Tool turret head swinging control method and system of numerical control machine tool

Abstract

The invention provides a tool turret head swinging control method and system of a numerical control machine tool. The method comprises the steps that according to a temperature load coupling data set and temperature gradient field distribution data, a thermal deformation space vector of a tool turret swing head is calculated and generated through a thermal resistance and thermal capacitance network; searching a pose deviation value corresponding to the thermal deformation space vector from a preset association relation table; and according to the pose deviation value, the rotation positioning parameter of the tool turret and the swing angle parameter of the swing head are adjusted, so that the tool nose track is matched with the target machining path in real time. According to the technical scheme, thermal errors in the machining process of the numerical control machine tool are eliminated through the thermal deformation real-time compensation technology, and the machining precision and the quality stability are improved.

Description

Technical Field

[0001] The present application relates to the technical field of CNC machine tools, and in particular to a turret swing head control method and system for a CNC machine tool. Background Art

[0002] In the field of high-end precision CNC machining, thermal deformation caused by long-term operation of CNC machine tools can cause tool tip trajectory deviation. How to compensate for thermal errors in high-end precision CNC machining and ensure that the tool tip trajectory consistently matches the theoretical path when machining complex curved surfaces is a current research hotspot.

[0003] The existing solution uses fixed-position temperature sensor network compensation technology, deploys temperature sensors at traditional heat source points such as spindle bearings and screw nuts, establishes a mapping relationship between temperature rise and thermal error at limited measuring points through a multivariate linear regression model, and writes preset compensation values ​​into the CNC system based on this mapping relationship.

[0004] However, the existing solutions have two core defects. First, the spatial coverage is insufficient. Sensors in fixed positions cannot capture the three-dimensional temperature gradient field distribution of complex structural parts such as the turret head base, resulting in a missing spatial dimension in the thermal deformation calculation. Second, the adaptability to working conditions is weak. The static regression model is difficult to couple the impact of dynamic changes in machining load parameters on the temperature field, and reduces the compensation accuracy in working condition processing. Summary of the Invention

[0005] The present application provides a turret head control method and system for a CNC machine tool, which is used to solve the problem of low turret head control accuracy caused by insufficient three-dimensional temperature gradient field representation accuracy and lack of thermal and force dynamic coupling mechanism in the prior art.

[0006] In a first aspect, the present application provides a turret head control method for a CNC machine tool, comprising:

[0007] Obtain the spindle temperature rise data, ambient temperature data, and machining load parameters of the CNC machine tool to form a temperature-load coupling data set, and obtain the temperature gradient field distribution data of the base where the turret swing head is located on the CNC machine tool;

[0008] Generate a thermal deformation space vector of the turret swing head by calculating the thermal resistance and heat capacitance network according to the temperature load coupling data set and the temperature gradient field distribution data;

[0009] Searching for a posture deviation corresponding to the thermal deformation space vector from a preset association relationship table;

[0010] According to the posture deviation, the rotation positioning parameters of the turret and the swing angle parameters of the swing head are adjusted to make the tool tip trajectory match the target processing path in real time.

[0011] Optionally, generating a thermal deformation space vector of the turret swing head by calculating the thermal resistance and heat capacitance network according to the temperature load coupling data set and the temperature gradient field distribution data includes:

[0012] Mapping the temperature gradient field distribution data to the boundary nodes of the thermal resistance and heat capacitance network to form the boundary temperature input of the thermal resistance and heat capacitance network;

[0013] Associating the spindle temperature rise data in the temperature load coupling data set as the internal heat source temperature to the spindle node of the thermal resistance and heat capacitance network, associating the constant temperature boundary condition corresponding to the ambient temperature data in the temperature load coupling data set to the base surface node of the thermal resistance and heat capacitance network, converting the machining load parameters in the temperature load coupling data set into frictional heat power, and allocating them to the kinematic pair associated nodes in the thermal resistance and heat capacitance network according to the kinematic pair positions, so as to form a complete heat source input of the thermal resistance and heat capacitance network;

[0014] According to the boundary temperature input and the complete heat source input, solving the node heat balance equation of the thermal resistance and heat capacitance network through implicit iteration to obtain the node temperature distribution of the thermal resistance and heat capacitance network;

[0015] Calculating the three-dimensional thermal expansion displacement of each node in the thermal resistance and heat capacitance network according to the node temperature distribution and the material thermal expansion coefficient;

[0016] The three-dimensional thermal expansion displacements of different nodes are aggregated based on the rigid connection relationship of the turret swing head to generate a thermal deformation space vector representing the overall deformation of the turret swing head.

[0017] Optionally, converting the processing load parameters in the temperature load coupling data set into frictional heat power and allocating them to kinematic pair associated nodes in the thermal resistance and heat capacitance network according to kinematic pair positions to form a complete heat source input of the thermal resistance and heat capacitance network includes:

[0018] Calculating the frictional heat power of the kinematic pair according to the axial cutting force, the rotational speed and the preset friction coefficient library in the machining load parameters;

[0019] Performing a heat conduction path topological decomposition on the friction heat power of the kinematic pair to generate a node heat source component allocated to the associated nodes of each kinematic pair;

[0020] The internal heat source temperature, the constant temperature boundary condition, and the nodal heat source components are combined into a complete heat source input.

[0021] Optionally, performing a heat conduction path topological decomposition on the frictional heat power of the kinematic pair to generate a node heat source component allocated to a node associated with each kinematic pair includes:

[0022] Calculating path weight factors between nodes based on the spatial position relationship of kinematic-pair associated nodes in the thermal resistance and heat capacitance network, thermal conductivity parameters of the kinematic-pair associated nodes, and heat conduction paths;

[0023] Calculating a heat transfer efficiency ratio based on the path weight factor;

[0024] The frictional heat power of the kinematic pair is decomposed according to the heat conduction efficiency ratio to generate path heat flow components distributed to the associated nodes of each kinematic pair, and all the path heat flow components are aggregated to generate node heat source components.

[0025] Optionally, decomposing the frictional heat power of the kinematic pair according to the heat conduction efficiency ratio to generate path heat flow components distributed to associated nodes of each kinematic pair includes:

[0026] Based on the heat conduction efficiency ratio, the friction heat power of the kinematic pair is decomposed proportionally to obtain the initial node heat source component allocated to the associated node of each kinematic pair;

[0027] Based on the heat capacity parameters of each node in the thermal resistance and heat capacity network and the thermal conductivity parameters between adjacent nodes, a heat flow dynamic balance iterative calculation is performed on the initial node heat source component so that the heat flow distribution satisfies the preset node energy conservation condition; based on the node heat source component after iterative convergence, a path heat flow component is generated.

[0028] Optionally, searching for the posture deviation corresponding to the thermal deformation space vector from a preset association table includes:

[0029] Obtaining the rotational positioning deviation and the swing angle deviation corresponding to the thermal deformation space vector from a preset association relationship table;

[0030] The rotational positioning deviation and the swing angle deviation are combined into a posture deviation.

