A control planning method and device for a five-axis hybrid machine tool

Abstract

The application provides a control planning method and device of a five-axis hybrid machine tool, and relates to the technical field of hybrid machine tools. The speed mapping relationship between tool movement and driving shafts is established, and the planning is combined with the double non-uniform rational B spline model of the tool path, so that high-precision matching of tool movement and driving shaft movement is realized. The method can smoothly express and interpolate the machining path of a complex surface while considering the performance constraints of the driving shafts, ensure the continuity of the tool path and the stability of the machining process, and improve the machining accuracy and the efficiency of the machine tool.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of hybrid machine tools, in particular to a control planning method and device for a five-axis hybrid machine tool. BACKGROUND

[0002] With the increasing requirements of manufacturing industry on part processing precision and complexity, the traditional machine tool structure is difficult to meet the demand. The five-axis hybrid machine tool emerges as the times require, which combines the characteristics of high stiffness, high precision of parallel mechanism and large workspace, high flexibility of serial mechanism. However, in the research and application of five-axis hybrid machine tool, many technical problems are faced.

[0003] At present, when the machining trajectory of the five-axis hybrid machine tool is planned, the decoupling fitting of the tool tip point and the tool axis vector in the trajectory fitting leads to large tool axis posture error. Moreover, due to the complex mapping between the tool pose and the drive shaft speed information, it is difficult to consider the limitation of the drive shaft in the trajectory planning, which is easy to produce the trajectory beyond the drive shaft capacity, or fail to fully exert the performance of the machine tool. SUMMARY

[0004] Therefore, the present application provides a control planning method and device for a five-axis hybrid machine tool to improve the machining precision and make the machining trajectory more consistent with the performance of the machine tool drive shaft.

[0005] Specifically, the present application is realized by the following technical solutions:

[0006] In a first aspect, the present application provides a control planning method for a five-axis hybrid machine tool, comprising:

[0007] obtaining a first speed mapping model corresponding to the speed between the tool tip point of the machining tool in the five-axis hybrid machine tool and the five drive shafts, and a second speed mapping model corresponding to the speed between the tool axis angular velocity of the machining tool and the five drive shafts;

[0008] based on the drive shaft motion performance constraint of the five-axis hybrid machine tool, the first speed mapping model, the second speed mapping model, and the contour information of the sample to be machined, constructing a first tool trajectory model of the five-axis hybrid machine tool; the first tool trajectory model is a double non-uniform rational B-spline, which is used to represent the first trajectory of the tool tip point and the second trajectory of another point on the tool axis of the machining tool; the first trajectory and the second trajectory include a plurality of discrete points;

[0009] carrying out interpolation point calculation on the first tool trajectory model to obtain a second tool trajectory model;

[0010] based on the kinematic model between the drive shaft and the machining tool, and the second tool trajectory model, determining the corresponding position information of each drive shaft in the machining process;

[0011] control planning of the five-axis hybrid machine tool based on the corresponding position information of the driving shafts in the machining process.

[0012] Optionally, the first tool path model of the five-axis hybrid machine tool is constructed based on the driving shaft motion performance constraint of the five-axis hybrid machine tool, the first speed mapping model, the second speed mapping model, and the profile information of the sample to be machined, and the method comprises the following steps:

[0013] determining the machining path of the machining tool based on the profile information of the sample to be machined;

[0014] discretizing the machining path by equal arc length to obtain a plurality of discrete points, and performing second-order Taylor expansion on the machining path corresponding to the discrete points to obtain initial trajectory parameters corresponding to the discrete points;

[0015] determining a target motion time interval of a machining path segment corresponding to the discrete points based on the initial trajectory parameters, the first speed mapping model, and the second speed mapping model under the constraints of trajectory geometric error and driving shaft motion performance of the five-axis hybrid machine tool; the driving shaft motion performance constraint and the trajectory geometric error constraint are used to constrain the allowable speed of the machining tool;

[0016] determining the target motion time of the machining path segment based on the target motion time interval;

[0017] determining the trajectory parameters of the discrete points based on the initial trajectory parameters and the target motion time, and obtaining the first tool path model of the five-axis hybrid machine tool.

[0018] Optionally, the method further comprises:

[0019] determining the motion time interval of the machining path segment based on the initial trajectory parameters, the first speed mapping model, and the second speed mapping model under each constraint condition, respectively;

[0020] determining the intersection between the motion time intervals under each constraint condition as the target motion time interval.

[0021] Optionally, the method further comprises:

[0022] In the case where the intersection is empty, the target motion time interval of the previous discrete point is re-determined.

[0023] Optionally, the drive shaft motion performance constraints include at least one of the following:

[0024] The tangential velocity constraint of the tool tip; the acceleration constraint of the tool tip; the jerk constraint of the tool tip; the acceleration constraint of the drive shaft; the jerk constraint of the drive shaft;

[0025] The trajectory geometric error constraint includes the trajectory bow height error constraint.

[0026] Optionally, the allowable speed under the trajectory bow height error constraint is:

[0027] ;

[0028] in, The allowable speed under the trajectory height error constraint; This represents the maximum bow height error. The radius of curvature corresponding to the micro-segment of the processing trajectory; v The velocity of the discrete point; T The interpolation period is the period corresponding to the discrete point.

[0029] Optionally, in the first tool trajectory model, the initial trajectory parameters of two adjacent discrete points satisfy:

[0030] ;

[0031] in, i Indicates the first i A discrete point; For the first i Initial trajectory parameters for discrete points; The step size is the arc length. for The first derivative vector; for The second-order derivative.

[0032] Optionally, determining the target motion time of the micro-segment of the processing trajectory based on the target motion time interval includes:

[0033] Determine the acceleration type of the micro-segment of the machining trajectory; the acceleration type includes acceleration type and deceleration type;

[0034] Based on the acceleration type of the micro-segment of the machining trajectory, the target motion time of the micro-segment of the machining trajectory is determined from the maximum and minimum values ​​of the target motion time interval.

[0035] Optionally, determining the acceleration type of the micro-segment of the machining trajectory includes:

[0036] searching a deceleration start point in the machining trajectory by dichotomy;

[0037] performing acceleration type division on the machining trajectory based on the deceleration start point;

[0038] determining the acceleration type of each machining trajectory segment based on the division result.

