Digital twin modeling method of laser pipe cutting equipment

Abstract

The invention relates to the technical field of intelligent manufacturing and digital twinning, in particular to a digital twinning modeling method of laser pipe cutting equipment, which comprises the following steps: S1, acquiring pipe clamping deformation parameters in real time through a multi-axis sensor array on a clamping mechanism; s2, performing reverse geometric reconstruction based on the pipe clamping deformation parameters; s3, energy absorption parameters are determined according to the dynamic relation between the laser incident angle and the pipe surface reflectivity; s4, equivalent heat flux density distribution on the laser cutting path is calculated; s5, predicting the width of a heat affected zone of the cutting area; and S6, integrating the deformation compensation coefficient, the width of the heat affected zone and the equivalent heat flux density distribution, and constructing a digital twinborn model of the laser pipe cutting equipment. According to the method, the digital twinborn model is constructed by fusing deformation compensation, heat input distribution and response characteristics, and precise modeling of multi-physics field cooperative behaviors in the laser cutting process and dynamic prediction of the heat affected zone are achieved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent manufacturing and digital twin technologies, and in particular to a digital twin modeling method for laser tube cutting equipment. Background Art

[0002] With the continuous advancement of intelligent manufacturing and industrial digitalization, laser tube cutting equipment is increasingly used in aerospace, automobile manufacturing, precision engineering and other fields; the laser cutting process involves the synergistic effect of laser energy input, thermal diffusion response and material deformation, which puts higher requirements on cutting path accuracy and heat-affected zone control; traditional CNC tube cutting systems generally rely on static geometric models and preset parameters for path planning and thermal simulation, which makes it difficult to reflect the impact of clamping deformation on the actual geometry of the pipe. At the same time, there is a lack of real-time response modeling of laser incident behavior and material surface dynamic characteristics (such as reflectivity and absorptivity), resulting in a large deviation between simulation and actual processing, which restricts the further improvement of process optimization and online control capabilities.

[0003] Existing technologies lack a high-precision digital twin modeling method that can simultaneously integrate the pipe clamping state, laser heat input characteristics, and changes in the thermal response area. Traditional modeling approaches struggle to achieve efficient coordination of three-dimensional multi-physics fields, especially when faced with complex deformations, multi-source parameter linkage, and nonlinear heat conduction behavior, and are unable to dynamically predict the changing trends of the heat-affected zone along the cutting path. Therefore, a digital twin modeling method for laser pipe cutting equipment is urgently needed to address these issues. Summary of the Invention

[0004] Based on the above objectives, the present invention provides a digital twin modeling method for laser tube cutting equipment.

[0005] The digital twin modeling method for laser tube cutting equipment includes the following steps:

[0006] S1: Obtaining the pipe clamping deformation parameters in real time through the multi-axis sensor array on the clamping mechanism, wherein the pipe clamping deformation parameters include the axial stress distribution gradient and the radial displacement deviation;

[0007] S2: Perform reverse geometry reconstruction based on the pipe clamping deformation parameters to generate a pipe solid model including deformation compensation coefficients;

[0008] S3: Real-time acquisition of the laser incident angle and the pipe surface reflectivity, and determination of the energy absorption parameters based on the dynamic relationship between the laser incident angle and the pipe surface reflectivity;

[0009] S4: Input the tube solid model and energy absorption parameters into the thermal-mechanical coupling simulation module to calculate the equivalent heat flux density distribution on the laser cutting path;

[0010] S5: Predict the width of the heat-affected zone in the cutting area based on the equivalent heat flux density distribution and deformation compensation coefficient;

[0011] S6: Integrate the above deformation compensation coefficient, heat-affected zone width and equivalent heat flux density distribution to build a digital twin model of laser tube cutting equipment.