[0031] Optionally, adjusting the rotation positioning parameters of the turret and the swing angle parameters of the swing head according to the posture deviation so that the tool tip trajectory matches the target machining path in real time includes:

[0032] Generating a turret rotation control amount according to a rotation positioning deviation amount in the posture deviation amount, and writing the turret rotation control amount into a current control cycle parameter register of a turret servo controller;

[0033] Generating a swing head swing control amount according to a swing angle deviation amount in the posture deviation amount, and writing the swing head swing control amount into a current control cycle parameter register of a swing head servo controller;

[0034] The closed-loop position control of the turret servo controller and the swing head servo controller is triggered to drive the turret to rotate according to the rotation positioning parameter corresponding to the turret rotation control amount, and the swing head to swing according to the swing angle parameter corresponding to the swing head swing control amount, so that the tool tip trajectory matches the target processing path in real time.

[0035] In a second aspect, the present application provides a turret head control system for a CNC machine tool, comprising:

[0036] An acquisition module is used to obtain the spindle temperature rise data, ambient temperature data and processing load parameters of the CNC machine tool, form a temperature-load coupling data set, and obtain the temperature gradient field distribution data of the base where the turret swing head is located on the CNC machine tool;

[0037] A calculation module, configured to generate a thermal deformation space vector of the turret swing head through a thermal resistance and heat capacitance network calculation based on the temperature load coupling data set and the temperature gradient field distribution data;

[0038] A search module, configured to search a preset association table for a posture deviation corresponding to the thermal deformation space vector;

[0039] The adjustment module is used to adjust the rotation positioning parameters of the turret and the swing angle parameters of the swing head according to the posture deviation, so that the tool tip trajectory matches the target processing path in real time.

[0040] In a third aspect, the present application provides a computing device comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a turret swing head control method for a CNC machine tool as described in any one of the first aspects.

[0041] In a fourth aspect, the present application provides a computer storage medium storing a computer program, which, when executed by a computer, implements a turret head control method for a CNC machine tool as described in any one of the first aspects.

[0042] In the present application, a turret swing head control method for a CNC machine tool is provided, the method comprising: obtaining spindle temperature rise data, ambient temperature data and processing load parameters of the CNC machine tool to form a temperature load coupling data set, and obtaining temperature gradient field distribution data of a base on which the turret swing head is located on the CNC machine tool; generating a thermal deformation space vector of the turret swing head through a thermal resistance and heat capacitance network calculation based on the temperature load coupling data set and the temperature gradient field distribution data; searching for a posture deviation corresponding to the thermal deformation space vector from a preset association table; and adjusting the rotation positioning parameters of the turret and the swing angle parameters of the swing head based on the posture deviation so that the tool tip trajectory matches the target processing path in real time.

[0043] This application forms a temperature-load dynamic coupling data set by acquiring the spindle temperature rise, ambient temperature and processing load parameters in real time, and synchronously collects the three-dimensional temperature gradient field distribution of the turret swing head base to achieve full-dimensional perception of the thermal deformation inducement; based on the thermal resistance and heat capacitance network, the temperature field data is converted into the spatial thermal deformation vector of the turret swing head, breaking through the dimensional limitation of traditional point temperature measurement; the pre-association relationship table is used to realize the fast and accurate mapping of thermal deformation to posture deviation, avoiding real-time modeling calculation delays; finally, by dynamically adjusting the turret rotation parameters and the swing head swing angle, the tool tip trajectory tracks the target path in real time, forming a thermal error closed-loop control, and improving the processing accuracy and stability under complex working conditions.

[0044] Furthermore, the temperature gradient field of the turret head base is mapped to the boundary nodes of the thermal resistance and heat capacitance network to construct the boundary temperature input; at the same time, the temperature load coupling data set is decomposed, the spindle temperature rise is associated with the spindle node as the internal heat source, and the ambient temperature is associated with the base node as the constant boundary. The machining load parameters are processed by the friction heat power conversion module, and the friction heat power of the kinematic pair is calculated based on the axial cutting force, rotational speed and friction coefficient. The node heat source components are generated by the topological decomposition of the heat conduction path and distributed to the kinematic pair associated nodes; after combining the three types of heat sources to form a complete input, the node heat balance equation is solved by implicit iteration to obtain the temperature distribution of the entire network; the three-dimensional thermal expansion displacement of each node is calculated according to the thermal expansion coefficient of the material, and finally the displacement is aggregated based on the rigid connection relationship to generate the thermal deformation space vector. Through the precise coupling of multi-source heterogeneous data and physical networks and the topological decomposition mechanism of frictional heat power, physical mechanism-level modeling of heat input under complex working conditions is achieved; by combining implicit iterative solution with material thermodynamic calculations, the local to global thermal deformation transfer process is accurately quantified; the generated thermal deformation space vector is integrated with the structural constraint relationship to more realistically characterize the overall deformation of the turret head, providing high-fidelity input for subsequent posture compensation, and effectively ensuring the physical rationality and working condition adaptability of thermal error compensation.

[0045] These and other aspects of the present application will become more readily apparent from the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0047] Figure 1 A flowchart of a turret swing control method for a CNC machine tool provided in an embodiment of the present application;

[0048] Figure 2A schematic structural diagram of a turret swing head control system for a CNC machine tool provided in an embodiment of the present application;

[0049] Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0051] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this document or may be executed in parallel. The serial numbers of the operations, such as 11, 12, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to being different types.

[0052] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0053] In order to solve the problem of low turret head control accuracy caused by insufficient three-dimensional temperature gradient field representation accuracy and lack of dynamic coupling mechanism of heat and force in the prior art, an embodiment of the present application provides a turret head control method for a CNC machine tool, which adopts the following concept: targeting the core problem of attenuation of machining accuracy caused by thermal deformation of CNC machine tools, taking multi-source thermodynamic data fusion as the entry point, first construct a dynamic coupling data set that integrates spindle temperature rise, ambient temperature and machining load, and break through the limitations of traditional point temperature monitoring to synchronously obtain the three-dimensional temperature gradient field of the turret head base; then, based on physical mechanisms and data-driven collaborative strategies, multi-source data are input into the thermal resistance and heat capacitance network model, and spatial thermal deformation vectors are generated through thermal-mechanical coupling calculations; in order to avoid the computing power bottleneck of real-time modeling, an association mapping table of thermal deformation vectors to posture deviations is pre-established to achieve rapid retrieval; finally, through a closed-loop control architecture, the posture deviation amount is reversely injected as a compensation amount into the turret rotation and head swing parameter control system, so as to realize adaptive tracking of the tool tip trajectory to the theoretical path, forming a real-time suppression closed loop of "perception-calculation-compensation".

[0054] Figure 1 A flowchart of a turret swing head control method for a CNC machine tool provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, the method includes:

[0055] S11. Obtain the spindle temperature rise data, ambient temperature data, and machining load parameters of the CNC machine tool to form a temperature-load coupling data set, and obtain the temperature gradient field distribution data of the base where the turret swing head is located on the CNC machine tool.

