic equation of each axis to form a first kinematic model; decomposing the cutting force prediction result to obtain the cutting force component acting on each axis; correcting the first kinematic equation of each axis in the first kinematic model according to the cutting force component to obtain a second motion equation, and establishing a dynamic model of each axis according to the second motion equation to obtain a second dynamic model.

[0039] Specifically, when analyzing the motion range of the feed axis and rotary axis of the PCB milling machine tool according to the PCB processing model, it is first necessary to extract the geometric information and processing requirements of the workpiece from the PCB processing model. This includes the size of the PCB board, the location of the processing area, and the required processing accuracy. Then, combined with the structural parameters of the machine tool, such as the worktable size, spindle travel, etc., the motion limits of each axis are determined. For the feed axis, it is usually necessary to consider the travel limits in the three directions of X, Y, and Z; for the rotary axis, it is necessary to determine the rotation angle range of the B axis and the C axis. In addition, the mechanical limit, soft limit, and interference relationship between the axes of the machine tool need to be considered. By analyzing these factors, a set of mathematical inequalities can be obtained to describe the motion constraints of each axis. These constraints will play an important role in subsequent motion planning and control to ensure that the machine tool moves within a safe and effective range.

[0040] Specifically, when calculating the position, velocity, and acceleration of each axis based on the tool path data and motion constraints, the tool path data must first be converted into a position sequence in the machine coordinate system. For a five-axis machine tool, this process involves complex coordinate transformations that require consideration of the position and posture of the tool. Then, the velocity and acceleration of each axis are calculated based on the time interval between adjacent position points. During the calculation process, the motion constraints obtained previously must be considered to ensure that the calculation results do not exceed the allowable range. For situations that exceed the range, path replanning or velocity adjustment is required. Next, the calculated position, velocity, and acceleration data are used to establish mathematical equations that describe the motion of each axis. These equations are usually in the form of second-order differential equations, which contain parameters such as mass, damping, and stiffness. Finally, the motion equations of all axes are combined to form a complete matrix equation, which constitutes the first kinematic model.

[0041] Specifically, when decomposing the cutting force prediction results to obtain the cutting force components acting on each axis, it is first necessary to convert the cutting force prediction results in the workpiece coordinate system to the machine tool coordinate system. This process involves the calculation of coordinate transformation and rotation matrices. Then, according to the kinematic structure of the machine tool, the cutting force is decomposed into each axis. For the feed axis, the force component along the axis direction is mainly considered; for the rotation axis, the torque component needs to be calculated. In the decomposition process, the current position and posture of the tool need to be considered, because these factors affect the force transmission path. In addition, the stiffness distribution of the machine tool structure needs to be considered, because the difference in stiffness at different positions will lead to uneven force distribution. Finally, a vector containing the force or torque components acting on each axis is obtained. This vector will be used for subsequent dynamic model correction.

[0042] Specifically, when the first kinematic equations of each axis in the first kinematic model are modified according to the cutting force components, the cutting force components must first be converted into equivalent external excitations. This process involves the dynamic characteristics of the machine tool structure, such as mass distribution, stiffness, and damping. These external excitation terms are then added to the first kinematic equations to form the second kinematic equations that include the effects of the cutting forces. These equations are usually nonlinear because the cutting forces are related to position, velocity, and acceleration. Next, based on the second kinematic equations, the dynamic models of each axis are established. This process involves converting the equations of motion into state space representation or transfer function form. During the modeling process, the coupling effects between the axes need to be considered, resulting in the appearance of cross terms. Finally, the dynamic models of all axes are combined to form a complete multi-input multi-output (MIMO) system, which is the final second dynamic model. This model not only includes the kinematic characteristics of the machine tool, but also considers the dynamic effects during the cutting process, and can more accurately describe the behavior of the machine tool during PCB milling.

[0043] 105. According to the multi-axis motion synchronization control model and the cutting force prediction result, adaptive synchronization control is performed on the multi-axis motion of the PCB milling machine.

[0044] In one embodiment of the present invention, the adaptive synchronous control of the multi-axis motion of the PCB milling machine tool according to the multi-axis motion synchronous control model and the cutting force prediction result includes: performing feedforward compensation calculation on each axis of the PCB milling machine tool according to the cutting force prediction result to obtain the feedforward compensation amount of each axis; performing real-time measurement of the actual position and speed of each axis of the PCB milling machine tool according to the multi-axis motion synchronous control model to obtain the actual motion state data of each axis; calculating the tracking error of each axis of the PCB milling machine tool according to the actual motion state data and the theoretical trajectory to obtain the tracking error data of each axis; automatically adjusting the control parameters of each axis of the PCB milling machine tool according to the tracking error data and the feedforward compensation amount to obtain updated control parameters; and coordinating the axes of the PCB milling machine tool according to the updated control parameters to obtain multi-axis synchronous motion instructions, and sending the multi-axis synchronous motion instructions to the control system of the PCB milling machine tool.