[0039] In a second aspect, the embodiments of the present disclosure further provide a control planning device of a five-axis hybrid machine tool, comprising:

[0040] an acquisition module, configured to acquire a first speed mapping model corresponding to a tool tip point speed of a machining tool and five driving shafts respectively, and a second speed mapping model corresponding to a tool shaft angular speed of the machining tool and the five driving shafts respectively;

[0041] a construction module, configured to construct a first tool trajectory model of the five-axis hybrid machine tool based on a driving shaft motion performance constraint of the five-axis hybrid machine tool, the first speed mapping model, the second speed mapping model, and profile information of a sample to be machined; the first tool trajectory model is a double non-uniform rational B-spline, used to represent a first trajectory of the tool tip point and a second trajectory of another point on the tool shaft of the machining tool; the first trajectory and the second trajectory comprise a plurality of discrete points;

[0042] an interpolation module, configured to perform interpolation point calculation on the first tool trajectory model to obtain a second tool trajectory model;

[0043] a determination module, configured to determine corresponding position information of the driving shafts in a machining process based on a kinematics model between the driving shafts and the machining tool, and the second tool trajectory model;

[0044] a planning module, configured to perform control planning on the five-axis hybrid machine tool based on the corresponding position information of the driving shafts in the machining process.

[0045] Optionally, the construction module is specifically configured to:

[0046] determine a machining trajectory of the machining tool based on the profile information of the sample to be machined;

[0047] perform equi-arc length discretization processing on the machining trajectory to obtain a plurality of discrete points, and perform second-order Taylor expansion processing on the machining trajectory corresponding to the discrete points to obtain initial trajectory parameters corresponding to the discrete points;

[0048] determine a target motion time interval of a machining trajectory micro-segment corresponding to the discrete point based on the initial trajectory parameters, the first speed mapping model and the second speed mapping model under trajectory geometric error constraints and driving shaft motion performance constraints of the five-axis hybrid machine tool; the driving shaft motion performance constraints and the trajectory geometric error constraints are used to constrain a permissible speed of the machining tool;

[0049] determine a target motion time of the machining trajectory micro-segment based on the target motion time interval;

[0050] determine trajectory parameters of the discrete point based on the initial trajectory parameters and the target motion time, and obtain a first tool trajectory model of the five-axis hybrid machine tool.

[0051] Optionally, the construction module is specifically configured to:

[0052] determine a motion time interval of the machining trajectory micro-segment based on the initial trajectory parameters, the first speed mapping model and the second speed mapping model under each constraint condition respectively;

[0053] determine an intersection between the motion time intervals under each constraint condition as the target motion time interval.

[0054] Optionally, the construction module is further configured to:

[0055] in a case where the intersection is empty, re-determine a target motion time interval of a previous discrete point.

[0056] Optionally, the driving shaft motion performance constraints include at least one of:

[0057] a tangential velocity constraint of the tool tip point, an acceleration constraint of the tool tip point, a jerk constraint of the tool tip point, an acceleration constraint of the driving shaft, a jerk constraint of the driving shaft;

[0058] the trajectory geometric error constraints include a trajectory sag error constraint.

[0059] Optionally, the permissible speed under the trajectory sag error constraint is:

[0060] ;

[0061] wherein, is the permissible speed under the trajectory sag error constraint; is a maximum sag error; is a curvature radius corresponding to the machining trajectory micro-segment; v is a motion velocity of the discrete point; T is an interpolation period corresponding to the discrete point.

[0062] Optionally, in the first tool trajectory model, the initial trajectory parameters of two adjacent discrete points satisfy:

[0063] ;

[0064] in, i Indicates the first i A discrete point; For the first i Initial trajectory parameters for discrete points; The step size is the arc length. for The first derivative vector; for The second-order derivative.

[0065] Optionally, the building module is specifically used for:

[0066] Determine the acceleration type of the micro-segment of the machining trajectory; the acceleration type includes acceleration type and deceleration type;

[0067] Based on the acceleration type of the micro-segment of the machining trajectory, the target motion time of the micro-segment of the machining trajectory is determined from the maximum and minimum values ​​of the target motion time interval.

[0068] Optionally, the building module is specifically used for:

[0069] The starting point of deceleration is searched in the machining trajectory using the binary search method;

[0070] Based on the acceleration / deceleration starting point, the machining trajectory is classified into acceleration types;

[0071] Based on the segmentation results, the acceleration type of each micro-segment of the processing trajectory is determined.

[0072] Thirdly, an optional implementation of this disclosure also provides a computer device, a processor, and a memory, wherein the memory stores machine-readable instructions executable by the processor, and the processor is configured to execute the machine-readable instructions stored in the memory, wherein when the machine-readable instructions are executed by the processor, they perform the steps of the first aspect above, or any possible implementation of the first aspect.

[0073] Fourthly, an optional implementation of this disclosure also provides a computer-readable storage medium storing a computer program that, when run, performs the steps of the first aspect or any possible implementation of the first aspect.

[0074] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, but not limiting the technical solutions of the present disclosure.

[0075] The control planning method and device of the five-axis hybrid machine tool provided by the embodiments of the present disclosure realize high-precision matching of tool movement and driving shaft movement by establishing a speed mapping relationship between tool movement and driving shafts and planning in combination with a double non-uniform rational B-spline model of a tool path. The method can smoothly express and interpolate a machining path of a complex surface while considering performance constraints of driving shafts, ensure continuous tool path and stable machining process, and improve machining accuracy and machine tool use efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0076] Figure 1 A schematic diagram of a five-axis hybrid machine tool provided by the embodiments of the present disclosure;

[0077] Figure 2 A schematic diagram of a parallel mechanism provided by the embodiments of the present disclosure;

[0078] Figure 3 A simplified diagram of a parallel mechanism provided by the embodiments of the present disclosure;

[0079] Figure 4 A flowchart of a control planning method of a five-axis hybrid machine tool provided by the embodiments of the present disclosure;

[0080] Figure 5 A schematic diagram of a track camber error provided by the embodiments of the present disclosure;

[0081] Figure 6 A schematic diagram of a time interval intersection provided by the embodiments of the present disclosure;

[0082] Figure 7a One of the schematic diagrams of the speed of discrete points provided by the embodiments of the present disclosure;

[0083] Figure 7b Another of the schematic diagrams of the speed of discrete points provided by the embodiments of the present disclosure;

[0084] Figure 7c The third of the schematic diagrams of the speed of discrete points provided by the embodiments of the present disclosure;

[0085] Figure 8 A schematic diagram of a feed speed limit curve provided by the embodiments of the present disclosure;

[0086] Figure 9 A flowchart of another control planning method of a five-axis hybrid machine tool provided by the embodiments of the present disclosure;

[0087] Figure 10A schematic diagram of a control planning device of a five-axis hybrid machine tool provided by an embodiment of the present disclosure is shown in the figure;

[0088] Figure 11 A schematic diagram of a computer device provided by an embodiment of the present disclosure is shown in the figure. DETAILED DESCRIPTION

[0089] The exemplary embodiments will be described in detail herein with reference to the attached drawings. In the following description, the same numbers are used to indicate the same or similar elements, unless otherwise represented. The embodiments described in the following exemplary embodiments do not represent all the embodiments consistent with the present disclosure. Rather, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0090] The terms used in the present disclosure are merely for the purpose of describing particular embodiments and are not intended to limit the present disclosure. The singular forms "a," "an," and "the" used in the present disclosure and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0091] It should be understood that although the terms first, second, third, etc. can be employed in this disclosure to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another type of information. For example, without departing from the scope of the present disclosure, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information. Depending on the context, the word "if" as used herein can be interpreted as "when" or "upon determination" or "in response to determining".

