Five-axis numerical control machine tool debugging method, system and equipment based on digital twinning and medium

Abstract

The invention discloses a five-axis numerical control machine tool debugging method, system and equipment based on digital twinning and a medium, and relates to the field of numerical control machine tool precision control, and the method comprises the steps: building a digital twinning model of a five-axis numerical control machine tool; performing virtual RTCP detection on the digital twinborn model, and recording a deviation vector between a theoretical tool nose point position and an actual tool nose point position; constructing an objective function based on the deviation vector, and solving the objective function by adopting a differential evolution algorithm to obtain an optimal servo parameter; and debugging the five-axis numerical control machine tool based on the optimal servo parameters. According to the method, all parameters are verified in the digital twinborn model firstly, and a physical machine does not need to be started and stopped repeatedly, tried and measured manually, so that the test period is shortened, and the risk of machine collision caused by misoperation is eliminated.

Description

Technical Field

[0001] This application relates to the field of precision control of CNC machine tools, and in particular to a debugging method, system, equipment and medium for a five-axis CNC machine tool based on digital twins. Background Technology

[0002] Currently, the machining accuracy requirements of five-axis CNC machine tools are gradually increasing. Among the error types of machine tools, dynamic errors caused by insufficient dynamic performance of the servo system are the main factor affecting high-speed and high-precision machining. A commonly used dynamic accuracy method for five-axis CNC machine tools is instrument-based non-cutting inspection. The principle is to use precision measuring instruments to measure the tool offset to reflect the dynamic control accuracy of the machine tool. RTCP (Rotational Tool Center Point) detection involves setting a fixed tool tip position, rotating the axis in a specific motion, and the translational axis needing to follow and compensate to ensure the tool tip position remains unchanged. Due to the following error of each axis, the tool tip will produce a slight offset. By detecting the tool tip displacement with precision instruments, machine tool performance can be evaluated, and machine tool adjustments can be made based on the results.

[0003] Traditional five-axis CNC machine tool RTCP accuracy debugging requires repeated start-stop of the equipment and actual measurement of position error using a ballbar / dial indicator. On-site servo parameter adjustments are usually based on the operator's work experience, often using conservative and subjective parameters. This requires repeated loading and testing of parameters between software and hardware, resulting in long debugging cycles (several days to several weeks), easy damage to the equipment due to misoperation, and limited coverage of test conditions. Summary of the Invention

[0004] To address the aforementioned issues, this application provides a method, system, equipment, and medium for debugging a five-axis CNC machine tool based on digital twins.

[0005] To achieve the above objectives, this application provides the following solution.

[0006] In a first aspect, this application provides a method for debugging a five-axis CNC machine tool based on digital twins, comprising: establishing a digital twin model of the five-axis CNC machine tool; performing virtual RTCP detection on the digital twin model and recording the deviation vector between the theoretical tool tip position and the actual tool tip position; constructing an objective function based on the deviation vector and solving the objective function using a differential evolution algorithm to obtain optimal servo parameters; and debugging the five-axis CNC machine tool based on the optimal servo parameters.

[0007] Secondly, this application provides a five-axis CNC machine tool debugging system based on digital twins, comprising: a digital twin model construction module for establishing a digital twin model of the five-axis CNC machine tool; a virtual RTCP detection module for performing virtual RTCP detection on the digital twin model and recording the deviation vector between the theoretical tool tip position and the actual tool tip position; an objective function construction and solution module for constructing an objective function based on the deviation vector and solving the objective function using a differential evolution algorithm to obtain optimal servo parameters; and a debugging module for debugging the five-axis CNC machine tool based on the optimal servo parameters.

[0008] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described five-axis CNC machine tool debugging method based on digital twin.

[0009] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described digital twin-based five-axis CNC machine tool debugging method.

[0010] According to the specific embodiments provided in this application, this application has the following technical effects: This application constructs a high-fidelity digital twin model of a five-axis CNC machine tool based on digital twin technology, performs virtual RTCP testing on the digital twin model, establishes a mapping relationship between the RTCP results and the servo parameters of each axis, and provides assurance for virtual debugging. All parameters in this application are first verified within the digital twin model, eliminating the need for repeated start-ups, stop-starts, trial cuts, and manual measurements on the physical machine, thus shortening the testing cycle and eliminating the risk of accidental machine collisions. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a flowchart illustrating a five-axis CNC machine tool debugging method based on digital twins, provided as an embodiment of this application.

[0013] Figure 2 This is a schematic diagram of the modules of a digital twin model of a five-axis CNC machine tool.