[0045] Specifically, when performing feedforward compensation calculations on each axis of a PCB milling machine tool based on the cutting force prediction results, it is first necessary to convert the cutting force prediction results into the machine tool coordinate system. Then, the influence of the cutting force on the motion of each axis is calculated using the dynamic model of the machine tool. This process involves solving the dynamic equations, which usually requires the use of numerical integration methods such as the Runge-Kutta method. The calculated motion deviation is the feedforward compensation amount for each axis. For linear axes, feedforward compensation is mainly reflected in position and speed; for rotary axes, compensation for angles and angular velocity also needs to be considered. The purpose of feedforward compensation is to offset the disturbance caused by the cutting force in advance, thereby improving machining accuracy. During the calculation process, the dynamic characteristics of the machine tool, such as the natural frequency and damping ratio, also need to be considered to ensure that the compensation signal does not excite the resonance of the machine tool.

[0046] Specifically, when the actual position and speed of each axis of the PCB milling machine tool are measured in real time according to the multi-axis motion synchronization control model, various sensors on the machine tool need to be used. For linear axes, grating scales or magnetic scales are usually used to measure the position, and the speed information is obtained by differentiating the position signal. For rotary axes, rotary encoders are used to measure the angle, and the angular velocity is also obtained by differentiation. The resolution and sampling frequency of the sensor need to be considered during the measurement process to ensure measurement accuracy and real-time performance. At the same time, signal filtering and data fusion are also required to reduce the impact of measurement noise. The measured data needs to be converted to the workpiece coordinate system through the kinematic model of the machine tool for comparison with the theoretical trajectory. This process involves complex coordinate transformation and rotation matrix calculation, especially for five-axis machine tools. Finally, the actual motion state data of each axis is obtained, including position, velocity, and acceleration information.

[0047] Specifically, when calculating the tracking errors of each axis of the PCB milling machine tool based on the actual motion state data and the theoretical trajectory, it is first necessary to discretize the theoretical trajectory and correspond it to the time point of the actual measurement data. Then, for each time point, the difference between the actual position and the theoretical position is calculated, which is the position tracking error. Similarly, by comparing the actual speed with the theoretical speed, the speed tracking error is obtained. For five-axis machine tools, it is also necessary to calculate the tracking error of the tool posture, which involves the operation of the rotation matrix or quaternion. In the calculation process, the coupling effect between different axes needs to be considered, because the error of one axis may affect the movement of other axes. In addition, it is necessary to calculate the statistical characteristics of the tracking error, such as the root mean square error and the maximum error, to comprehensively evaluate the processing accuracy. Finally, the tracking error data of all axes are integrated into a vector or matrix as the basis for subsequent control parameter adjustment.

[0048] Specifically, when automatically adjusting the control parameters of each axis of the PCB milling machine tool based on the tracking error data and the feedforward compensation, an adaptive control algorithm needs to be established first. Commonly used algorithms include model reference adaptive control (MRAC) and self-correcting control (STC). These algorithms dynamically adjust the controller parameters by comparing the actual system output with the ideal model output. During the adjustment process, the influence of the feedforward compensation needs to be considered because feedforward control and feedback control cooperate with each other. For PID controllers, the three main parameters of proportion, integration and differentiation need to be adjusted; for more complex controllers, the state feedback gain or observer parameters also need to be adjusted. During the parameter adjustment process, the stability of the system needs to be guaranteed, and the Lyapunov stability theory is usually used to design the parameter adjustment law. At the same time, the upper and lower limits of the parameter changes need to be set to prevent excessive adjustment from causing system instability. Finally, a set of updated control parameters are obtained, which can better adapt to the current processing conditions.