[0092] The term "and / or" used herein is merely to describe an association relationship, which means that there can be three relationships, for example, A and / or B can mean that A exists alone, A and B exist together, and B exists alone. In addition, the term "at least one" used herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0093] It is found through research that when the machining trajectory of the five-axis hybrid machine tool is planned, the decoupling fitting of the tool tip point and the tool axis vector in the trajectory fitting results in a large tool axis attitude error. Moreover, due to the complex mapping between the tool pose and the drive shaft speed information, it is difficult to consider the limitations of the drive shaft in the trajectory planning, which is prone to produce trajectories that exceed the drive shaft capacity, or fail to fully exert the performance of the machine tool.

[0094] In view of this, the present disclosure provides a control planning method and apparatus for a five-axis hybrid machine tool. By establishing a speed mapping relationship between the tool motion and the drive axis, and combining it with a bi-non-uniform rational B-spline model of the tool trajectory for planning, high-precision matching of tool motion and drive axis motion is achieved. This method can smoothly express and interpolate the machining trajectory of complex curved surfaces while considering the performance constraints of the drive axis, ensuring continuous tool trajectory, stable machining process, and improving machining accuracy and machine tool utilization efficiency.

[0095] The deficiencies of the existing technical solutions are the result of the inventors' practice and careful research. Therefore, the discovery process of the above problems and the solutions proposed in this disclosure below should be considered as the inventors' contributions to this disclosure.

[0096] To facilitate understanding of this embodiment, a control planning method for a five-axis hybrid machine tool disclosed in this disclosure and its application scenarios will be described in detail first. The execution subject of the control planning method for a five-axis hybrid machine tool provided in this disclosure is generally a computer device with certain computing capabilities.

[0097] The five-axis hybrid machine tool in this embodiment is a type of CNC machine tool that integrates serial and parallel kinematic chains. Structurally, a parallel mechanism typically handles part of the motion degrees of freedom (e.g., Z Axis translation and A , B (shaft rotation), while cooperating with a series mechanism (such as the worktable). X , Y The five-axis movement constitutes a complete five-degree-of-freedom motion. Functionally, it enables the tool to perform a composite motion of three translations and two rotations in three-dimensional space. In terms of performance, the hybrid configuration combines the high rigidity and good dynamic performance of parallel mechanisms with the large stroke and simple structure of serial mechanisms, making it very suitable for high-speed and high-precision machining of complex curved surfaces (such as aerospace blades and automotive molds).

[0098] For example, see Figure 1 The diagram shown is a schematic of a five-axis hybrid machine tool provided in an embodiment of this disclosure. Figure 1 In this five-axis hybrid machine tool, a worktable 1, a stationary platform 2, and a moving platform 3 can be included. The tandem mechanism enables movement in two directions. The worktable 1 is used for... The column moves along the axis and drives the moving platform 3. Movement in the axial direction. The parallel mechanism may include a moving platform 3 and multiple branches connected to the moving platform 3, the branches being used to drive the moving platform 3 in... Z axial movement, and, in A axis,B axial direction swing.

[0099] wherein, Z axial, A axial and B The axis is a virtual axis, and the movement in the direction thereof is actually realized by a parallel mechanism.

[0100] In one possible implementation, the parallel mechanism described above can be in a 3PRRU configuration, wherein 3 represents 3 branches, P represents a moving pair (moving pair joint), R represents a rotating pair (rotating pair joint), and U represents a spherical hinge pair (universal joint). Referring to Figure 2 , a schematic diagram of a parallel mechanism provided by an embodiment of the present disclosure is shown. Among them, 3 branches can be distributed at an interval of 120° on the moving platform 3, the universal joint 5 is hinged to the moving platform 3, the first connecting rod 6 connects the universal joint 5 and the second rotating joint 7, the second connecting rod 8 connects the first rotating joint 9 and the second rotating joint 7, the first rotating joint 9 is hinged to the moving joint 10, and the moving joint 10 is connected to the motor. One end of the moving joint 10 is connected to the static platform 2. By adjusting the slider of the moving joint, the shape of the branch can be changed, thereby driving the moving platform 3.

[0101] Referring to Figure 3 , a simplified diagram of the parallel mechanism provided by an embodiment of the present disclosure is shown. Figure 3 , i represents the first i branch, a coordinate system can be established on the moving platform and the static platform respectively, and the moving platform motion coordinate system and the static platform coordinate system are obtained. Among them, O is the center point of the static platform; represents the center point of the moving platform; a represents the vector from the center point of the moving platform to the universal joint; b represents the vector from the center point of the static platform to the moving joint in the vector ring; c represents the vector from the moving joint to the first rotating joint; d represents the vector from the first rotating joint to the second rotating joint; e represents the vector from the second rotating joint to the universal joint; h represents the vector from the center point of the static platform to the center point of the moving platform (also represents the distance between the center point of the moving platform and the center point of the static platform); A represents the moving joint; B represents the first rotating joint; C represents the second connecting rod and the first connecting rod; D represents the universal joint; represents the radius of the static platform, represents the radius of the moving platform, represents the direction perpendicular to the moving platform; t represents a vector in the direction.

[0102] Non-Uniform Rational B-Spline (NURBS) provides a unified mathematical representation for various analytical curves or free-form curves. Therefore, it has been widely used in many fields such as computer-aided design, computer-aided manufacturing, and computer-aided engineering. A parametric equation of a p-degree NURBS curve can be represented as:

[0103] .

[0104] where, is a dimensionless trajectory parameter. ; is a set of control vertices on the curve; is a set of weight factors corresponding to the control vertices; is a node vector on the p-degree B-spline basis function; is a node vector.

[0105] Usually, in five-axis parallel machine tool trajectory planning, a five-axis double NURBS curve method is used to fit NURBS curves for the tool tip and another point on the tool axis, respectively. The two NURBS curves have the same node vector, weight factor, and trajectory parameter, but different control points. Let the NURBS curve equation for the tool tip motion and the NURBS curve equation for the other point on the tool axis be and , respectively. Their expressions are as follows:

[0106] .

[0107] where is a set of control vertices on the NURBS curve for the tool tip motion; is a set of control vertices on the NURBS curve for the other point on the tool axis. After obtaining the position information of the tool tip and the other point on the tool axis, the tool axis vector can be calculated as:

[0108] .