[0012] Optionally, the S1 specifically includes:

[0013] S11: Arrange a multi-axis sensor array in the circumferential and axial directions of the clamping mechanism, and establish a spatial coordinate system of the sensor array;

[0014] S12: The axial strain signal of the pipe after clamping is collected in real time through the strain sensor in the sensor array and converted into the axial stress distribution gradient based on Hooke's law. The calculation formula of the axial stress distribution gradient is:

[0015] Among them, σ z is the axial stress distribution gradient; E is the elastic modulus of the pipe material; ΔL is the axial strain of the pipe; L0 is the initial clamping length of the pipe;

[0016] S13: The radial position change of the pipe is measured in real time by the displacement sensor in the sensor array to obtain the radial displacement deviation. The calculation formula of the radial displacement deviation is: δ r =r-r0, where δ r is the radial displacement deviation; r is the radial position of the pipe measured in real time; r0 is the initial radial position of the pipe.

[0017] Optionally, the S2 specifically includes:

[0018] S21: Inputting the pipe clamping deformation parameters into the reverse reconstruction unit, and constructing the initial deformation point cloud data of the pipe based on the measured axial stress distribution gradient and radial displacement deviation;

[0019] S22: Based on the initial deformed point cloud data, a point cloud surface reconstruction algorithm is used to perform surface fitting processing to generate a deformed surface model of the pipe;

[0020] S23: Based on the deformable surface model of the pipe, the pipe solid model is constructed through the topological mapping relationship from the surface model to the solid model;

[0021] S24: Based on the numerical characteristics of the axial stress distribution gradient, a linear regression algorithm is used to determine the corresponding deformation compensation coefficient, and the deformation compensation coefficient is assigned to the pipe solid model.

[0022] Optionally, the S24 specifically includes:

[0023] S241: Based on the measured data of the axial stress distribution gradient and the corresponding actual deformation of the pipe, a linear regression data set is established and the data set is preprocessed for standardization;

[0024] S242: Using a linear regression algorithm, with minimizing the prediction error as the optimization goal, determine the fitting relationship between the axial stress distribution gradient and the deformation compensation coefficient. The specific optimization objective function is:

[0025] Where J(θ) is the optimization objective function of the linear regression algorithm; m is the total number of data points in the data set; C i is the actual deformation compensation coefficient corresponding to the i-th data point; σ zi is the axial stress distribution gradient corresponding to the i-th data point; θ0, θ1 are the linear regression coefficients obtained by the algorithm;

[0026] S243: Calculate the deformation compensation coefficient C in the current pipe clamping state based on the linear regression coefficients θ0 and θ1 obtained by solving;

[0027] S244: The current deformation compensation coefficient calculated in S243 is embedded into the pipe solid model as an attribute parameter to complete the correction of the pipe solid model.

[0028] Optionally, the S3 specifically includes:

[0029] S31: A laser three-dimensional posture sensor is set in the interaction area between the laser head and the pipe surface to collect the incident angle α of the laser beam relative to the cutting surface of the pipe in real time;

[0030] S32: using a surface reflectivity monitoring module to obtain a unit area reflectivity ρ of the laser irradiated area of ​​the pipe;

[0031] S33: Input the incident angle α and the surface reflectivity ρ into the absorption model calculation unit, and calculate the energy absorption parameter of the laser at the current incident angle based on the nonlinear relationship between the two. The formula is: η=1-ρ·cos n (α), where η is the laser energy absorption parameter and n is the fitting constant.

[0032] Optionally, the S4 specifically includes:

[0033] S41: importing the pipe solid model including the deformation compensation coefficient generated in S2 into the thermal-mechanical coupling simulation module as the three-dimensional geometric input basis of the object to be analyzed;

[0034] S42: mapping the energy absorption parameters calculated in S3 to the surface of the tube solid model according to the coordinates of each point on the laser scanning path, thereby forming the initial boundary conditions for the spatial distribution of the laser input heat source;

[0035] S43: Set the thermophysical properties of the pipe material in the simulation module, including thermal conductivity, specific heat capacity, and density, and determine the heat source movement trajectory based on the time history of laser processing;

[0036] S44: The finite element method is used to dynamically solve the heat transfer process of the heat source on the cutting path and calculate the instantaneous heat flux density distribution at any time t and spatial position. The formula is:

[0037] Where q(x, y, z, t) is the equivalent heat flux density at the time t and position (x, y, z); η is the energy absorption parameter of the corresponding point; P is the total power of the laser beam; r b is the laser spot radius; (x0(t), y0(t)) is the center coordinate position of the laser heat source on the surface at time t.