[0056] Among them, the spindle temperature rise data can refer to the increase in the spindle bearing or housing relative to the ambient temperature monitored in real time by the temperature sensor, reflecting the heat intensity during the operation of the spindle. The ambient temperature data can refer to the static air temperature value collected by the sensor arranged in the working area of ​​the machine tool. The processing load parameters can refer to the parameters such as axial cutting force, spindle torque and feed speed output by the NC system in real time, reflecting the mechanical load state during the processing. The temperature load coupling data set refers to the structured data set formed by aligning and fusing the spindle temperature rise data, ambient temperature data and processing load parameters in time series, which is used to characterize the thermal-mechanical coupling effect. The temperature gradient field distribution data can refer to the three-dimensional spatial temperature change rate data of the turret swing head base obtained by infrared thermal imaging or distributed sensors, including the mapping relationship between position coordinates and temperature gradient values.

[0057] In an embodiment of the present application, first, the temperature rise data of the CNC machine tool spindle is collected in real time through the spindle temperature sensor, and the ambient temperature data is obtained through the ambient temperature sensor, and the processing load parameters are read from the CNC system; secondly, the spindle temperature rise data, ambient temperature data and processing load parameters are aligned and fused according to the timestamp to form a temperature load coupling data set containing thermodynamic parameters and working condition parameters; finally, the temperature distribution of the base surface and internal key points is obtained by scanning with an infrared thermal imager array installed on the base of the turret swing head, and temperature gradient field distribution data representing the changes in the spatial thermal field is generated through three-dimensional reconstruction. It should be noted that the embodiment of the present application does not specifically limit the position of the internal key points.

[0058] S12. Generate the thermal deformation space vector of the turret swing head through thermal resistance and heat capacitance network calculation based on the temperature load coupling data set and the temperature gradient field distribution data.

[0059] Among them, the thermal resistance and heat capacitance network can be understood as a thermal network model, and the thermal deformation space vector can refer to the six-degree-of-freedom deformation vector calculated and output by the thermal network model.

[0060] In an embodiment of the present application, the temperature gradient field distribution data is first mapped to the boundary nodes of the pre-constructed thermal resistance and heat capacitance network as the boundary temperature input; secondly, the temperature load coupling data set is decomposed. Specifically, the spindle temperature rise data is associated with the network spindle node as the internal heat source, and the ambient temperature data is associated with the base surface node as the constant boundary. The processing load parameters are calculated by the friction heat power conversion module and distributed to the kinematic pair associated nodes; then, the node thermal balance equation is solved by an implicit iterative algorithm to obtain the temperature distribution of the entire network node; then, the three-dimensional thermal expansion displacement of each node is calculated based on the thermal expansion coefficient of the material; finally, the displacement is aggregated according to the rigid connection relationship of the turret swing head to generate a thermal deformation space vector that represents the overall deformation.

[0061] S13. Searching for the posture deviation corresponding to the thermal deformation space vector from a preset association table.

[0062] Among them, the posture deviation refers to the compensation value of the turret rotation center offset angle and the swing head swing angle obtained after the thermal deformation space vector is mapped and transformed.

[0063] In an embodiment of the present application, the thermal deformation space vector is first input into a pre-stored association table, which is pre-established through finite element simulation and machine tool calibration experiments; secondly, a nearest neighbor matching search is performed in the vector space to find the mapping item with the smallest Euclidean distance to the current thermal deformation space vector; then, the rotational positioning deviation and swing angle deviation corresponding to the item are extracted; finally, the two types of deviations are combined into a posture deviation that can be directly used for servo control.

[0064] It should be understood that before the search, this embodiment has established a preset association table through a large number of computer simulations and actual machine tool tests. This table records how much deviation in the tool tip position will result from different thermal deformation space vectors. Based on the current "overall distortion" data calculated by S12, the most matching row is found in the association table. The two key values ​​that need to be compensated are read out from this row: the rotational positioning deviation used to indicate how much additional angle the turret needs to rotate, and the swing angle deviation used to indicate how much additional angle the swing head needs to swing, which are then combined into a posture deviation.

[0065] S14. According to the posture deviation, adjust the rotation positioning parameters of the turret and the swing angle parameters of the swing head so that the tool tip trajectory matches the target processing path in real time.

[0066] The rotational positioning parameters refer to the target position command values ​​of the servo system that control the rotation angle of the turret around the spindle. The swing angle parameters refer to the target position command values ​​of the servo system that control the deflection angle of the swing head around the hinge point. The tool tip path can refer to the actual motion path of the tool end point relative to the workpiece during machining.

[0067] In the embodiment of the present application, the posture deviation is first analyzed to obtain the turret rotation positioning deviation and the swing head swing angle deviation; secondly, the rotation positioning deviation is converted into an incremental control instruction of the turret servo controller and written into its current control cycle parameter register; at the same time, the swing angle deviation is converted into an incremental control instruction of the swing head servo controller and written into the corresponding register; then the closed-loop position control of the dual servo system is triggered; finally, the turret is driven to rotate according to the compensated rotation positioning parameter, and the swing head is driven to swing according to the compensated swing angle parameter, so that the tool tip trajectory can track the target processing path in real time. These fine-tuning just offsets the influence of thermal deformation, so that the actual movement trajectory of the tool tip can follow and match the ideal processing path set by the computer, thereby processing high-precision parts.

[0068] The following is a specific example: First, spindle temperature rise data is collected using an embedded temperature sensor at the spindle end, while ambient temperature data is collected using a workshop temperature and humidity sensor. The CNC system bus reads the current axial cutting force and spindle speed parameters to form a temperature-load coupled data set. Simultaneously, an 8×8 thermocouple array deployed at the turret base collects temperature distribution data, and spatial interpolation generates temperature gradient field distribution data. Next, the gradient field data is mapped to the 32 boundary nodes of a thermal resistance and capacitance network. Spindle temperature rise data is associated with the spindle nodes, while ambient temperature is bound to the base nodes. Axial cutting force is converted into thermal power using a friction coefficient library and distributed to kinematic nodes. An implicit iterative solution is used to obtain the temperature distribution of 142 nodes. Node displacements are calculated based on the material expansion coefficient and aggregated to generate a thermal deformation space vector. The closest vectors are then matched against a pre-stored association table to extract the turret rotation deviation of 0.003° and the head swing deviation of 0.07mm. Finally, the rotation deviation is converted into the number of turret servo control pulses and written to a register. The swing deviation is converted into the voltage value of the head servo control and written to a register, triggering closed-loop control to correct the tool tip trajectory to the theoretical path in real time.

[0069] By executing S11 to S14, the embodiment of the present application realizes high-fidelity calculation of thermal deformation space vectors through multi-source thermodynamic data fusion and physical mechanism modeling; utilizes pre-stored relationship tables to realize rapid conversion of thermal deformation to posture deviation; and dynamically adjusts servo parameters to ensure that the tool tip trajectory continuously fits the theoretical processing path, effectively maintaining dimensional consistency in precision processing.

[0070] In a possible embodiment, S12, generating a thermal deformation space vector of the turret swing head through a thermal resistance and heat capacitance network calculation based on the temperature load coupling data set and the temperature gradient field distribution data, includes:

[0071] Step 121 : Map the temperature gradient field distribution data to the boundary nodes of the thermal resistance and heat capacitance network to form the boundary temperature input of the thermal resistance and heat capacitance network.