[0109] However, in this way, the tool tip and the tool axis vector are decoupled and fitted, resulting in large tool axis attitude error. Due to the complex mapping between the tool pose and the drive shaft speed information, it is difficult to implement adaptive speed planning with acceleration and jerk constraints, and ignoring the drive shaft performance constraints can easily lead to drive shaft over-limit or under-utilization of performance. The discontinuity of acceleration parameters in speed planning and the difficulty in determining the start point of deceleration and acceleration phase result in low trajectory accuracy and efficiency. ​

[0110] To this end, the application provides a control planning method of a five-axis hybrid machine tool, which realizes high-precision matching of tool movement and driving shaft movement by establishing a speed mapping relationship between tool movement and driving shafts and planning in combination with a double non-uniform rational B-spline model of tool trajectory. The method can smoothly express and interpolate the machining trajectory of a complex surface while considering performance constraints of driving shafts, ensure continuous tool trajectory and stable machining process, and improve machining accuracy and machine tool use efficiency.

[0111] Referring to Figure 4 , a flowchart of a control planning method of a five-axis hybrid machine tool provided by an embodiment of the present disclosure is shown. The method comprises the following steps:

[0112] S401, acquiring a first speed mapping model corresponding between a tool tip point speed of a machining tool in a five-axis hybrid machine tool and five driving shafts, and a second speed mapping model corresponding between a tool axis angular speed of the machining tool and the five driving shafts.

[0113] In this step, the speed mapping model can reflect the corresponding relationship between the tool tip point speed, the tool axis angular speed and the driving shafts. The first speed mapping model and the second speed mapping model can be obtained by modeling and analyzing the five-axis hybrid machine tool.

[0114] For example, a parallel mechanism kinematics model can be constructed based on first feature information of a parallel mechanism in a five-axis hybrid machine tool. Then, based on second feature information of a worktable and a column in the five-axis hybrid machine tool and the parallel mechanism kinematics model, a five-axis hybrid machine tool kinematics model is constructed. Then, based on the parallel mechanism kinematics model and the five-axis hybrid machine tool kinematics model, a first speed mapping model corresponding between a tool tip point speed of a machining tool in the five-axis hybrid machine tool and five driving shafts in a workpiece coordinate system, and a second speed mapping model corresponding between a tool axis angular speed of the machining tool and the five driving shafts are determined.

[0115] Specifically, under the parallel mechanism shown in Figure 3 , the Z axial direction position coordinates of the input end slider of the branch chain can be as follows:

[0116] .

[0117] wherein, i represents the i th branch chain, s represents sin ; c represents cos ; α represents the A-axis swing angle; β representsB The axis swing angle; γ represents the moving platform motion coordinate system caused by the associated motion Rotating around The axis, The distance from the center point of the moving platform to the tool tip point. The three degrees of freedom of the parallel mechanism include , , , , , Corresponding six motions, , , Corresponding motion as the main motion, , Corresponding motion as the associated motion. d i , e i The length of the second connecting rod represented by L2 and the first connecting rod, and the length is known, that is , .

[0118] After obtaining , the kinematics model of the parallel mechanism can be derived to obtain the velocity model of the parallel mechanism:

[0119] .

[0120] Where, is the angular velocity of the swing of the first connecting rod and the second connecting rod in the parallel mechanism, Indicates the angular velocity of the rotation of the moving platform.

[0121] The mapping relationship of the position and velocity of the three feed axes of the parallel mechanism And the degree of freedom velocity Is:

[0122] .

[0123] Where, , , The coefficient matrix of the velocity mapping relationship of the parallel mechanism is:

[0124] ;

[0125] ;

[0126] .

[0127] Where, subscript Z Indicates the component of the vector in the Z Direction, that is, the third component. The first two lines are associated with movement , The partial differential equations are composed of the last three lines, which represent the angular velocity of the rotating platform. The total differential coefficients are specifically related as follows:

[0128] ;

[0129] ;

[0130] .

[0131] To study the velocity of the tool in the workpiece coordinate system, a velocity mapping analysis was performed on the moving platform and the tool. The velocity of the tool in the workpiece coordinate system, i.e. the angular velocity of the vector direction of the tool axis, is consistent with the angular velocity of the moving platform of the parallel mechanism.

[0132] angular velocity of the tool axis in the workpiece coordinate system and the speed of the five drive shafts The mapping relationship is as follows:

[0133] .

[0134] The velocity mapping model of the tool tip in the workpiece coordinate system is as follows: Tool tip velocity in workpiece coordinate system and the speed of the five drive shafts The mapping relationship is as follows:

[0135] .

[0136] in, .

[0137] Five drive shaft speeds Speed ​​of tool pose in workpiece coordinate system The mapping relationship between them is as follows:

[0138] .

[0139] Based on the above, we can obtain the first velocity mapping model and the second velocity mapping model. The motion speed of the tool pose needs to be controlled by the coordinated motion speeds of the five drive axes. The motion speed of the tool position is controlled simultaneously by the five drive axes, while the motion speed of the tool posture is controlled only by the Z1, Z2, and Z3 axes.

[0140] S402, based on the driving shaft motion performance constraint of the five-axis hybrid machine tool, the first speed mapping model, the second speed mapping model, and the contour information of the sample to be machined, a first tool path model of the five-axis hybrid machine tool is constructed; the first tool path model is a double non-uniform rational B-spline, used to represent a first trajectory of the tool tip point and a second trajectory of another point on the tool axis of the machining tool; the first trajectory and the second trajectory include a plurality of discrete points.

[0141] After obtaining the first speed mapping model and the second speed mapping model, a first tool path model of the five-axis hybrid machine tool can be constructed. The first tool path model can be a double non-uniform rational B-spline (i.e., a double NURBS curve), and the discrete points on the double NURBS curve have the same node vector, weight factor, and trajectory parameter, and are controlled by the control point of the additional point on the tool axis.

[0142] For example, based on the contour information of the sample to be machined, the machining trajectory of the machining tool can be determined; the machining trajectory is discretized by equal arc length to obtain a plurality of discrete points, and the machining trajectory corresponding to the discrete points is processed by second-order Taylor expansion to obtain initial trajectory parameters corresponding to the discrete points; based on the initial trajectory parameters, the first speed mapping model, and the second speed mapping model, the target motion time interval of the machining trajectory segment corresponding to the discrete points is determined under the trajectory geometric error constraint and the driving shaft motion performance constraint of the five-axis hybrid machine tool; the driving shaft motion performance constraint and the trajectory geometric error constraint are used to constrain the allowable speed of the machining tool; based on the target motion time interval, the target motion time of the machining trajectory segment is determined; based on the initial trajectory parameters and the target motion time, the trajectory parameters of the discrete points are determined to obtain the first tool path model of the five-axis hybrid machine tool.

[0143] In a possible implementation, when determining the target motion time interval of the machining trajectory segment corresponding to the discrete points, the motion time interval of the machining trajectory segment can be determined based on the initial trajectory parameters, the first speed mapping model, and the second speed mapping model under each constraint condition, respectively; and the intersection between the motion time intervals under each constraint condition is determined as the target motion time interval.