[0038] Optionally, the S5 specifically includes:

[0039] S51: extract the peak heat flux density sequence and the corresponding heat source residence time sequence of each microelement on the cutting path from the equivalent heat flux density distribution obtained in S4, and establish a heat input time history database;

[0040] S52: Inputting the heat input time history database and the thermophysical property parameters of the pipe material into a transient heat conduction analysis module to calculate the three-dimensional temperature field distribution around the cutting path;

[0041] S53: setting a critical metallurgical phase transformation temperature threshold of 650° C. in the three-dimensional temperature field, searching for an isothermal surface that meets the threshold, and determining an initial heat-affected zone contour;

[0042] S54: performing axial and radial coordinate correction on the initial heat-affected zone profile according to the deformation compensation coefficient obtained in S2, and generating a corrected heat-affected zone profile curve;

[0043] S55: performing cross-sectional analysis on the corrected heat-affected zone contour curve along the cutting path, calculating the maximum radial distance between the heat-affected zone contour curve and the slit centerline on each section, and outputting the heat-affected zone width of the cutting area.

[0044] Optionally, the S54 specifically includes:

[0045] S541: Extract the original space coordinates of each boundary point in the initial heat-affected zone contour, set as (u j , r j ), where u j is the position coordinate of the jth point in the axial direction of the tube; r j is the radial distance of the point relative to the cutting center axis;

[0046] S542: Obtain the deformation compensation coefficient C calculated in S2, and perform coordinate correction on the axial position of the contour point. The coordinate after axial correction is expressed as: u j ′=u j +C·Δu, where u j ′ is the coordinate after axial correction; Δu is the average length offset caused by axial strain in the clamped state; C is the deformation compensation coefficient;

[0047] S543: At the same time, the radial position of the contour point is corrected. The coordinate after radial correction is expressed as: r j ′=r j +C·Δr, where r j ′ is the coordinate after radial correction; Δr is the average displacement deviation in the radial direction;

[0048] S544: All corrected contour points are connected in order to construct a corrected contour curve of the heat-affected zone, and the corrected contour curve is superimposed and compared with the original contour to complete the thermal response adjustment under deformation compensation.

[0049] Optionally, the S55 specifically includes:

[0050] S551: Along the axial direction of the laser cutting path, a series of sections perpendicular to the cutting path are selected on the heat-affected zone correction contour curve. Each section is based on the tube axial coordinate u j ' is the center of the local section coordinate system;

[0051] S552: In each local section coordinate system, obtain all intersection points of the modified contour curve and the corresponding slit center line, and measure the radial distances from these intersection points to the center line, set as r jk ′, where k represents the kth intersection point on the cross section;

[0052] S553: ​​For each section, calculate the maximum value of all radial distances to obtain the width W of the heat-affected zone on the section. j , the calculation formula is: W j =2·max k (|r jk ′|), where W j is the width of the heat-affected zone on the jth section; |r jk ′| is the absolute radial distance from the kth intersection point to the center line of the slit;

[0053] S554: The width of the heat-affected zone W on all cross sections j The heat affected zone width distribution curve of the entire cutting path is generated by summarizing them one by one.