[0072] Boundary nodes refer to nodes in the thermal resistance and capacitance network that are in contact with the external environment. They are used to carry temperature boundary conditions and their spatial locations are determined by meshing. Boundary temperature input refers to the set of temperature values ​​formed by mapping the temperature gradient field distribution data to the boundary nodes according to spatial coordinates. This can be used as a boundary constraint for thermal calculations. Internal heat source temperature refers to the temperature value of the internal nodes of the thermal network formed by converting the temperature rise data caused by the heating of the main shaft. It is used to reflect the intensity of the main heat source.

[0073] In an embodiment of the present application, the correspondence between the spatial coordinates and the temperature values ​​in the temperature gradient field distribution data is first extracted; secondly, the temperature value of each coordinate point is mapped to the corresponding boundary node in the predefined thermal resistance and heat capacitance network; finally, a boundary temperature input containing the temperature values ​​of all boundary nodes is generated.

[0074] Step 122: Associating the spindle temperature rise data in the temperature load coupling data set as the internal heat source temperature to the spindle node of the thermal resistance and heat capacitance network, associating the constant temperature boundary condition corresponding to the ambient temperature data in the temperature load coupling data set to the base surface node of the thermal resistance and heat capacitance network, converting the machining load parameters in the temperature load coupling data set into frictional heat power, and distributing them to the kinematic pair associated nodes in the thermal resistance and heat capacitance network according to the kinematic pair positions, so as to form a complete heat source input of the thermal resistance and heat capacitance network.

[0075] A spindle node can refer to a specific group of nodes in a thermal resistance and capacitance network specifically designed to simulate spindle components, characterizing the spindle's thermal inertia through heat capacitance parameters. A constant temperature boundary condition can refer to converting ambient temperature data into a fixed temperature value and applying it to the base surface nodes to simulate the ambient heat dissipation effect. A base surface node can refer to a set of boundary nodes located on the outer surface of the turret head mounting base in the thermal network. Frictional heat power can refer to the heat generation power of the kinematic pair calculated by multiplying the product of the axial cutting force in the machining load parameters and the spindle speed by the friction coefficient. Kinematic pair-related nodes can refer to kinematic pair structures such as guideways and bearings in the thermal network. Multiple kinematic pair-related nodes can form a node group. For example, a bearing may be discretized into 5-10 nodes. These nodes collectively characterize the thermal behavior of the kinematic pair, and the frictional heat generated by the kinematic pair must be distributed to the kinematic pair-related nodes. A complete heat source input can refer to the set of driving forces in the thermal network formed by the combination of the internal heat source temperature, the constant temperature boundary condition, and the heat source components of the kinematic pair nodes. The physical meaning of the kinematic pair position refers to the actual spatial position of the mechanical connection parts with relative motion in the CNC machine tool and their heat conduction topological relationship.

[0076] In an embodiment of the present application, the temperature load coupling data set is first analyzed: the spindle temperature rise data is associated with the spindle node of the thermal resistance and heat capacitance network as the internal heat source temperature; the ambient temperature data is converted into a constant temperature value and associated with the base surface node to form a constant temperature boundary condition; at the same time, the processing load parameters are input into the friction heat power calculation module, and the friction heat power of the moving pair is calculated by multiplying the axial cutting force by the rotational speed and then by the friction coefficient; secondly, the friction heat power is distributed to the corresponding moving pair associated nodes according to the position of the moving pair; finally, the internal heat source temperature, the constant temperature boundary condition and the heat source component of the moving pair node are combined to form a complete heat source input.

[0077] Step 123: Based on the boundary temperature input and the complete heat source input, the node heat balance equations of the thermal resistance and heat capacitance network are solved by implicit iteration to obtain the node temperature distribution of the thermal resistance and heat capacitance network.

[0078] The node heat balance equation may refer to a differential equation describing that the heat flow into each node is equal to the heat capacity energy storage. This embodiment does not specifically limit the form. The node temperature distribution may refer to a spatiotemporal distribution data set consisting of the temperature values ​​of all nodes in the network obtained by solving the heat balance equation. The expressions of the heat balance equations of different nodes can be unified in form. For example, the formula of the node heat balance equation is: Among them, C i is the heat capacity of node i, T i is the temperature of node i, t is the time, G ij is the thermal conductivity between node i and adjacent node j, T j is the temperature of the adjacent node j, Q i is the heat source power injected into node i.

[0079] In an embodiment of the present application, the boundary temperature input and the complete heat source input are first loaded into the thermal resistance and heat capacitance network; secondly, a thermal balance equation is established for each node, which includes the heat flow change caused by thermal conductivity between adjacent nodes and the temperature change caused by the heat capacitance of this node; then an implicit iterative algorithm is used to solve the equation group; finally, a set of steady-state temperature values ​​of all nodes, i.e., the node temperature distribution, is obtained.

[0080] Step 124 : Calculate the three-dimensional thermal expansion displacement of each node in the thermal resistance and heat capacitance network based on the node temperature distribution and the material thermal expansion coefficient.

[0081] The material thermal expansion coefficient can refer to the change in unit length of the material caused by a unit temperature rise, and the corresponding value for each node can be obtained from the material database. The three-dimensional thermal expansion displacement can refer to the three-dimensional linear displacement vector calculated by multiplying the node temperature rise by the thermal expansion coefficient and then by the geometric dimensions.

[0082] In this embodiment, the method first reads the material thermal expansion coefficient database to obtain the linear expansion coefficient of the material corresponding to each node. Next, for each node, the thermal expansion displacement in the X, Y, and Z axes is calculated by multiplying the temperature change by the thermal expansion coefficient and then by the node's original size. Finally, a three-dimensional thermal expansion displacement set containing all node displacement vectors is output. This step can be understood as using a physical model to perform calculations, taking into account all input heat, temperature boundaries, and the thermal properties of the metal itself, ultimately calculating the three-dimensional thermal expansion displacement for each "point" in the model. This displacement indicates how much that point has expanded due to heat.

[0083] Step 125: Aggregate the three-dimensional thermal expansion displacements of different nodes based on the rigid connection relationship of the turret swing head to generate a thermal deformation space vector representing the overall deformation of the turret swing head.

[0084] The rigid connection relationship refers to a mechanical constraint relationship in which there is no relative displacement between the components in the turret swing head.

[0085] In an embodiment of the present application, a rigid connection relationship topology diagram is first extracted based on the turret head assembly drawing; secondly, the displacement of each node is traversed, and the mutually rigidly constrained node displacements are vector-superimposed according to the connection relationship in the topology diagram; then, the degree-of-freedom constraint conversion is performed on the non-rigid connection node displacement; finally, all node displacements are aggregated to generate a six-degree-of-freedom thermal deformation space vector representing the overall deformation.

[0086] It should be understood that because the turret and the swing head are rigidly connected as a whole, the tiny expansions of these "points" are summed up according to their connection relationship, ultimately resulting in a thermal deformation space vector. This vector is used to comprehensively describe the overall distortion of the turret and the swing head. This data includes information such as the direction of the bend and the amount of twist.

