A laser cutting thermal error compensation method based on digital twinning

Abstract

A laser cutting thermal error compensation method based on digital twinning, comprising the following steps: S1, establishing a laser heat source model; S2, establishing a thermal deformation theoretical model; setting the boundary conditions of deformation through three basic ways of heat conduction, heat convection and heat radiation, and then describing the thermal deformation through thermal expansion; S3, establishing a finite element model; according to the boundary conditions and workpiece parameters of the finite element model, a finite element model is established, the rationality of the finite element model is verified by using the recommended parameters of the manufacturer, and when it is judged to be reasonable, a discretized real-time machining data set is generated; S4, the discretized real-time machining data set is used as the training data set of the machine learning algorithm to predict the thermal deformation of the cutting process and generate a thermal deformation prediction cloud picture; S5, cutting; the virtual and real information transmission is driven through the digital twinning technology, and the cutting speed is compensated in real time according to the size of the cutting thermal deformation. The application can reduce the thermal deformation amount at the cutting seam, reasonably avoid thermal error, and improve the laser cutting precision.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of laser cutting, and particularly relates to a laser cutting thermal error compensation method based on digital twinning. BACKGROUND

[0002] Laser cutting is widely used for its high speed and high precision, and the overall precision is determined by machine tool performance, laser performance, workpiece properties, processing parameters and processing phenomena, as shown in the formula. Figure 1 Among them, the machine tool performance and the laser generator attenuation period are long, and it is difficult to be used as the main representation factor of real-time processing precision for research. When the workpiece material is certain, the processing parameters and the thermal phenomena in the cutting process play a decisive role in the processing precision. When cutting, the surface temperature field and the structure field of the workpiece form a solid-thermal coupling, and thermal expansion phenomenon occurs, and the cutting speed is the decisive factor of the amount of heat absorbed by the workpiece. Therefore, the cutting speed is selected as the main representation factor and compensation parameter of the change of laser cutting precision.

[0003] Most of the existing laser cutting parameter optimization schemes are empirical models, and the cutting speed is adjusted according to a large number of processing results, so as to improve the cutting precision. This method is not only time-consuming and laborious, but also has high economic cost, and does not fully consider the influence of the change of the motion state of the laser generator in the time dimension on the cutting seam. SUMMARY

[0004] In order to reduce the time and economic cost and improve the precision of laser cutting, the application provides a laser cutting thermal error compensation method based on digital twinning, and the specific scheme is as follows.

[0005] A laser cutting thermal error compensation method based on digital twinning comprises the following steps:

[0006] S1, establishing a laser heat source model;

[0007] S2, establishing a thermal deformation theoretical model; the boundary conditions of deformation are set through three basic ways of heat conduction, heat convection and heat radiation, and the thermal deformation is described through thermal expansion according to the boundary conditions;

[0008] S3, establishing a finite element model; the model is established according to the boundary conditions and workpiece parameters of the finite element model, the rationality of the finite element model is verified by using the recommended parameters of the manufacturer, and when it is judged to be reasonable, the discretized real-time processing data set is generated;

[0009] S4, using the discretized real-time processing data set as the training data set of the machine learning algorithm to predict the thermal deformation of the cutting process and generate a thermal deformation prediction cloud map;

[0010] S5, cutting; the virtual-real information transmission is driven through the digital twinning technology, and the cutting speed is compensated in real time according to the size of the cutting thermal deformation.

[0011] Specifically, step S5 further generates a visualized thermal deformation digital model.

[0012] Specifically, the heat source model in step S1 is as follows:

[0013] The heat flux density formula of the laser heat source is

[0014]

[0015]

[0016] wherein q m is the maximum heat flux at the center of the heat source, P is the total power of the heat source, K is the heat source concentration coefficient, and (x, y) is the distance between the point (x, y) and the maximum heat source point in the X direction and the Y direction.

[0017] Specifically, the boundary conditions of deformation are set by three basic ways of heat conduction, heat convection and heat radiation, and are as follows:

[0018]

[0019] The first type of boundary condition is used to describe the temperature distribution on the boundary of the system, Γ is the boundary range, T is the temperature, and t is the time; wherein T / Γ1 is a constant, which is a steady-state condition, and T(Γ, t) is expressed as a function of time, which is a non-steady-state heat source; the second type of boundary condition describes whether heat flows into or out of the boundary, q s is the heat flux density, wherein is the normal direction outside the boundary of the system; when , it is an adiabatic boundary; when , it is a constant heat flux boundary; when , it is a non-constant heat flux boundary; the third type of boundary condition is used to describe the heat exchange between the system and the outside world, k is the heat conduction coefficient, ε is the surface emissivity, σ is the Stefan-Boltzmann constant, T amb is the ambient temperature.