[0054] Optionally, the S6 specifically includes:

[0055] S61: Construct a multidimensional data structure including the deformation compensation coefficient C, the equivalent heat flux density distribution q(x, y, z, t), and the heat-affected zone width W(u), which correspond to the basic physical information of the geometric field, thermal field, and response field respectively;

[0056] S62: Input the multidimensional data structure into the digital twin modeling engine and establish the physical coupling mapping relationship between model parameters through the three-field joint indexing mechanism;

[0057] S63: By establishing the transfer function relationship between physical fields, a response prediction model driven by input variables C, q (x, y, z, t) and W (u) is formed. The functions are logically combined through the coupling kernel function to obtain a complete digital twin model of laser tube cutting equipment. The specific expression is:

[0058] M DT =F(C, q(x, y, z, t), W(u)), where, M DT represents the constructed digital twin model of laser tube cutting equipment; F( ) represents the transfer function library after integrating the three-field information, which is used to realize the simulation and prediction of processing response under input conditions.

[0059] Beneficial effects of the present invention:

[0060] The present invention acquires the pipe clamping deformation parameters in real time through an integrated multi-axis sensor array, adopts inverse geometric reconstruction and point cloud surface fitting algorithms, and combines linear regression to accurately calculate the deformation compensation coefficient, thereby achieving high-precision correction of the pipe solid model. This method significantly improves the coupling accuracy of geometric modeling and clamping conditions, laying an accurate physical foundation for subsequent thermal field simulation and response analysis.

[0061] The present invention dynamically associates the laser incident angle, surface reflectivity and energy absorption parameters, introduces equivalent heat flux density and deformation compensation information in the thermal-mechanical coupling simulation, and constructs a structured digital twin model through the integration of multi-field physical data and transfer function coupling. This model can accurately predict the spatial distribution of the heat-affected zone of the cutting path in real time, providing strong data support and theoretical basis for virtual simulation, process optimization and intelligent decision-making of laser cutting equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0063] Figure 1Schematic diagram of a digital twin modeling method according to an embodiment of the present invention;

[0064] Figure 2 Schematic diagram of the process of generating a pipe solid model according to an embodiment of the present invention. DETAILED DESCRIPTION

[0065] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. It is also noted that, to provide a more detailed description, the following embodiments are best and preferred embodiments, and those skilled in the art may employ alternative methods for implementing certain known technologies. Furthermore, the accompanying drawings are intended only to provide a more detailed description of the embodiments and are not intended to limit the present invention.

[0066] It should be noted that references in the specification to "one embodiment," "an embodiment," "an exemplary embodiment," "some embodiments," etc. indicate that the described embodiments may include specific features, structures, or characteristics, but not every embodiment necessarily includes such specific features, structures, or characteristics. In addition, when specific features, structures, or characteristics are described in conjunction with an embodiment, it is within the knowledge of persons skilled in the relevant art to implement such features, structures, or characteristics in conjunction with other embodiments (whether or not explicitly described).

[0067] In general, terms can be understood, at least in part, from their use in context. For example, depending at least in part on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending at least in part on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0068] like Figure 1-Figure 2 As shown in FIG, the digital twin modeling method of laser tube cutting equipment includes the following steps:

[0069] S1: The multi-axis sensor array on the clamping mechanism is used to obtain the pipe clamping deformation parameters in real time. The pipe clamping deformation parameters include the axial stress distribution gradient and the radial displacement deviation.

[0070] S2: Reverse geometric reconstruction is performed based on the pipe clamping deformation parameters to generate a pipe solid model including a deformation compensation coefficient, where the deformation compensation coefficient is positively correlated with the axial stress distribution gradient;

[0071] S3: Real-time acquisition of the laser incident angle and the pipe surface reflectivity, and determination of the energy absorption parameters based on the dynamic relationship between the laser incident angle and the pipe surface reflectivity;

[0072] S4: Input the tube solid model and energy absorption parameters into the thermal-mechanical coupling simulation module to calculate the equivalent heat flux density distribution on the laser cutting path;

[0073] S5: Predict the width of the heat-affected zone in the cutting area based on the equivalent heat flux density distribution and deformation compensation coefficient;

[0074] S6: Integrate the above deformation compensation coefficient, heat-affected zone width and equivalent heat flux density distribution to build a digital twin model of laser tube cutting equipment. The digital twin model contains a transfer function relationship library of deformation and thermal coupling.