[0087] The following is a specific example: First, the base temperature gradient field data captured by an infrared thermal imager is mapped to the 12 boundary nodes of the thermal resistance and heat capacitance network to form the boundary temperature input. Next, the temperature-load coupling data set is decomposed: the spindle temperature rise data is associated with the spindle node group, and the ambient temperature data is bound to the base surface node. The axial cutting force in the machining load is combined with the spindle speed and friction coefficient library to calculate the guideway friction heat power. This is distributed to the three kinematic joint-associated nodes based on the kinematic joint positions to form the nodal heat source components. The three types of heat sources are combined to form a complete heat source input. A thermal balance equation is then established for 142 nodes, and the nodal temperature distribution is obtained through implicit iterative solution. Three-dimensional thermal expansion displacements are then calculated based on the material expansion coefficient and initial dimensions of each node. For example, the spindle node X-axial displacement is equal to the temperature rise multiplied by the expansion coefficient multiplied by the shaft length. Finally, the displacements are aggregated based on the rigid connection relationship of the turret head. For example, the displacements of the four fixed nodes are weighted averaged to generate a thermal deformation space vector. This method is like installing an intelligent "anti-thermal deformation system" on the CNC machine tool, which can sense the deformation caused by heat more comprehensively and in real time, and automatically adjust the position of the tool to offset this deformation, ensuring that the tool always moves on the correct path.

[0088] By executing steps 121 to 125, the embodiment of the present application accurately quantifies the transfer process from temperature field to structural deformation through thermal network modeling driven by physical mechanisms; integrates multi-source heat input and material thermodynamic properties to achieve high-fidelity prediction of thermal deformation space vectors, providing a reliable theoretical basis for thermal error compensation.

[0089] In one possible embodiment, step 122 converts the processing load parameters in the temperature load coupling data set into frictional heat power and distributes them to the kinematic pair associated nodes in the thermal resistance and heat capacitance network according to the kinematic pair positions to form a complete heat source input of the thermal resistance and heat capacitance network, including:

[0090] Step a1: Calculate the friction heat power of the kinematic pair based on the axial cutting force, rotational speed, and a preset friction coefficient library in the machining load parameters.

[0091] Among them, the preset friction coefficient library refers to the pre-stored friction coefficient data set of different types of kinematic pairs under different lubrication conditions, which is obtained through experimental calibration and is used to accurately calculate frictional heat generation.

[0092] In an embodiment of the present application, the axial cutting force and spindle speed values ​​are first extracted from the machining load parameters; secondly, the preset friction coefficient library is called to match the corresponding dynamic friction coefficient according to the type of kinematic pair; then, the axial cutting force is multiplied by the spindle speed and then by the matching friction coefficient to calculate the friction heat power of the kinematic pair.

[0093] Step a2: perform heat conduction path topological decomposition on the friction heat power of the kinematic pair to generate node heat source components allocated to the associated nodes of each kinematic pair.

[0094] The node heat source component refers to the thermal power value allocated to a single node after decomposition through the heat conduction path, reflecting the energy receiving ratio of the node in the friction heat transfer of the moving pair.

[0095] In an embodiment of the present application, first, based on the spatial topological relationship of the kinematic pair associated nodes in the thermal resistance and heat capacitance network, the heat conduction path weight factors between each node are calculated; secondly, the heat conduction efficiency ratio is determined based on the weight factors; then, the frictional heat power of the kinematic pair is decomposed into path heat flow components according to the heat conduction efficiency ratio; finally, all path heat flow components associated with the same node are summed to generate the node heat source components allocated to the nodes associated with each kinematic pair.

[0096] Step a3: Combine the internal heat source temperature, constant temperature boundary conditions, and node heat source components into a complete heat source input.

[0097] Among them, in the embodiment of the present application, the internal heat source temperature is first bound to the main axis node; secondly, the constant temperature boundary condition is loaded to the base surface node; then the node heat source component is injected into the corresponding motion pair associated node; finally, the three types of heat input are integrated to form a complete heat source input covering all nodes of the thermal network.

[0098] The following is a specific example: First, based on the axial cutting force and spindle speed in the machining load parameters, combined with the corresponding values ​​of the guideway kinematic pair in the preset friction coefficient library, the guideway friction heat power is calculated. Secondly, based on the spatial position of the kinematic pair associated nodes in the thermal network, the weight factor of the heat conduction path between nodes is calculated as the inverse of the distance between adjacent nodes. The friction heat power is decomposed into path heat flow components according to the weight ratio and summed to generate the heat source components of each node. Finally, the internal heat source temperature converted from the spindle temperature rise is loaded onto the spindle node, the constant boundary converted from the ambient temperature is loaded onto the base node, and the node heat source component is injected into the kinematic pair node to combine into a complete heat source input.

[0099] For example, the embodiment of the present application achieves accurate conversion of machining load parameters to heat source input through the following specific process: First, based on the axial cutting force of 1200N and the spindle speed of 3000rpm in the machining load parameters, combined with the preset friction coefficient library to match the kinematic pair type, such as angular contact ball bearings with a friction coefficient of 0.0025, the friction heat power is calculated to be 37.7W through the calculation formula of cutting force × linear speed × friction coefficient, where the linear speed is calculated by the bearing pitch diameter of 80mm and the speed. Then, the heat power is physically decomposed: based on the spatial topology of the four bearing-related nodes in the thermal resistance and heat capacity network, such as the spacing of 20mm and the thermal conductivity of cast iron of 45W / (m·K), the equal-weighted heat conduction path factor of 0.25 is calculated, and the heat source component of each node is initially allocated to 18.85W; considering the node heat capacity of 120J / K and the temperature difference conduction between adjacent nodes, the node heat source component is further corrected to 17.2W through dynamic heat flow balance iteration, eliminating the energy conservation deviation of the initial allocation. Finally, three types of heat input are integrated: the spindle node is loaded with a measured temperature rise of 8.5°C as the internal heat source, the base surface node is bound to the ambient temperature of 25°C as a constant boundary, and the kinematic sub-node is injected with the iteratively optimized 17.2W heat source component to form a complete heat source input.

[0100] By executing steps a1 to a3, the embodiment of the present application realizes the physical-level mapping of the heat generated by the moving pair to the network nodes through the refined decomposition and dynamic allocation of frictional heat power; combined with the systematic integration of multiple types of heat sources, a high-fidelity heat input model is constructed to improve the adaptability of thermal deformation prediction to working conditions.

[0101] In a possible embodiment, step a2, performing a heat conduction path topological decomposition on the frictional heat power of the kinematic pair to generate a node heat source component allocated to each kinematic pair associated node, includes:

[0102] Step a21: Calculate the path weight factors between nodes based on the spatial position relationship of the kinematic pair associated nodes in the thermal resistance and heat capacitance network, the thermal conductivity parameters of the kinematic pair associated nodes, and the heat conduction paths.

[0103] The path weight factor refers to a dimensionless parameter that characterizes the heat conduction capacity between nodes. It is calculated based on the product of the inverse of the node spacing and the thermal conductivity, and reflects the heat flux intensity under unit temperature difference.

[0104] In an embodiment of the present application, the three-dimensional coordinate data of the kinematically associated nodes in the thermal resistance and heat capacitance network are first obtained to establish a spatial position relationship; secondly, the thermal conductivity parameters of the material of each node are read; then, the topological structure of the heat conduction path between the nodes is analyzed; finally, the path weight factor between the nodes is calculated based on the inverse of the node spacing multiplied by the thermal conductivity parameter.