[0014] Figure 3 This is a flowchart illustrating the differential evolution algorithm. Detailed Implementation

[0015] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0016] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0017] In one exemplary embodiment, such as Figure 1 As shown, a five-axis CNC machine tool debugging method based on digital twin is provided. This method is executed by computer equipment, specifically by a computer device such as a terminal or server alone, or by a terminal and a server together. In this embodiment, the method is described using a server as an example, including the following steps S1 to S4.

[0018] S1: Establish a digital twin model of a five-axis CNC machine tool.

[0019] Specifically, a multi-domain unified model of a five-axis CNC machine tool is established using the Modelica language, such as... Figure 2 As shown, the digital twin model includes: a mechanical system model, an electrical system model, and a control system model.

[0020] (1) A five-axis topology chain is constructed based on the Modelica.MultiBody library, and the kinematic chain nodes and connection relationships are defined according to the actual mechanical structure of the five-axis CNC machine tool to obtain the mechanical system model; the kinematic chain nodes include the base, X-axis, Y-axis, Z-axis, A rotary table, C rotary table and spindle. Among them, the X-axis, Y-axis and Z-axis are translational axes, and the A rotary table and C rotary table are moving axes.

[0021] The mechanical system model is based on the Modelica.MultiBody library to construct a five-axis topology chain. According to the actual mechanical structure of the five-axis CNC machine tool, the kinematic chain nodes and connection relationships are defined, the kinematic chain nodes are connected to form a kinematic chain, and the motion direction vectors of the translational axis and the rotational axis are defined.

[0022] (2) Construct an electrical system model based on the inverter and permanent magnet synchronous motor of the five-axis CNC machine tool.

[0023] The electrical system model and the mechanical system model interact via an electromechanical interface coupling module. The permanent magnet synchronous motor is integrated with the mechanical shaft to establish a permanent magnet synchronous motor model. The motor output shaft is connected to the mechanical load. The inverter controls the motor stator, while the controller sends voltage commands to the inverter.

[0024] (3) Construct a control system model based on the three-loop control structure of the servo drives of each axis in the five-axis CNC machine tool.

[0025] The control system model accurately simulates the three-loop control structure of each axis servo drive. The implementation process of the three-loop control structure is as follows: the position loop is set as proportional control, PI control and feedforward compensation are constructed, and the current loop is simplified to a first-order inertial element. The position loop output is used as the speed loop input, the actual motor speed is used as feedback, a feedforward speed command is added, and the speed loop output is used as the current loop input.

[0026] After the digital twin model is constructed, its fidelity is verified. The axis motion vibration spectrum and feed rate response characteristics of the digital twin model are monitored in a simulation environment and compared with the data collected by sensors on a five-axis CNC machine tool under the same control commands.

[0027] The vibration spectrum of the shaft motion was obtained by sampling using triaxial accelerometers installed on each shaft slide and at the end of the main shaft. The sampling requirements were as follows:

[0028] in, The sampling frequency (in this embodiment, it is...) ), The maximum sampling frequency (in this embodiment, it is...) ).

[0029] Using step and ramp inputs as test signals, the encoder provides feedback on position and actual speed. The above instructions are written into standard test G-code, and the same instructions are input into the digital twin model established in S1 to obtain the feed rate response characteristics.

[0030] Compare the collected data from the actual sensors with the simulation data. If the error is less than the preset value (5%), it indicates that the digital twin model has fidelity. Otherwise, re-examine and adjust the model in S1.

[0031] S2: Perform virtual RTCP detection on the digital twin model and record the deviation vector between the theoretical blade tip position and the actual blade tip position.

[0032] After verifying the fidelity of the digital twin model, the dynamic accuracy evaluation stage, namely virtual RTCP testing, begins. This step aims to accurately reproduce the standard RTCP test procedure in the digital twin model and quantitatively evaluate the dynamic accuracy performance of the machine tool under five-axis linkage trajectory.

[0033] The input for virtual RTCP detection is the rotary axis command trajectory and the translational axis command trajectory. It adopts the "figure-eight" trajectory recommended by international standards, which can fully reflect the dynamic characteristics of each axis of a five-axis CNC machine tool.

[0034] The rotation axis command trajectory is:

[0035]

[0036] in, Let t be the instruction that turntable A needs to move to the target position at time t. Let A be the reference point for the rotational motion of turntable A. Let A be the swing amplitude of turntable A. The angular frequency of the commanded trajectory of the rotation axis; Let t be the instruction that turntable C needs to move to the target position. This serves as the reference point for the rotational motion of the C-shaped turntable. Let be the swing amplitude of turntable C.