[0144] In a possible implementation, in the case that the intersection is empty, the target motion time interval of the previous discrete point is re-determined.

[0145] In a possible implementation, the driving shaft motion performance constraint includes at least one of the following:

[0146] a tangential velocity constraint of the tool tip point; an acceleration constraint of the tool tip point; a jerk constraint of the tool tip point; an acceleration constraint of the driving shaft; a jerk constraint of the driving shaft;

[0147] The trajectory geometry error constraint comprises a trajectory camber error constraint.

[0148] Specifically, a machining code (such as a G code) of a machining object can be imported into the trajectory model to form a double NURBS trajectory parameter, the double NURBS curve is subjected to equi-arc length discretization and second-order Taylor expansion processing, and a discrete point parameter is obtained, which meets the requirements of reasonable accuracy and calculation efficiency.

[0149] The parameter of the i-th discrete point can be denoted as The parameter of the i-th discrete point can be denoted as The calculation formula of the i-th parameter The calculation formula of the i-th parameter is as follows:

[0150] .

[0151] wherein, the i-th discrete point is denoted as i The i-th discrete point is denoted as i The initial trajectory parameter of the i-th discrete point is denoted as The initial trajectory parameter of the i-th discrete point is denoted as i The arc length step is denoted as The first derivative vector of the NURBS curve is denoted as The second derivative vector of the NURBS curve is denoted as The second derivative vector of the NURBS curve is denoted as The second derivative vector of the NURBS curve is denoted as The second derivative vector of the NURBS curve is denoted as

[0152] Then, the allowable velocity under the geometry error constraint can be calculated, the curvature radius of any point on the NURBS curve is obtained through the first and second derivative vectors of the discrete point, when the machine tool runs, the motion of the tool is not completely ideal to fit the target trajectory, in the region between every two interpolation points, it is not on the curve, which will cause the existence of the geometry error between the actual trajectory and the ideal trajectory, that is, the trajectory camber error. As shown in FIG. 1, it is a schematic diagram of the trajectory camber error provided by the embodiment of the present disclosure. Figure 5 In the figure, the current motion velocity is denoted as Figure 5 The interpolation period is denoted as v The displacement between the two interpolation points is denoted as T The curvature radius at the point is denoted as vT The maximum feed under the trajectory camber error constraint condition is obtained by establishing an equation and derivation from the right-angled triangle composed of , , ,

[0153] ​​ .

[0154] wherein, is the allowable velocity under the track camber error constraint; is the maximum camber error; is the curvature radius corresponding to the micro-segment of the machining track; v is the motion velocity of the discrete point; T is the interpolation period corresponding to the discrete point.

[0155] The curvature radius of any point on the NURBS curve can be obtained by the trajectory parameter and its first and second derivative vectors:

[0156] .

[0157] Meanwhile, the tangential velocity, acceleration, and jerk constraints of the tool tip point and the acceleration and jerk constraints of the five driving shafts can be established, wherein:

[0158] The tool tip point adds the tangential velocity , acceleration , and jerk constraints as shown in the following formula:

[0159] .

[0160] The driving shafts add the acceleration and jerk constraints as shown in the following formula:

[0161] .

[0162] Under the constraints of the tool tip point and the five driving shafts adding the velocity, acceleration, and jerk, the time intervals satisfying the motion performance constraints of the tool tip point and the five driving shafts can be respectively calculated by the above formulas, and the intersection of all the time intervals is obtained . Within this time interval, the motion performance requirements of the tool tip point and the five driving shafts are met, as shown in Figure 6 . The minimum value of the micro-segment allowable time is selected in the jerk phase, and the maximum value of the micro-segment allowable time is selected in the deceleration phase.

[0163] When all the time intervals have an intersection which is an empty set, it means that no matter is equal to any value, the performance requirements of all the shafts cannot be met simultaneously, and the speed, acceleration, or jerk of the tool tip point or the driving shafts will be out of limits. It can be returned to a discrete point to recalculate.

[0164] After determining the target motion time of the micro-segment of the machining trajectory, the velocity, acceleration, and jerk of the corresponding discrete point can be determined based on the length of the micro-segment and the target motion time.

[0165] For example, the acceleration type of the micro-segment of the machining trajectory can be determined; the acceleration type includes acceleration type and deceleration type; based on the acceleration type of the micro-segment of the machining trajectory, the target motion time of the micro-segment of the machining trajectory is determined from the maximum and minimum values ​​of the target motion time interval.

[0166] In one possible implementation, a deceleration starting point can be searched in the machining trajectory using a bisection method; based on the deceleration starting point, the machining trajectory is divided into acceleration types; and based on the division results, the acceleration type of each micro-segment of the machining trajectory is determined.

[0167] Specifically, the velocity change phase consists of only acceleration and deceleration phases. For discrete points in the acceleration phase, the minimum allowable time for a micro-segment can be selected. For discrete points in the deceleration phase, the maximum allowable time for each micro-segment can be selected. Unlike traditional S-shaped acceleration / deceleration strategies, the starting point of the deceleration phase is unknown and needs to be calculated. The starting point of deceleration can be searched using a binary search method. If the acceleration is less than the critical value at the end of the deceleration phase, the intermediate time value is used.

[0168] For example, such as Figure 7a - Figure 7c As shown in Figure 1, the feed rate and tangential jerk are given limits of 60 mm / s and 10000 mm / s, respectively. 3 The velocity of the discrete point is shown at the center of the figure. Figure 7a In the process, all discrete points are in the acceleration phase, and the time within the micro-segment is selected. But at discrete points When calculating the time of the next micro-segment, an empty set occurs, meaning that the conditions for acceleration and velocity limits cannot be met simultaneously in this segment. Therefore, deceleration needs to be initiated earlier, and the timing of the micro-segment motion during the deceleration / acceleration phase should be selected accordingly. The search for the deceleration starting point uses a binary search method. When calculation cannot continue, take ; Figure 7b In the middle, the deceleration starting point is relatively far back, so take... At this point, acceleration occurs. And speed This indicates that the deceleration starting point is too far forward and needs to be adjusted backward. Figure 7c In the middle, take The situation is similar to Similar; take , there is a situation where the starting point of deceleration and acceleration is relatively late. Therefore, the starting point can be selected between and . Among them, when , for each micro-segment greater than j , the maximum jerk under the driving axis limit condition is obtained, and cannot be selected. In summary, is selected as the starting point of deceleration and acceleration. If the motion time of the micro-segment is always selected as , then finally there will be an acceleration of , while the speed is ; therefore, at the end of deceleration and acceleration, when the acceleration of a discrete point is less than a critical value, , the motion time of the micro-segment is no longer selected as , but the intermediate value of is used.