[0020] Specifically, the formula for describing the thermal deformation amount is as follows:

[0021] ε = αT(T - T ref )

[0022] wherein ε is the thermal deformation amount, α is the thermal expansion secant coefficient, which is related to the processed material, T is the input temperature, which comes from the finite element temperature field simulation, and T ref is the processing environment temperature.

[0023] The beneficial effects of the present application are:

[0024] (1) According to the Gaussian law, the laser heat source model is established, and the thermal deformation theoretical model is established according to the Fourier law. Secondly, the visual finite element simulation model is established, and the rationality of the finite element model is verified by using the technical parameters recommended by the manufacturer, and the discrete real-time processing data set is simulated, and the finite element data set conforming to the actual processing is used as the training data set of the machine learning algorithm to optimize the processing parameters. Through the digital twin technology to drive the virtual and real information transmission, a hybrid model of'model driven + data driven' is constructed to realize high approximation simulation and real-time compensation of cutting speed, reduce the thermal deformation of the cutting seam, reasonably avoid thermal errors, and improve the laser cutting precision.

[0025] (2) Borrowing the visual characteristics of the finite element model, the operator can observe the cutting progress in real time, reduce the scrap rate, and improve the work efficiency.

[0026] (3) In the working process of the laser cutting machine, the cutting speed has time-varying nature, especially at the starting and ending stages, relying on the mapping ability of the digital twin technology to the time-varying nature, a full-cycle speed optimization strategy is established.

[0027] (4) The generation of the visual thermal deformation digital model not only allows the operator to observe the cutting progress in real time, but also enables real-time monitoring of the thermal deformation. BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 A structure diagram of a laser cutting thermal error compensation method based on digital twinning is proposed.

[0029] Figure 2 It is a heat source model.

[0030] Figure 3 It is a thermal deformation simulation cloud chart of the cutting seam at a certain moment. DETAILED DESCRIPTION

[0031] As shown in Figure 1 , a laser cutting thermal error compensation method based on digital twinning, characterized in that it comprises the following steps:

[0032] S1, establish a laser heat source model; the heat source is based on the Gaussian model and has maximum flow at the intersection and decreases towards the periphery;

[0033] Specifically, the heat source model is as follows:

[0034] As shown in Figure 2 , the laser cutting equipment has a complex structure, and in the processing process, except for the support for fixing the workpiece, it does not contact the workpiece, which has little effect on the simulation results. Therefore, the mechanical part is reasonably simplified as a laser heat source. Laser is not a uniform heat source, and its heat flux density formula is

[0035]

[0036]

[0037] In the formula q m Let P be the maximum heat flux at the center of the heat source, P be the total power of the heat source, and K be the heat source concentration factor. The heat flux density at any point (x, y) is related to its distance from the center of the maximum heat source; that is, the closer to the center, the greater the heat flux density. The rate of increase in heat flux density is related to the heat source concentration factor.

[0038] S2. Establish a theoretical model for thermal deformation; set the boundary conditions for deformation through the three basic modes of heat conduction, heat convection and heat radiation, and then describe the thermal deformation through thermal expansion based on the boundary conditions.

[0039] The boundary conditions for deformation are defined using the three basic modes of heat conduction, heat convection, and heat radiation, as follows:

[0040]

[0041] The first type of boundary condition describes the temperature distribution on the system boundary, where Γ is the boundary range, T is the temperature, and t is the time. Where T / Γ1 When q is a constant, it represents a steady-state condition; when T(Γ,t) is expressed as a time function, it represents a non-steady-state heat source. The second type of boundary condition describes whether heat flows in or out of the boundary, q s Let be the heat flux density, where This is the direction of the outward normal to the system boundary. When... When, it is an adiabatic boundary; when When the heat flux is constant, it is a constant heat flux boundary; when When the heat flux is a time-dependent function, it is a non-constant heat flux boundary. During the cutting process, the laser heat source moves along the cutting trajectory according to the cutting speed, which changes with time, resulting in a non-steady-state, non-constant heat flux boundary. The third type of boundary condition is used to describe the heat exchange between the system and the external environment, where k is the thermal conductivity, ε is the surface emissivity, σ is the Stefan-Boltzmann constant, and T... amb The ambient temperature.