[0037] The translation axis command trajectory is as follows:

[0038] in, This is the instruction that the X-axis needs to move to the target position at time t. This is the instruction that the Y-axis needs to move to the target position at time t. This is the instruction that the Z-axis needs to move to the target position at time t. This is the theoretical distance from the tip of the blade to the center of rotation.

[0039] The above-generated instruction trajectory , , , , The data is synchronously input into a validated high-fidelity digital twin model, which outputs the actual motion response of each axis. Throughout the simulation, the deviation vector between the theoretical and actual tool tip positions is continuously read and recorded. , These are servo parameters.

[0040] S3: Construct an objective function based on the deviation vector, and solve the objective function using the differential evolution algorithm to obtain the optimal servo parameters.

[0041] The servo parameter optimization problem can be formulated as a global optimization problem that minimizes the objective function:

[0042] in, Let D be the decision vector, i.e., the servo parameters, where D is the number of servo parameters, R is a real number, and T denotes the transpose. Objective function. The value obtained by performing virtual RTCP testing using a digital twin model is the maximum deviation vector. .

[0043] The objective function is solved using the differential evolution algorithm, specifically including: initializing the population; each individual in the population represents a set of servo parameters; performing mutation, crossover, and selection on each generation of the population in sequence, and selecting the individual with the smallest fitness value as the optimal servo parameter; the fitness value is the objective function value.

[0044] A population containing multiple candidate solutions is randomly generated, with each individual (candidate solution) representing a set of servo parameters.

[0045]

[0046] in, For the servo parameters to be optimized, To optimize the lower bound of the parameters, To optimize the upper bound of the parameters, is a random number that is uniformly distributed in the interval [0,1].

[0047] For each generation of population Perform the following operations sequentially until the termination condition is met: Mutation operation: for each target vector Generate a mutation vector .

[0048]

[0049] Among them, index To randomly select distinct integers from the population, and belonging to... . The scaling factor is a parameter that controls the degree of scaling of the difference vector, and its value ranges from [value missing].

[0050] Crossover operation: To increase population diversity, the mutation vector is crossed over. With the target vector Mix them to generate test vectors Using binary crossover:

[0051] in, For the experimental vectors to be generated The j-th parameter value, The mutated vector generated by the mutation operation The j-th parameter value, For contemporary target vectors The j-th parameter value, The vector represents the first One dimension, The crossover probability takes a value from 1. The probability that the experimental vector inherits parameters from the mutation vector. It is a randomly selected dimension index that ensures that at least one dimension of the test vector comes from the mutation vector.

[0052] Selection operation: Based on a greedy strategy, the trial vector competes with the target vector, and the best one is selected to enter the next generation of the population.

[0053]

[0054] That is, if the experimental vector If the corresponding objective function value is smaller, then the objective vector is replaced. Become an individual in the next generation. Otherwise, retain the original target vector. It is the i-th individual selected to enter the next generation of the population.

[0055] If the fitness value (here, the bias vector) of the experimental vector is better, it replaces the target vector as an individual in the next generation of the population; otherwise, the original target vector is retained. The optimization process terminates when the algorithm reaches the preset maximum number of iterations or when the optimal solution shows no significant improvement over several consecutive generations. At this point, the global optimal solution is the individual with the smallest objective function value in the current generation of the population, i.e., the optimal combination of servo parameters.

[0056] S4: Debug the five-axis CNC machine tool based on the optimal servo parameters.

[0057] All parameters in this application are first verified within the digital twin model, eliminating the need for repeated start-ups, trial cuts, and manual measurements on the physical machine, thus shortening the testing cycle and eliminating the risk of collisions due to misoperation.

[0058] Based on the same inventive concept, this application also provides a five-axis CNC machine tool debugging system based on digital twins. The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the five-axis CNC machine tool debugging system based on digital twins provided below can be found in the limitations of the five-axis CNC machine tool debugging method based on digital twins above, and will not be repeated here.

[0059] In one exemplary embodiment, a five-axis CNC machine tool debugging system based on digital twins is provided, including the following modules.

[0060] The digital twin model building module is used to create a digital twin model of a five-axis CNC machine tool.

[0061] The virtual RTCP detection module is used to perform virtual RTCP detection on the digital twin model and record the deviation vector between the theoretical blade tip position and the actual blade tip position.

[0062] The objective function construction and solution module is used to construct an objective function based on the deviation vector and solve the objective function using the differential evolution algorithm to obtain the optimal servo parameters.