[0169] For the segmented boundary points, the driving axis acceleration can be calculated by difference based on the speed mapping relationship to ensure the continuity of the boundary parameters. As shown in Figure 8 , in Figure 8 , for the segmented feed speed limit curve, at the points at the boundary, represented by j , its acceleration and speed are known, which are 0 mm / s2 and respectively, but the speed and acceleration of the driving axis are unknown, which are necessary conditions in speed planning and can be obtained through the speed mapping relationship. Among them, assuming that the speed difference between , , is small, the acceleration after difference of the driving axis through speed mapping can be used as the acceleration at point j.

[0170] The speed of the driving axis at points can be obtained through the mapping relationship formula between the five driving axis speeds and the speed of the tool pose in the workpiece coordinate system, and then the acceleration of the driving axis at point , , can be calculated by difference as:

[0171] .

[0172] S403. Calculate the interpolation points of the first tool path model to obtain the second tool path model.

[0173] After obtaining the first tool path model, since the points on the first tool path model are discrete points, there are still multiple trajectory points between the discrete points whose trajectory parameters have not been determined. The interpolation point calculation can be performed on the first tool path model to supplement the trajectory parameters of multiple trajectory points.​

[0174] In this step, the tool tip point and an additional point on the tool axis are second-order Taylor expansion interpolated based on the same trajectory parameters of the double NURBS curve, the interpolation position is calculated, the tool axis vector is obtained according to the interpolation position, inverse kinematics transformation is performed in combination with the kinematics model of the parallel mechanism, and the interpolation point positions of the five driving shafts are obtained.

[0175] S404, based on the kinematics model between the driving shafts and the machining tool, and the second tool trajectory model, determining the corresponding position information of each driving shaft in the machining process.

[0176] In this step, the rotate speed mapping index is calculated based on the speed mapping model to analyze the nonlinear and coupled relationship between the tool posture and the driving shaft speed; the real-time positions of the five driving shafts of the five-axis hybrid machine tool are determined by combining the driving shaft positions of the interpolation points and the speed mapping relationship, that is, the aforementioned 、 、 、 、 real-time positions of the driving shafts.

[0177] S405, based on the corresponding position information of the driving shafts in the machining process, control planning is performed on the five-axis hybrid machine tool.

[0178] After obtaining the corresponding position information of the driving shafts in the machining process, the same can be analyzed to reflect the rotational motion of the machining tool and the influence of the tool posture speed on the driving shaft speed. The rotate speed mapping index (RSMI) can be defined to represent the size of the driving shaft speed required by the tool rotate speed. For the five-axis hybrid machine tool, the dimension of the tool rotate speed is º / s, the dimension of the driving shaft speed is mm / s, and the dimension of the tool rotate speed mapping index RSMI is mm / º.

[0179] For example, the tool rotate speed mapping index can be:

[0180] .

[0181] According to the tool rotate speed mapping index, it can be known that the speed mapping relationship between the A and B axis rotate speeds and the tool posture has nonlinear and coupled characteristics. At the same time, the relationship between the RSMI of the A and B axes and the tool posture is symmetric about A=0, which is caused by the symmetric structure of the parallel mechanism. It can be seen that the five-axis hybrid machine tool has a serial mechanism composed of the A and B axes, and a parallel mechanism composed of the C, D, and E axes. 、 、 、 、 Because of the symmetrical structure of the axis, the velocity mapping of the tool during translational motion is linear and independent; while the rotation of the parallel mechanism is simultaneously affected by... , , Axis control, with its speed mapping between the axis and the tool posture exhibiting nonlinearity and coupling characteristics, yields position information that better reflects the actual situation.

[0182] After obtaining the position information of each drive axis during the machining process, the control system can generate corresponding motion commands based on this position information to coordinate the synchronous operation of the five drive axes. This ensures that the tool moves strictly according to the pre-planned trajectory during actual machining, while taking into account the performance constraints of the machine tool such as speed and acceleration, thereby achieving stable and precise control of the five-axis hybrid machine tool.

[0183] The control planning method for a five-axis hybrid machine tool provided in this disclosure establishes a speed mapping relationship between the tool motion and the drive axis, and combines it with a bi-non-uniform rational B-spline model of the tool trajectory for planning, achieving high-precision matching between the tool motion and the drive axis motion. This method can smoothly express and interpolate the machining trajectory of complex surfaces while considering the performance constraints of the drive axis, ensuring continuous tool trajectory, stable machining process, and improved machining accuracy and machine tool utilization efficiency.

[0184] See Figure 9 The diagram shows a flowchart of another control planning method for a five-axis hybrid machine tool provided in this embodiment. The method includes a speed planning stage and an interpolation point calculation stage. In the speed planning stage, a dual NURBS curve is first obtained based on the machining code, and then subjected to equal arc length discretization. The positions of the five drive axes are obtained through inverse kinematic transformation of the discrete points, and the geometric errors are calculated to obtain the allowable feed rate curve. Then, the speed range is divided according to the motion performance limitations of each drive axis, and segmented planning is performed. Finally, the feed rate is generated, resulting in a first tool path model. In the interpolation point calculation stage, the first tool path model generated in the speed planning stage can be parametrically interpolated to obtain a second tool path model. Then, the second tool path model can be used to perform inverse kinematic transformation to determine the positions of the five drive axes, and the control commands of the drivers are adjusted according to the drive axis positions.

[0185] Corresponding to the aforementioned embodiments of the control planning method for a five-axis hybrid machine tool, this disclosure also provides embodiments of a control planning device for a five-axis hybrid machine tool.

[0186] See Figure 10 The diagram shown is a schematic of a control planning device for a five-axis hybrid machine tool provided in an embodiment of this disclosure. The device includes:

[0187] The acquisition module 1010 is configured to acquire a first speed mapping model respectively corresponding between a tool tip point speed of a machining tool and five driving shafts in a five-axis hybrid machine tool, and a second speed mapping model respectively corresponding between a tool axis angular speed of the machining tool and the five driving shafts.

[0188] The construction module 1020 is configured to construct a first tool path model of the five-axis hybrid machine tool based on a driving shaft motion performance constraint of the five-axis hybrid machine tool, the first speed mapping model, the second speed mapping model, and profile information of a sample to be machined; the first tool path model is a double non-uniform rational B-spline, used to represent a first trajectory of the tool tip point and a second trajectory of another point on the tool axis of the machining tool; the first trajectory and the second trajectory include a plurality of discrete points.

[0189] The interpolation module 1030 is configured to perform interpolation point calculation on the first tool path model to obtain a second tool path model.

[0190] The determination module 1040 is configured to determine corresponding position information of the driving shafts in a machining process based on a kinematics model between the driving shafts and the machining tool, and the second tool path model.

[0191] The planning module 1050 is configured to perform control planning on the five-axis hybrid machine tool based on the corresponding position information of the driving shafts in the machining process.