[0042] Based on the boundary conditions, the thermal deformation can be further described by thermal expansion as follows:

[0043] During laser cutting, the heat source moves at high speed, causing localized heating at the cut edge. This heating results in rapid and intense expansion, accompanied by deformation. The cut edge undergoes elastic deformation due to thermal expansion, which is short-lived and gradually recovers after the heat source passes. However, when the thermal stress in the heated area exceeds the material's yield strength, plastic deformation occurs. This deformation has a significant impact on machining accuracy.

[0044] ε=αT(TTref )

[0045] wherein ε is the thermal deformation, α is the thermal expansion secant coefficient, which is related to the machined material, T is the input temperature, which is from the finite element temperature field simulation, T ref is the processing environment temperature.

[0046] S3, a finite element model is established; a model is established according to boundary conditions and workpiece parameters of the finite element model, the rationality of the finite element model is verified by using manufacturer recommended parameters, and when it is judged to be reasonable, a discretized real-time machining data set is generated;

[0047] S4, the finite element data set conforming to the machining actuality is taken as a training data set of a machine learning algorithm to predict the thermal deformation of the cutting process, and a thermal deformation prediction cloud map as shown in Figure 3 is generated;

[0048] S5, cutting; virtual-real information transmission is driven by a digital twinning technology, a visual thermal deformation digital model is generated by real-time compensation of the cutting speed according to the size of the cutting thermal deformation, and a compensated thermal deformation cloud map is generated.

[0049] The above is only a preferred specific embodiment of the present application, but the protection scope of the present application is not limited to this, any person skilled in the art can make equivalent replacement or change according to the technical solution and the inventive concept of the present application within the technical range disclosed by the present application, which should be covered in the protection scope of the present application.

Claims

1. A method for compensating thermal errors in laser cutting based on digital twins, characterized in that, Includes the following steps: S1. Establish a laser heat source model; S2. Establish a theoretical model for thermal deformation; set the boundary conditions for deformation through the three basic modes of heat conduction, heat convection and heat radiation, and then describe the thermal deformation through thermal expansion based on the boundary conditions. S3. Establish a finite element model; establish a model based on the boundary conditions and machining parameters of the finite element model, verify the rationality of the finite element model with the manufacturer's recommended parameters, and generate a discretized real-time machining dataset when the model is deemed reasonable. S4. Use the discretized real-time processing dataset as the training dataset for machine learning algorithms to predict the thermal deformation of the cutting process and generate a thermal deformation prediction cloud map. S5. Cutting; Driven by digital twin technology, the transmission of virtual and real information is accelerated, and the cutting speed is compensated in real time according to the amount of thermal deformation during cutting. The heat source model in step S1 is as follows: The formula for the heat flux density of a laser heat source is: ； ； In the formula Let P be the maximum heat flux at the center of the heat source, K be the heat source concentration factor, and (x, y) be the distance between point (x, y) and the maximum heat source point in the X and Y directions, respectively. The boundary conditions for deformation are defined using the three basic modes of heat conduction, heat convection, and heat radiation, as follows: ； The first type of boundary condition is used to describe the temperature distribution on the system boundary. The boundary range is defined by T, where T is the temperature and t is the time. in When is a constant, it is a steady-state condition; when When expressed as a time function, it is an unsteady heat source; the second type of boundary condition describes whether heat flows in or out of the boundary. Let be the heat flux density, where The direction of the outward normal to the system boundary; when When, it is an adiabatic boundary; when When the heat flux is constant, it is a constant heat flux boundary; when When the heat flux is a time-dependent function, it is a non-constant heat flux boundary condition; the third type of boundary condition is used to describe the heat exchange between the system and the surroundings, where k is the thermal conductivity coefficient. For surface emissivity, This is the Stefan-Boltzmann constant. The ambient temperature.

2. The laser cutting thermal error compensation method based on digital twin according to claim 1, characterized in that, Step S5 also generates a visualized digital model of thermal deformation.

3. The laser cutting thermal error compensation method based on digital twin according to claim 1, characterized in that, The formula for describing thermal deformation using thermal expansion is as follows: ； in, This is the amount of thermal deformation. The coefficient of thermal expansion is secant, which is related to the material being processed. T is the input temperature, derived from finite element temperature field simulation. The processing environment temperature.

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