[0063] The debugging module is used to debug the five-axis CNC machine tool based on the optimal servo parameters.

[0064] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments. The computer device can be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O), and a communication interface. The processor, memory, and I / O interface are connected via a system bus, and the communication interface is connected to the system bus via the I / O interface. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device stores data to be processed. The I / O interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with an external terminal via a network connection. When the computer program is executed by the processor, it implements a five-axis CNC machine tool debugging method based on digital twins.

[0065] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0066] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0067] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0068] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0069] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0070] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A digital-twin-based five-axis NC machine tool commissioning method, characterized by, include: Establish a digital twin model of a five-axis CNC machine tool; Virtual RTCP detection is performed on the digital twin model, and the deviation vector between the theoretical blade tip position and the actual blade tip position is recorded; Based on the deviation vector, an objective function is constructed, and the objective function is solved using the differential evolution algorithm to obtain the optimal servo parameters; The five-axis CNC machine tool is debugged based on the optimal servo parameters.

2. The digital-twin-based five-axis CNC machine tool commissioning method according to claim 1, characterized in that, The digital twin model includes: a mechanical system model, an electrical system model, and a control system model; The establishment of a digital twin model of a five-axis CNC machine tool specifically includes: A five-axis topology chain is constructed based on the Modelica.MultiBody library, and the kinematic chain nodes and connection relationships are defined according to the actual mechanical structure of the five-axis CNC machine tool to obtain the mechanical system model; the kinematic chain nodes include the base, X-axis, Y-axis, Z-axis, A rotary table, C rotary table and spindle; An electrical system model is constructed based on the inverter and permanent magnet synchronous motor of the aforementioned five-axis CNC machine tool; A control system model is constructed based on the three-loop control structure of the servo drives of each axis in the five-axis CNC machine tool.

3. The digital-twin-based five-axis CNC machine tool commissioning method according to claim 2, characterized in that, In the virtual RTCP detection, both the rotation axis command trajectory and the translation axis command trajectory are "figure-eight" shaped trajectories.

4. The five-axis CNC machine tool debugging method based on digital twin according to claim 3, characterized in that, The expression for the shaft command trajectory is: ； ； in, Let t be the instruction that turntable A needs to move to the target position at time t. Let A be the reference point for the rotational motion of turntable A. Let A be the swing amplitude of turntable A. The angular frequency of the axis command trajectory; Let t be the instruction that turntable C needs to move to the target position. This serves as the reference point for the rotational motion of the C-shaped turntable. The oscillation amplitude of turntable C; t represents time. The expression for the translational axis command trajectory is: ； in, This is the instruction that the X-axis needs to move to the target position at time t. This is the instruction that the Y-axis needs to move to the target position at time t. This is the instruction that the Z-axis needs to move to the target position at time t. This is the theoretical distance from the tip of the blade to the center of rotation.

5. The five-axis CNC machine tool debugging method based on digital twin according to claim 1, characterized in that, The objective function is solved using the differential evolution algorithm, specifically including: Initialize the population; each individual in the population represents a set of servo parameters; Each generation of the population is subjected to mutation, crossover, and selection in sequence, and the individual with the smallest fitness value is selected as the optimal servo parameter; the fitness value is the objective function value.

6. The five-axis CNC machine tool debugging method based on digital twin according to claim 1, characterized in that, After establishing the digital twin model of the five-axis CNC machine tool, the next step is to verify the fidelity of the digital twin model.

7. The five-axis CNC machine tool debugging method based on digital twin according to claim 6, characterized in that, Verifying the fidelity of the digital twin model specifically includes: The verification indicators for the five-axis CNC machine tool and the digital twin model are obtained; the verification indicators include the axis motion vibration spectrum and feed speed response characteristics. When the difference between the verification index of the five-axis CNC machine tool and the digital twin model is less than a preset value, the digital twin model is determined to have fidelity.

8. A five-axis CNC machine tool debugging system based on digital twin, characterized in that, include: The digital twin model building module is used to create a digital twin model of a five-axis CNC machine tool; The virtual RTCP detection module is used to perform virtual RTCP detection on the digital twin model and record the deviation vector between the theoretical blade tip position and the actual blade tip position. The objective function construction and solution module is used to construct an objective function based on the deviation vector and solve the objective function using the differential evolution algorithm to obtain the optimal servo parameters; The debugging module is used to debug the five-axis CNC machine tool based on the optimal servo parameters.

9. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the five-axis CNC machine tool debugging method based on digital twin as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the five-axis CNC machine tool debugging method based on digital twin as described in any one of claims 1-7.

Images