[0105] Step a22: Calculate the heat conduction efficiency ratio based on the path weight factor.

[0106] The heat conduction efficiency ratio refers to the ratio of the weight factor of a single heat conduction path to the sum of the weight factors of all associated paths, which is used to determine the distribution ratio of friction heat power in the path.

[0107] In an embodiment of the present application, the path weight factors of all kinematic pair associated nodes are first normalized; secondly, the weight factor of each path is calculated and divided by the sum of all path weight factors to obtain a proportional value; finally, the proportional value is defined as the thermal conduction efficiency ratio of the path.

[0108] Step a23: Decompose the frictional heat power of the kinematic pair according to the heat conduction efficiency ratio to generate path heat flow components allocated to the associated nodes of each kinematic pair. Aggregate all path heat flow components to generate node heat source components.

[0109] The path heat flow component refers to the heat power value flowing through a specific heat conduction path, which is decomposed from the total friction heat power according to the heat conduction efficiency ratio.

[0110] In an embodiment of the present application, the frictional heat power of the moving pair is first multiplied by the heat conduction efficiency ratio of each path to generate an initial path heat flow component; secondly, the initial path heat flow component is iteratively optimized for heat flow conservation; then, the optimized heat flow component is distributed to the corresponding node according to the path association relationship; finally, all path heat flow components received by each node are aggregated to generate a node heat source component.

[0111] The following is a specific example: First, the spacing between adjacent nodes is calculated based on the coordinates of the five nodes associated with the guideway kinematic pair. Path weight factors are then combined with the cast iron material's thermal conductivity parameters to generate path weight factors. Next, the path weight factors are divided by their sum to obtain the heat conduction efficiency ratio. The guideway friction heat power is then multiplied by the heat conduction efficiency ratio of each path to generate the initial path heat flux components. This is then iteratively optimized using heat capacity constraints. Finally, the optimized path heat flux components are assigned to the nodes. For example, node 3 receives the sum of the heat flux components from paths 1-3 and 2-3 to generate the node heat source component.

[0112] By executing steps a21 to a23, the embodiment of the present application realizes accurate transfer modeling of frictional heat energy in complex structures through heat flow topological decomposition driven by physical mechanisms; combined with heat flow dynamic balance optimization, the physical rationality of node heat source components is improved, providing high-fidelity input for thermal network calculations.

[0113] In a possible embodiment, step a23, decomposing the frictional heat power of the kinematic pair according to the heat conduction efficiency ratio to generate path heat flow components distributed to the associated nodes of each kinematic pair, includes:

[0114] Step b1: Based on the heat conduction efficiency ratio, the friction heat power of the kinematic pair is decomposed proportionally to obtain the initial node heat source components allocated to the associated nodes of each kinematic pair.

[0115] Among them, in the embodiment of the present application, the heat conduction efficiency ratio data and the friction heat power value of the kinematic pair are first obtained; secondly, the friction heat power is multiplied by the heat conduction efficiency ratio corresponding to each kinematic pair associated node; finally, the initial node heat source component of each node is generated.

[0116] For example, this example physically decomposes the frictional heat power of 50W for a ball screw-nut pair with a five-node chain topology. First, based on a node spacing of 25mm and a cast iron thermal conductivity of 45W / (m·K), the equally weighted path thermal conductivity of 1.08W / K is calculated. Normalized, the heat conduction efficiency ratio of each path is 0.25. The total power is then distributed to each conduction path according to the efficiency ratio, with each path receiving a heat flux component of 12.5W. The node-associated path heat flux is then aggregated, with nodes 1 and 5 receiving a single-path component of 12.5W, and nodes 2, 3, and 4 receiving a dual-path component of 25W. While this initial allocation satisfies the topological logic, it fails to account for the thermal capacity storage effect, resulting in an artificially high heat source at the intermediate nodes, providing an optimization basis for subsequent energy conservation iterations.

[0117] Step b2: Based on the heat capacitance parameters of each node in the thermal resistance and heat capacitance network and the thermal conductivity parameters between adjacent nodes, perform an iterative calculation of the heat flux dynamic balance of the initial node heat source components to ensure that the heat flux distribution satisfies the preset node energy conservation conditions. Generate path heat flux components based on the node heat source components after iterative convergence.

[0118] Among them, the heat capacity parameter refers to the amount of heat required to be absorbed per unit temperature rise, which is obtained by multiplying the specific heat capacity of the node material by the mass, and reflects the node's own heat storage capacity. The thermal conductivity parameter refers to the heat flux value under a unit temperature difference between adjacent nodes, which is calculated based on the thermal conductivity of the material and the heat transfer area divided by the node spacing. Iterative calculation of dynamic balance of heat flow: refers to the numerical optimization process of gradually adjusting the node heat source component so that the sum of the heat flow flowing into the node is equal to the change in the node's heat capacity energy storage. The node energy conservation condition refers to the physical constraint equation that requires any node to satisfy the sum of the heat flow incoming from the adjacent nodes plus its own heat source component equals the heat capacity of the node multiplied by the time derivative of the temperature.

[0119] In an embodiment of the present application, the heat capacitance parameters of each node in the thermal resistance and heat capacitance network and the thermal conductivity parameters between adjacent nodes are first read; secondly, a node energy conservation equation is established, requiring that the sum of the heat fluxes flowing into the node is equal to the heat capacitance of the node multiplied by the temperature change rate; then, the Newton iteration method is used to perform a dynamic balance calculation on the initial node heat source component, the heat flux is calculated by dividing the temperature difference between adjacent nodes by the thermal conductivity parameter, and the heat source component is adjusted so that the algebraic sum of the node heat flux approaches zero; finally, when all nodes meet the energy conservation condition, the iteration is terminated, and the optimized node heat source component is output as the path heat flux component.

[0120] The following is a specific example: First, based on the heat conduction efficiency ratio, the guide rail friction heat power is proportionally decomposed to generate the initial nodal heat source components of the kinematic pair's associated nodes. Next, the nodal heat capacity parameters and inter-node thermal conductivity parameters are read to establish the energy conservation equation. The conduction heat flux is calculated by dividing the temperature difference between adjacent nodes by the thermal conductivity parameter. The initial heat source components are adjusted to bring the net nodal heat flux close to zero. After three iterations and convergence, the nodal heat source components that satisfy the energy conservation equation are output as the path heat flux components.

[0121] By executing steps b1 to b2, the embodiment of the present application eliminates the physical distortion of the initial heat source distribution through iterative optimization of thermal inertia modeling and energy conservation constraints; achieves high-fidelity simulation of the heat flow propagation process, and improves the transient accuracy of thermal deformation prediction.

[0122] In a possible embodiment, S13, searching a preset association table for a posture deviation corresponding to the thermal deformation space vector, includes:

[0123] Step 131 : Obtain the rotational positioning deviation and the swing angle deviation corresponding to the thermal deformation space vector from a preset association relationship table.

[0124] The rotational positioning deviation refers to the angular offset that needs to be compensated for the turret around its central axis. This is obtained by mapping the angular component of the thermal deformation space vector in an association table and is used to correct the turret's circumferential positioning error. The swing angle deviation refers to the swing angle correction value that needs to be compensated for the swing head around its hinge axis. This is generated by converting the linear displacement component of the thermal deformation space vector in an association table and is used to eliminate radial offset at the end of the swing head.