[0049] Specifically, when coordinating the axes of a PCB milling machine tool according to the updated control parameters, it is first necessary to generate the theoretical trajectory of each axis according to the tool path. Then, using the updated control parameters, the control output of each axis is calculated. This process usually involves solving the equations of a multiple-input multiple-output (MIMO) control system. For linear axes, the control output is usually a force or torque; for rotary axes, it is an angular acceleration or angular velocity. While generating the control output, it is necessary to consider the synchronization between the axes to ensure that the motion of each axis is coordinated. This is usually achieved by designing a multi-axis interpolation algorithm, such as NURBS interpolation or spline interpolation. The interpolation algorithm needs to consider the motion constraints of each axis, such as maximum velocity, acceleration, and jerk limits. Finally, the calculated control output is converted into a motor drive signal, such as a PWM signal or an analog voltage signal, and sent to the machine tool control system through a communication interface. This process needs to consider communication delays and data transmission rates to ensure that control instructions can be executed in a timely manner.

[0050] In this embodiment, a PCB processing model is generated by geometrically modeling the PCB board and the tool, and a tool path is generated based on the model, the meshing state of the tool and the PCB board is extracted, and the meshing geometric entity is obtained. Subsequently, the instantaneous undeformed chip thickness is calculated based on the meshing geometric entity, and the cutting force of the tool acting on the PCB board is predicted. Based on the cutting force prediction results, the tool path data and the PCB processing model, the multi-axis motion of the PCB milling machine is modeled, and a multi-axis motion synchronous control model is generated. Finally, according to the synchronous control model and the cutting force prediction results, the multi-axis motion is adaptively synchronously controlled. The PCB milling method of the present invention predicts the cutting force in real time and performs adaptive synchronous control on the multi-axis machine tool to improve the processing accuracy, extend the tool life, and ensure the stability and consistency of the PCB processing process.

[0051] The above describes the multi-axis PCB milling synchronization control method in the embodiment of the present invention. The following describes the multi-axis PCB milling synchronization control device in the embodiment of the present invention. Figure 2 , an embodiment of the multi-axis PCB milling synchronization control device in the embodiment of the present invention includes: The processing modeling module 201 is used to perform geometric modeling on the PCB board and the tool on the PCB milling machine to obtain a PCB processing model, and generate a tool path of the tool according to the PCB processing model to obtain tool path data; The entity extraction module 202 is used to extract the meshing state between the PCB board and the tool according to the tool path data to obtain the meshing geometric entity; A cutting force prediction module 203 is used to calculate the instantaneous undeformed chip thickness between the PCB board and the tool according to the meshing geometric entity, and predict the cutting force of the tool acting on the PCB board based on the instantaneous undeformed chip thickness to obtain a cutting force prediction result; A motion modeling module 204 is used to model the multi-axis motion of the PCB milling machine according to the cutting force prediction result, the tool path data and the PCB processing model to obtain a multi-axis motion synchronization control model; The control module is used to perform adaptive synchronous control on the multi-axis motion of the PCB milling machine according to the multi-axis motion synchronous control model and the cutting force prediction result.

[0052] In an embodiment of the present invention, the multi-axis PCB milling synchronous control device runs the multi-axis PCB milling synchronous control method, and the multi-axis PCB milling synchronous control device performs geometric modeling on the PCB board and the tool, generates a PCB processing model, and generates a tool path based on this, extracts the meshing state of the tool and the PCB board, and obtains the meshing geometric entity. Subsequently, the instantaneous undeformed chip thickness is calculated according to the meshing geometric entity, and the cutting force of the tool acting on the PCB board is predicted. Based on the cutting force prediction result, the tool path data and the PCB processing model, the multi-axis motion of the PCB milling machine tool is modeled, and a multi-axis motion synchronous control model is generated. Finally, according to the synchronous control model and the cutting force prediction result, the multi-axis motion is adaptively synchronously controlled. The PCB milling method of the present invention predicts the cutting force in real time and performs adaptive synchronous control on the multi-axis machine tool to improve the processing accuracy, extend the tool life, and ensure the stability and consistency of the PCB processing process.

[0053] above Figure 2 The multi-axis PCB milling synchronization control device in the embodiment of the present invention is described in detail from the perspective of modular functional entities. The multi-axis PCB milling synchronization control device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0054] Figure 3 1 is a schematic diagram of the structure of a multi-axis PCB milling synchronous control device provided by an embodiment of the present invention. The multi-axis PCB milling synchronous control device 300 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 310 (for example, one or more processors) and a memory 320, and one or more storage media 330 (for example, one or more mass storage device terminals) storing application programs 333 or data 332. Among them, the memory 320 and the storage medium 330 can be short-term storage or permanent storage. The program stored in the storage medium 330 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the multi-axis PCB milling synchronous control device 300. Furthermore, the processor 310 can be configured to communicate with the storage medium 330, and execute a series of instruction operations in the storage medium 330 on the multi-axis PCB milling synchronous control device 300 to implement the steps of the multi-axis PCB milling synchronous control method described above.