[0192] Optionally, the construction module 1020 is specifically configured to:

[0193] determine a machining trajectory of the machining tool based on the profile information of the sample to be machined;

[0194] perform equi-arc length discretization processing on the machining trajectory to obtain a plurality of discrete points, and perform second-order Taylor expansion processing on the machining trajectory corresponding to the discrete points to obtain initial trajectory parameters corresponding to the discrete points;

[0195] determine a target motion time interval of a machining trajectory micro-segment corresponding to the discrete points based on the initial trajectory parameters, the first speed mapping model, and the second speed mapping model under trajectory geometric error constraints and the driving shaft motion performance constraint of the five-axis hybrid machine tool; the driving shaft motion performance constraint and the trajectory geometric error constraint are used to constrain a permissible speed of the machining tool;

[0196] determine a target motion time of the machining trajectory micro-segment based on the target motion time interval.

[0197] Determine trajectory parameters of the discrete points based on the initial trajectory parameters and the target motion time, to obtain a first tool trajectory model of the five-axis hybrid machine tool.

[0198] Optionally, the construction module 1020 is specifically used for:

[0199] Determine motion time intervals of the machining trajectory micro-segments based on the initial trajectory parameters, the first velocity mapping model and the second velocity mapping model under respective constraint conditions respectively;

[0200] Determine an intersection between the motion time intervals under respective constraint conditions as the target motion time interval.

[0201] Optionally, the construction module 1020 is further used for:

[0202] In a case where the intersection is empty, redetermine the target motion time interval of the previous discrete point.

[0203] Optionally, the driving shaft motion performance constraint comprises at least one of:

[0204] A tangential velocity constraint of the tool tip point; an acceleration constraint of the tool tip point; a jerk constraint of the tool tip point; an acceleration constraint of the driving shaft; a jerk constraint of the driving shaft;

[0205] The trajectory geometric error constraint comprises a trajectory sag error constraint.

[0206] Optionally, the allowable velocity under the trajectory sag error constraint is:

[0207] ;

[0208] Wherein, is the allowable velocity under the trajectory sag error constraint; is a maximum sag error; is a curvature radius corresponding to the machining trajectory micro-segment; v is a motion velocity of the discrete point; T is an interpolation period corresponding to the discrete point.

[0209] Optionally, in the first tool trajectory model, initial trajectory parameters of two adjacent discrete points satisfy:

[0210] ;

[0211] Wherein, i denotes the i-th discrete point; i is the initial trajectory parameter of the i-th discrete point; i ​​The step size is the arc length. for The first derivative vector; for The second-order derivative.

[0212] Optionally, the construction module 1020 is specifically used for:

[0213] Determine the acceleration type of the micro-segment of the machining trajectory; the acceleration type includes acceleration type and deceleration type;

[0214] Based on the acceleration type of the micro-segment of the machining trajectory, the target motion time of the micro-segment of the machining trajectory is determined from the maximum and minimum values ​​of the target motion time interval.

[0215] Optionally, the construction module 1020 is specifically used for:

[0216] The starting point of deceleration is searched in the machining trajectory using the binary search method;

[0217] Based on the acceleration / deceleration starting point, the machining trajectory is classified into acceleration types;

[0218] Based on the segmentation results, the acceleration type of each micro-segment of the processing trajectory is determined.

[0219] The control planning device for a five-axis hybrid machine tool provided in this disclosure achieves high-precision matching between tool motion and drive axis motion by establishing a speed mapping relationship between the tool motion and the drive axis, and by combining the planning with a double non-uniform rational B-spline model of the tool trajectory. This method can smoothly express and interpolate the machining trajectory of complex surfaces while considering the performance constraints of the drive axis, ensuring continuous tool trajectory, stable machining process, and improving machining accuracy and machine tool utilization efficiency.

[0220] This disclosure also provides a computer device, such as... Figure 11 The diagram shown is a schematic representation of a computer device structure provided in an embodiment of this disclosure, including:

[0221] A processor 111 and a memory 112; the memory 112 stores machine-readable instructions executable by the processor 111, and the processor 111 executes the machine-readable instructions stored in the memory 112. When the machine-readable instructions are executed by the processor 111, the processor 111 performs the following steps:

[0222] Obtain the first velocity mapping model between the tip velocity of the machining tool and the five drive axes in the five-axis hybrid machine tool, and the second velocity mapping model between the angular velocity of the machining tool axis and the five drive axes.

[0223] construct a first tool path model of the five-axis hybrid machine tool based on the motion performance constraints of the driving shafts of the five-axis hybrid machine tool, the first speed mapping model, the second speed mapping model, and profile information of a sample to be machined; the first tool path model is a double non-uniform rational B-spline, used to represent a first trajectory of the tool tip point and a second trajectory of another point on the tool shaft of the machining tool; the first trajectory and the second trajectory include a plurality of discrete points;

[0224] perform interpolation point calculation on the first tool path model to obtain a second tool path model;

[0225] determine corresponding position information of the driving shafts in the machining process based on a kinematics model between the driving shafts and the machining tool and the second tool path model;

[0226] perform control planning on the five-axis hybrid machine tool based on the corresponding position information of the driving shafts in the machining process.

[0227] The memory 112 described above includes an internal memory 1121 and an external memory 1122; the internal memory 1121 is also referred to as an internal storage, used to temporarily store operation data in the processor 111 and exchange data with the external memory 1122 such as a hard disk, and the processor 111 exchanges data with the external memory 1122 through the internal memory 1121.

[0228] The specific execution process of the instructions can refer to the steps of the control planning method of the five-axis hybrid machine tool described in the embodiments of the present disclosure, which will not be described here.

[0229] For the device embodiment, since it basically corresponds to the method embodiment, the related parts can refer to the part of the method embodiment. The device embodiments described above are only schematic, and the units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, that is, they can be located in one place, or distributed on multiple network units. According to actual needs, some or all of the modules can be selected to achieve the purpose of the present disclosure. Those skilled in the art can understand and implement without creative labor.

[0230] The embodiments of the present disclosure also provide a computer readable storage medium, which stores a computer program. When the computer program is run by a processor, the steps of the control planning method of the five-axis hybrid machine tool described in the method embodiments are executed. The storage medium can be a volatile or non-volatile computer readable storage medium.

[0231] The embodiments of the present disclosure further provide a computer program product, comprising computer programs / instructions, which, when executed by a processor, implement the control planning method of the five-axis hybrid machine tool provided by the embodiments of the present disclosure.

[0232] The computer program product can be implemented by hardware, software or a combination thereof. In an optional embodiment, the computer program product is embodied as a computer storage medium. In another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (SDK) or the like.

[0233] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system and device described above can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here. In several embodiments provided by the present disclosure, it should be understood that the disclosed system, device and method can be implemented by other ways. The device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there can be another division manner in actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some communication interface, device or unit, and can be electrical, mechanical or other forms.

[0234] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., they can be located in one place, or can be distributed on a plurality of network units. According to actual needs, some or all of the units can be selected to achieve the purpose of the present embodiment.