[0125] In an embodiment of the present application, the thermal deformation space vector is first input into a preset association table; secondly, the mapping item with the smallest Euclidean distance to the vector is retrieved from the table through a vector similarity matching algorithm; then, the corresponding turret rotation center axis offset angle value, i.e., the rotation positioning deviation, and the angle compensation value within the swing plane of the swing head, i.e., the swing angle deviation, are extracted from the mapping item.

[0126] Step 132: Combine the rotational positioning deviation and the swing angle deviation into a posture deviation.

[0127] Among them, in an embodiment of the present application, a data container containing the rotational positioning deviation and the swing angle deviation is first established; secondly, the rotational positioning deviation is written into the first data field of the container; then the swing angle deviation is written into the second data field of the container; finally, the posture deviation data packet that can be directly input into the servo control system is encapsulated and generated.

[0128] The following is a specific example: First, the thermal deformation space vector is input into the association table stored in the finite element calibration. The K-nearest neighbor algorithm is used to match the most similar vector items and extract the rotational positioning deviation and the swing angle deviation. Next, a two-field data structure is created, with the rotational positioning deviation written to field one and the swing angle deviation written to field two. This generates a pose deviation data packet and transmits it to the motion controller.

[0129] By executing steps 131 to 132, the embodiment of the present application realizes the precise conversion of thermal deformation to execution parameters through a fast mapping mechanism of a pre-built relationship table; the structured posture deviation encapsulation provides standardized input for servo control, ensuring the real-time and reliability of compensation instructions.

[0130] In a possible embodiment, S14, adjusting the rotation positioning parameters of the turret and the swing angle parameters of the swing head according to the posture deviation so that the tool tip trajectory matches the target machining path in real time, includes:

[0131] Step 141: Generate a turret rotation control value based on the rotation positioning deviation value in the posture deviation value, and write the turret rotation control value into the current control cycle parameter register of the turret servo controller.

[0132] The turret rotation control variable refers to the physical execution instructions generated by converting the rotation positioning deviation through the control algorithm. These instructions, including the servo motor pulse count and hydraulic valve current value, are used to accurately drive the turret's rotation axis to the compensation position. The current control cycle parameter register is a temporary memory within the servo controller dedicated to storing the target command value for a single control cycle. At the beginning of the cycle, new values ​​are loaded and overwrite the old values, ensuring real-time command updates.

[0133] In an embodiment of the present application, the posture deviation data packet is first parsed to extract the rotational positioning deviation value therein; secondly, the deviation is converted into a pulse frequency instruction or analog voltage signal, i.e., the turret rotation control value, which can be recognized by the turret servo driver through a motion control algorithm; finally, the control value is written in real time into a register of the turret servo controller specifically used to store the target parameters of the current control cycle.

[0134] Step 142: Generate a swing head swing control value according to the swing angle deviation in the posture deviation, and write the swing head swing control value into the current control cycle parameter register of the swing head servo controller.

[0135] The swing head's swing control variable is the physical execution command generated by kinematically converting the swing angle deviation. This includes the linear motor displacement and hydraulic cylinder stroke, which are used to drive the swing head to the compensation angle. Closed-loop position control is a control mechanism that dynamically corrects the actuator output through a real-time comparison of the target command and sensor feedback position using an adjustment algorithm. This control mechanism includes position detection, deviation calculation, and signal conditioning.

[0136] In an embodiment of the present application, the posture deviation data packet is first parsed to extract the swing angle deviation value; secondly, the deviation is converted into an opening instruction of the swing head hydraulic servo valve or a motor angle instruction, that is, a swing head swing control quantity, through an angle and displacement conversion module; finally, the control quantity is written in real time into a register of the swing head servo controller specifically used to store the target parameters of the current control cycle.

[0137] Step 143, triggering the closed-loop position control of the turret servo controller and the swing head servo controller, driving the turret to rotate according to the rotation positioning parameters corresponding to the turret rotation control amount, and driving the swing head to swing according to the swing angle parameters corresponding to the swing head swing control amount, so that the tool tip trajectory matches the target processing path in real time.

[0138] Among them, in the embodiment of the present application, first, a synchronous trigger instruction is sent to the turret servo controller and the swing head servo controller; secondly, each controller reads the control quantity in the register as the target input; then the actual position is fed back through the photoelectric encoder or grating ruler for comparison with the target value; finally, the output of the actuator is adjusted based on the proportional integral differential algorithm, driving the turret to rotate according to the compensated rotation angle and the swing head to deflect according to the compensated swing angle, so as to achieve dynamic matching of the tool tip trajectory with the theoretical path.

[0139] The following is a specific example: First, the rotational positioning deviation is extracted from the posture deviation, converted into a pulse command for the stepper motor, and written into the period register of the turret servo controller. Next, the swing angle deviation is extracted, converted into a voltage command for the hydraulic valve, and written into the period register of the swing head servo controller. Finally, dual-controller closed-loop position control is triggered: the turret servo uses encoder feedback to adjust the motor angle in real time, while the swing head servo uses laser interferometer feedback to adjust the valve opening, driving the tool tip trajectory to track the target path in real time.

[0140] By executing steps 141 to 143, the embodiment of the present application ensures real-time injection of compensation instructions through a register direct write mechanism, and combines dual-axis synchronous closed-loop control to achieve millisecond-level dynamic correction of the tool tip trajectory, effectively eliminating the path following error caused by thermal deformation.

[0141] Figure 2 A schematic diagram of the structure of a turret swing head control system for a CNC machine tool provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the system includes:

[0142] The acquisition module 21 is used to obtain the spindle temperature rise data, ambient temperature data and processing load parameters of the CNC machine tool, form a temperature load coupling data set, and obtain the temperature gradient field distribution data of the base where the turret swing head is located on the CNC machine tool.

[0143] The calculation module 22 is used to calculate and generate the thermal deformation space vector of the turret swing head through a thermal resistance and heat capacitance network according to the temperature load coupling data set and the temperature gradient field distribution data.

[0144] The search module 23 is used to search for the posture deviation corresponding to the thermal deformation space vector from a preset association relationship table.

[0145] The adjustment module 24 is used to adjust the rotation positioning parameters of the turret and the swing angle parameters of the swing head according to the posture deviation, so that the tool tip trajectory matches the target processing path in real time.

[0146] Figure 2 The turret swing head control system of a CNC machine tool can execute Figure 1 The implementation principle and technical effects of the turret swing head control method for a CNC machine tool described in the illustrated embodiment will not be elaborated on here. The specific manner in which each module and unit performs operations in the turret swing head control system for a CNC machine tool in the above embodiment has been described in detail in the embodiments of the method and will not be elaborated on here.

[0147] In one possible design, Figure 2 The turret swing head control system of a CNC machine tool in the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32 .