[0055] The multi-axis PCB milling synchronous control device 300 may also include one or more power supplies 340, one or more wired or wireless network interfaces 350, one or more input and output interfaces 360, and / or one or more operating systems 331, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. It can be understood by those skilled in the art that Figure 3 The structure of the multi-axis PCB milling synchronous control device shown does not constitute a limitation on the multi-axis PCB milling synchronous control device provided by the present invention, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0056] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the multi-axis PCB milling synchronization control method.

[0057] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device, or unit can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0058] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0059] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-axis PCB milling synchronous control method, characterized in that: The multi-axis PCB milling synchronous control method comprises: Performing geometric modeling on the PCB board and the tool on the PCB milling machine to obtain a PCB processing model, and generating a tool path of the tool according to the PCB processing model to obtain tool path data; Extracting the meshing state between the PCB board and the tool according to the tool path data to obtain a meshing geometric entity; Calculating the instantaneous undeformed chip thickness between the PCB board and the tool according to the meshing geometric entity, and predicting the cutting force of the tool acting on the PCB board based on the instantaneous undeformed chip thickness to obtain a cutting force prediction result; Modeling the multi-axis motion of the PCB milling machine tool according to the cutting force prediction result, the tool path data and the PCB processing model to obtain a multi-axis motion synchronization control model; According to the multi-axis motion synchronous control model and the cutting force prediction result, the multi-axis motion of the PCB milling machine tool is adaptively synchronously controlled.

2. The multi-axis PCB milling synchronous control method according to claim 1, characterized in that: The step of geometrically modeling the PCB board and the tool on the PCB milling machine to obtain a PCB processing model, and generating a tool path of the tool according to the PCB processing model to obtain tool path data includes: Performing geometric modeling on a PCB board and a tool on a PCB milling machine to obtain a three-dimensional geometric model of the PCB board and the tool; According to the three-dimensional geometric models of the PCB board and the tool, a workpiece coordinate system and a tool feed coordinate system are constructed to obtain a processing coordinate system; Generate a PCB processing model according to the three-dimensional geometric model of the PCB board, the three-dimensional geometric model of the tool and the processing coordinate system; According to the PCB processing model, a rough machining tool path of the tool is generated by using a contour method, and a fine machining tool path is generated according to the rough machining tool path by using a surface matching algorithm to obtain an initial tool path; The initial tool path is subjected to multi-objective optimization processing to obtain optimized tool path data.

3. The multi-axis PCB milling synchronous control method according to claim 1, characterized in that: The extracting the meshing state between the PCB board and the tool according to the tool path data to obtain the meshing geometric entity comprises: According to the tool path data, searching for historical tool position points adjacent to the current tool position point of the tool to obtain a local historical tool position point set; Reconstructing the local cutout material of the PCB board according to the local historical tool position point set to obtain a local cutout material geometric entity; Acquire the current tool entity of the tool and the PCB board entity of the PCB board according to the PCB processing model, and perform local Boolean operation on the current tool entity, the PCB board entity and the local cut material geometric entity to obtain an initial meshing geometric entity; Orthogonal plane projection is performed on the initial meshing geometric entity to obtain a side edge cutting state projection diagram and a bottom edge cutting state projection diagram, and two-dimensional image mapping is performed to obtain a meshing geometric entity.

4. The multi-axis PCB milling synchronous control method according to claim 1, characterized in that: The calculating the instantaneous undeformed chip thickness between the PCB board and the tool according to the meshing geometric entity, and predicting the cutting force of the tool acting on the PCB board based on the instantaneous undeformed chip thickness, to obtain the cutting force prediction result includes: Decomposing the feed motion between adjacent tool position points in the tool path data to obtain translation motion components along the X-axis and Z-axis of the tool feed coordinate system and a rotation motion component around the Y-axis; Calculating the instantaneous undeformed chip thickness between the PCB and the tool according to the translational motion component, the rotational motion component, the meshing geometric entity and the material parameters of the PCB; According to the instantaneous undeformed chip thickness and a preset cutting force coefficient model, the cutting force on the side edge and the bottom edge of the tool is calculated to obtain the cutting force data in the tool coordinate system.