[0235] In addition, each functional unit in the various embodiments of the present disclosure can be integrated into one processing unit, or each unit can exist physically, or two or more units can be integrated into one unit.

[0236] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a nonvolatile computer readable storage medium executable by a processor. Based on this understanding, the technical solutions of the present disclosure essentially or say the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present disclosure. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0237] Finally, it should be noted that: the above-described embodiments are merely specific embodiments of the present disclosure, used to illustrate the technical solutions of the present disclosure, rather than limit them. The protection scope of the present disclosure is not limited thereto, although the present disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art within the technical range disclosed by the present disclosure can still modify or easily think of changes to the technical solutions described in the foregoing embodiments, or make equivalent replacements to some technical features; and these modifications, changes or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should be covered within the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the protection scope of the claims.

[0238] The above-described is only the preferred embodiment of the present disclosure, and does not limit the present disclosure. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present disclosure should be included in the protection scope of the present disclosure.

Claims

1. A control planning method for a five-axis hybrid machine tool, characterized in that, The method includes: Obtain the first velocity mapping model between the tip velocity of the machining tool and the five drive axes in the five-axis hybrid machine tool, and the second velocity mapping model between the angular velocity of the machining tool axis and the five drive axes. Based on the motion performance constraints of the drive axes of the five-axis hybrid machine tool, the first velocity mapping model, the second velocity mapping model, and the contour information of the sample to be processed, a first tool trajectory model of the five-axis hybrid machine tool is constructed; the first tool trajectory model is a double non-uniform rational B-spline, used to represent the first trajectory of the tool tip and the second trajectory of another point on the tool axis of the machining tool; the first trajectory and the second trajectory include multiple discrete points; Interpolation points are calculated on the first tool trajectory model to obtain the second tool trajectory model; Based on the kinematic model between the drive shaft and the machining tool, and the second tool trajectory model, the position information of each drive shaft during the machining process is determined; Based on the position information of the drive axis during the machining process, the control plan is performed on the five-axis hybrid machine tool.

2. The method according to claim 1, characterized in that, The first tool trajectory model of the five-axis hybrid machine tool is constructed based on the motion performance constraints of the drive axes of the five-axis hybrid machine tool, the first velocity mapping model, the second velocity mapping model, and the contour information of the sample to be processed, including: Based on the contour information of the sample to be processed, the processing trajectory of the processing tool is determined; The machining trajectory is discretized into equal arc lengths to obtain multiple discrete points, and the machining trajectory corresponding to the discrete points is subjected to second-order Taylor expansion to obtain the initial trajectory parameters corresponding to the discrete points. Based on the initial trajectory parameters, the first velocity mapping model, and the second velocity mapping model, under the constraints of trajectory geometric error and the motion performance constraints of the drive axis of the five-axis hybrid machine tool, the target motion time interval of the machining trajectory micro-segment corresponding to the discrete point is determined; the drive axis motion performance constraints and the trajectory geometric error constraints are used to constrain the allowable speed of the machining tool. Based on the target motion time interval, the target motion time of the processing trajectory micro-segment is determined; Based on the initial trajectory parameters and the target motion time, the trajectory parameters of the discrete points are determined to obtain the first tool trajectory model of the five-axis hybrid machine tool.

3. The method according to claim 2, characterized in that, Based on the initial trajectory parameters, the first velocity mapping model, and the second velocity mapping model, and under the constraints of trajectory geometric error and the motion performance constraints of the drive axes of the five-axis hybrid machine tool, the determination of the target motion time interval of the machining trajectory micro-segment corresponding to the discrete point includes: Under each constraint condition, the motion time interval of the processing trajectory micro-segment is determined based on the initial trajectory parameters, the first velocity mapping model, and the second velocity mapping model. The intersection of the motion time intervals under each constraint is determined as the target motion time interval.

4. The method according to claim 3, characterized in that, The method further includes: If the intersection is empty, the target motion time interval of the previous discrete point is redefined.

5. The method according to claim 2, characterized in that, The drive shaft motion performance constraints include at least one of the following: The tangential velocity constraint of the tool tip; the acceleration constraint of the tool tip; the jerk constraint of the tool tip; the acceleration constraint of the drive shaft; the jerk constraint of the drive shaft; The trajectory geometric error constraint includes the trajectory bow height error constraint.

6. The method according to claim 5, characterized in that, The allowable speed under the trajectory bow height error constraint is: ； in, The allowable speed under the trajectory height error constraint; This represents the maximum bow height error. The radius of curvature corresponding to the micro-segment of the processing trajectory; T The interpolation period is the period corresponding to the discrete point.

7. The method according to claim 2, characterized in that, In the first tool trajectory model, the initial trajectory parameters of two adjacent discrete points satisfy: ； in, i Indicates the first i A discrete point; For the first i Initial trajectory parameters for discrete points; The step size is the arc length. for The first derivative vector; for The second-order derivative.

8. The method according to claim 2, characterized in that, Determining the target motion time of the micro-segment of the processing trajectory based on the target motion time interval includes: Determine the acceleration type of the micro-segment of the machining trajectory; the acceleration type includes acceleration type and deceleration type; Based on the acceleration type of the micro-segment of the machining trajectory, the target motion time of the micro-segment of the machining trajectory is determined from the maximum and minimum values ​​of the target motion time interval.

9. The method according to claim 8, characterized in that, Determining the acceleration type of the micro-segment of the machining trajectory includes: The deceleration starting point is searched in the machining trajectory using the binary search method; Based on the acceleration / deceleration starting point, the machining trajectory is classified into acceleration types; Based on the segmentation results, the acceleration type of each micro-segment of the processing trajectory is determined.

10. A control planning device for a five-axis hybrid machine tool, characterized in that, include: The acquisition module is used to acquire the first velocity mapping model between the tip velocity of the machining tool and the five drive axes in the five-axis hybrid machine tool, and the second velocity mapping model between the angular velocity of the machining tool axis and the five drive axes. A construction module is used to construct a first tool trajectory model of the five-axis hybrid machine tool based on the motion performance constraints of the drive axes of the five-axis hybrid machine tool, the first velocity mapping model, the second velocity mapping model, and the contour information of the sample to be processed; the first tool trajectory model is a double non-uniform rational B-spline, used to represent the first trajectory of the tool tip and the second trajectory of another point on the tool axis of the machining tool; the first trajectory and the second trajectory include multiple discrete points; The interpolation module is used to calculate interpolation points on the first tool trajectory model to obtain the second tool trajectory model; The determination module is used to determine the position information of each drive axis during the machining process based on the kinematic model between the drive axis and the machining tool, and the second tool trajectory model; The planning module is used to perform control planning for the five-axis hybrid machine tool based on the position information of the drive axis during the machining process.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 9.

12. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method according to any one of claims 1 to 9.

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