[0148] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0149] The processing component 32 is configured to execute the following process: It obtains spindle temperature rise data, ambient temperature data, and machining load parameters of the CNC machine tool to form a temperature-load coupling dataset, and obtains temperature gradient field distribution data for the base of the turret head on the CNC machine tool. Based on the temperature-load coupling dataset and the temperature gradient field distribution data, a thermal resistance and heat capacitance network is used to calculate and generate a thermal deformation space vector for the turret head. The position deviation corresponding to the thermal deformation space vector is retrieved from a preset association table. Based on the position deviation, the turret's rotational positioning parameters and the turret head's swing angle parameters are adjusted to ensure that the tool tip trajectory matches the target machining path in real time.

[0150] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component may also be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above method.

[0151] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as random access memory (RAM), static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0152] Of course, a computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0153] The input / output interface provides an interface between the processing component and the peripheral interface module, which can be an output device, an input device, etc.

[0154] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0155] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0156] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 The embodiment shown is a method for controlling the turret swing head of a CNC machine tool.

[0157] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0158] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0159] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0160] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. 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 application.

Claims

1. A turret head control method for a CNC machine tool, characterized in that: include: Obtain the spindle temperature rise data, ambient temperature data, and machining load parameters of the CNC machine tool to form a temperature-load coupling data set, and obtain the temperature gradient field distribution data of the base where the turret swing head is located on the CNC machine tool; Generate a thermal deformation space vector of the turret swing head by calculating the thermal resistance and heat capacitance network according to the temperature load coupling data set and the temperature gradient field distribution data; Searching for a posture deviation corresponding to the thermal deformation space vector from a preset association relationship table; According to the posture deviation, the rotation positioning parameters of the turret and the swing angle parameters of the swing head are adjusted to make the tool tip trajectory match the target processing path in real time.

2. The method according to claim 1, characterized in that The step of generating a thermal deformation space vector of the turret swing head by calculating the thermal resistance and heat capacitance network according to the temperature load coupling data set and the temperature gradient field distribution data includes: Mapping the temperature gradient field distribution data to the boundary nodes of the thermal resistance and heat capacitance network to form the boundary temperature input of the thermal resistance and heat capacitance network; Associating the spindle temperature rise data in the temperature load coupling data set as the internal heat source temperature to the spindle node of the thermal resistance and heat capacitance network, associating the constant temperature boundary condition corresponding to the ambient temperature data in the temperature load coupling data set to the base surface node of the thermal resistance and heat capacitance network, converting the machining load parameters in the temperature load coupling data set into frictional heat power, and allocating them to the kinematic pair associated nodes in the thermal resistance and heat capacitance network according to the kinematic pair positions, so as to form a complete heat source input of the thermal resistance and heat capacitance network; According to the boundary temperature input and the complete heat source input, solving the node heat balance equation of the thermal resistance and heat capacitance network through implicit iteration to obtain the node temperature distribution of the thermal resistance and heat capacitance network; Calculating the three-dimensional thermal expansion displacement of each node in the thermal resistance and heat capacitance network according to the node temperature distribution and the material thermal expansion coefficient; The three-dimensional thermal expansion displacements of different nodes are aggregated based on the rigid connection relationship of the turret swing head to generate a thermal deformation space vector representing the overall deformation of the turret swing head.

3. The method according to claim 2, characterized in that The process of converting the processing load parameters in the temperature load coupling data set into frictional heat power and allocating the parameters to the kinematic pair associated nodes in the thermal resistance and heat capacitance network according to the kinematic pair positions to form a complete heat source input of the thermal resistance and heat capacitance network includes: Calculating the frictional heat power of the kinematic pair according to the axial cutting force, the rotational speed and the preset friction coefficient library in the machining load parameters; Performing a heat conduction path topological decomposition on the friction heat power of the kinematic pair to generate a node heat source component allocated to the associated nodes of each kinematic pair; The internal heat source temperature, the constant temperature boundary condition, and the nodal heat source components are combined into a complete heat source input.

4. The method according to claim 3, characterized in that The step of performing a heat conduction path topological decomposition on the frictional heat power of the kinematic pair to generate a node heat source component allocated to the associated nodes of each kinematic pair includes: Calculating path weight factors between nodes based on the spatial position relationship of kinematic-pair associated nodes in the thermal resistance and heat capacitance network, thermal conductivity parameters of the kinematic-pair associated nodes, and heat conduction paths; Calculating a heat transfer efficiency ratio based on the path weight factor; The frictional heat power of the kinematic pair is decomposed according to the heat conduction efficiency ratio to generate path heat flow components distributed to the associated nodes of each kinematic pair, and all the path heat flow components are aggregated to generate node heat source components.

5. The method according to claim 4, characterized in that Decomposing the frictional heat power of the kinematic pair according to the heat conduction efficiency ratio to generate path heat flow components distributed to the associated nodes of each kinematic pair includes: Based on the heat conduction efficiency ratio, the friction heat power of the kinematic pair is decomposed proportionally to obtain the initial node heat source component allocated to the associated node of each kinematic pair; Based on the heat capacity parameters of each node in the thermal resistance and heat capacity network and the thermal conductivity parameters between adjacent nodes, a heat flow dynamic balance iterative calculation is performed on the initial node heat source component so that the heat flow distribution satisfies the preset node energy conservation condition; based on the node heat source component after iterative convergence, a path heat flow component is generated.

6. The method according to claim 1, characterized in that The step of searching for the posture deviation corresponding to the thermal deformation space vector from a preset association table includes: Obtaining the rotational positioning deviation and the swing angle deviation corresponding to the thermal deformation space vector from a preset association relationship table; The rotational positioning deviation and the swing angle deviation are combined into a posture deviation.

7. The method according to claim 1, characterized in that The method of adjusting the rotation positioning parameters of the turret and the swing angle parameters of the swing head according to the posture deviation so that the tool tip trajectory matches the target machining path in real time includes: Generating a turret rotation control amount according to a rotation positioning deviation amount in the posture deviation amount, and writing the turret rotation control amount into a current control cycle parameter register of a turret servo controller; Generating a swing head swing control amount according to a swing angle deviation amount in the posture deviation amount, and writing the swing head swing control amount into a current control cycle parameter register of a swing head servo controller; The closed-loop position control of the turret servo controller and the swing head servo controller is triggered to drive the turret to rotate according to the rotation positioning parameter corresponding to the turret rotation control amount, and the swing head to swing according to the swing angle parameter corresponding to the swing head swing control amount, so that the tool tip trajectory matches the target processing path in real time.

8. A turret head control system for a CNC machine tool, characterized in that: include: An acquisition module is used to obtain the spindle temperature rise data, ambient temperature data and processing load parameters of the CNC machine tool, form a temperature-load coupling data set, and obtain the temperature gradient field distribution data of the base where the turret swing head is located on the CNC machine tool; A calculation module, configured to generate a thermal deformation space vector of the turret swing head through a thermal resistance and heat capacitance network calculation based on the temperature load coupling data set and the temperature gradient field distribution data; A search module, configured to search a preset association table for a posture deviation corresponding to the thermal deformation space vector; The adjustment module is used to adjust the rotation positioning parameters of the turret and the swing angle parameters of the swing head according to the posture deviation, so that the tool tip trajectory matches the target processing path in real time.

9. A computing device, characterized in that It comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a turret swing head control method for a CNC machine tool as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed by a computer, the method for controlling the turret swing head of a CNC machine tool according to any one of claims 1 to 7 is implemented.

Images