5. The multi-axis PCB milling synchronous control method according to claim 1, characterized in that: The multi-axis motion of the PCB milling machine tool is modeled according to the cutting force prediction result, the tool path data and the PCB processing model to obtain a multi-axis motion synchronization control model, which includes: According to the PCB processing model and the tool path data, a kinematic analysis is performed on the feed axis and the rotation axis of the PCB milling machine tool to obtain a first kinematic model of each axis, and the first kinematic model is corrected for the influence of the cutting force according to the cutting force prediction result to obtain a second dynamic model; According to the second dynamic model, the coupling effect between the axes of the PCB milling machine tool is analyzed to obtain an inter-axis coupling model; According to the inter-axis coupling model, the multi-axis motion of the PCB milling machine tool is interpolated and designed to obtain a multi-axis coordinated motion strategy; According to the multi-axis coordinated motion strategy, the dynamic model and the inter-axis coupling model, the multi-axis motion controller of the PCB milling machine tool is parameter designed to obtain a multi-axis motion synchronization control model.

6. The multi-axis PCB milling synchronous control method according to claim 5, characterized in that: The kinematic analysis of the feed axis and the rotation axis of the PCB milling machine tool is performed according to the PCB processing model and the tool path data to obtain a first kinematic model of each axis, and the first kinematic model is corrected for the cutting force influence according to the cutting force prediction result to obtain a second dynamic model, including: According to the PCB processing model, the motion range of the feed axis and the rotation axis of the PCB milling machine tool is analyzed to obtain the motion constraint conditions of each axis; According to the tool path data and the motion constraint conditions, the position, velocity and acceleration of each axis are calculated to obtain the kinematic equation of each axis to form a first kinematic model; Decomposing the cutting force prediction result to obtain cutting force components acting on each axis; According to the cutting force component, the first kinematic equation of each axis in the first kinematic model is corrected to obtain a second kinematic equation, and according to the second kinematic equation, a dynamic model of each axis is established to obtain a second dynamic model.

7. The multi-axis PCB milling synchronous control method according to claim 1, characterized in that: The adaptive synchronous control of the multi-axis motion of the PCB milling machine tool according to the multi-axis motion synchronous control model and the cutting force prediction result includes: According to the cutting force prediction result, feedforward compensation calculation is performed on each axis of the PCB milling machine tool to obtain the feedforward compensation amount of each axis; According to the multi-axis motion synchronization control model, the actual position and speed of each axis of the PCB milling machine tool are measured in real time to obtain the actual motion state data of each axis; According to the actual motion state data and the theoretical trajectory, the tracking error of each axis of the PCB milling machine tool is calculated to obtain the tracking error data of each axis; Automatically adjusting the control parameters of each axis of the PCB milling machine tool according to the tracking error data and the feedforward compensation amount to obtain updated control parameters; According to the updated control parameters, each axis of the PCB milling machine is coordinated and controlled to obtain a multi-axis synchronous motion instruction, and the multi-axis synchronous motion instruction is sent to the control system of the PCB milling machine.

8. A multi-axis PCB milling synchronous control device, characterized in that: The multi-axis PCB milling synchronous control device comprises: A processing modeling module is used to perform geometric modeling on a PCB board and a tool on a PCB milling machine to obtain a PCB processing model, and to generate a tool path of the tool according to the PCB processing model to obtain tool path data; An entity extraction module, used for extracting the meshing state between the PCB board and the tool according to the tool path data, and obtaining a meshing geometric entity; A cutting force prediction module, used for calculating the instantaneous undeformed chip thickness between the PCB board and the tool according to the meshing geometric entity, and predicting the cutting force of the tool acting on the PCB board based on the instantaneous undeformed chip thickness to obtain a cutting force prediction result; A motion modeling module, used for modeling the multi-axis motion of the PCB milling machine according to the cutting force prediction result, the tool path data and the PCB processing model, to obtain a multi-axis motion synchronization control model; The control module is used to perform adaptive synchronous control on the multi-axis motion of the PCB milling machine according to the multi-axis motion synchronous control model and the cutting force prediction result.

9. A multi-axis PCB milling synchronous control device, characterized in that: The multi-axis PCB milling synchronous control device comprises: a memory and at least one processor, wherein instructions are stored in the memory; The at least one processor calls the instructions in the memory so that the multi-axis PCB milling synchronization control device executes the steps of the multi-axis PCB milling synchronization control method as described in any one of claims 1-7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the steps of the multi-axis PCB milling synchronization control method as described in any one of claims 1-7 are implemented.

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