[0075] S1 specifically includes:

[0076] S11: Arrange a multi-axis sensor array in the circumferential and axial directions of the clamping mechanism, and establish a spatial coordinate system of the sensor array;

[0077] S12: The axial strain signal of the pipe after clamping is collected in real time through the strain sensor in the sensor array and converted into the axial stress distribution gradient based on Hooke's law. The calculation formula of the axial stress distribution gradient is:

[0078] Among them, σ z is the axial stress distribution gradient; E is the elastic modulus of the pipe material; ΔL is the axial strain of the pipe; L0 is the initial clamping length of the pipe;

[0079] S13: The radial position change of the pipe is measured in real time by the displacement sensor in the sensor array to obtain the radial displacement deviation. The calculation formula of the radial displacement deviation is: δ r =r-r0, where δ r is the radial displacement deviation; r is the real-time measured radial position of the pipe; r0 is the initial radial position of the pipe. Through the above steps, it is clear that the axial stress distribution gradient and radial displacement deviation during the pipe clamping process can be accurately obtained in real time through the sensor array, which ensures the basic data accuracy of digital twin modeling and improves the accuracy of modeling and simulation.

[0080] S2 specifically includes:

[0081] S21: Inputting the pipe clamping deformation parameters into the reverse reconstruction unit, and constructing the initial deformation point cloud data of the pipe based on the measured axial stress distribution gradient and radial displacement deviation;

[0082] S22: Based on the initial deformed point cloud data, a point cloud surface reconstruction algorithm is used to perform surface fitting processing to generate a deformed surface model of the pipe;

[0083] The above S22 specifically includes:

[0084] S221: Denoising the initial deformed point cloud data by using a statistical filtering algorithm to remove outliers and retain valid data points. The statistical filtering algorithm calculates the average distance between each data point and its neighboring data points and removes data points whose distance exceeds a set threshold.

[0085] S222: Perform spatial grid division on the denoised point cloud data and establish the spatial topological connection relationship between adjacent data points using the 3D Delaunay triangulation algorithm;

[0086] S223: Based on the spatial topological connection relationship, a least squares surface fitting algorithm is used to perform surface interpolation on each triangular mesh area to obtain a fitting surface model of each local area. The objective function of the least squares surface fitting algorithm is: Among them, F(x, y, z) is the objective function of the fitting algorithm, x i ,y i , z i are the spatial coordinates of the i-th point cloud data point, f(x i ,y i ) is the fitting surface function to be determined;

[0087] S224: All local fitting surface models are spliced ​​and smoothed to generate a complete and continuous pipe deformation surface model.

[0088] S23: Based on the deformable surface model of the pipe, the pipe solid model is constructed through the topological mapping relationship from the surface model to the solid model;

[0089] S24: Based on the numerical characteristics of the axial stress distribution gradient, a linear regression algorithm is used to determine the corresponding deformation compensation coefficient, and the deformation compensation coefficient is assigned to the pipe solid model to achieve accurate correction of the pipe solid model; through the limitations of the above steps S21 to S24, accurate reverse geometric reconstruction based on the pipe clamping deformation parameters is achieved, and a high-precision pipe solid model including the deformation compensation coefficient is generated, which effectively improves the adaptability and accuracy of the digital twin model to actual working conditions.

[0090] S24 specifically includes:

[0091] S241: Based on the measured data of the axial stress distribution gradient and the corresponding actual deformation of the pipe, a linear regression data set is established and the data set is preprocessed for standardization;

[0092] S242: Using a linear regression algorithm, with minimizing the prediction error as the optimization goal, determine the fitting relationship between the axial stress distribution gradient and the deformation compensation coefficient. The specific optimization objective function is:

[0093] Where J(θ) is the optimization objective function of the linear regression algorithm; m is the total number of data points in the data set; C i is the actual deformation compensation coefficient corresponding to the i-th data point; σ zi is the axial stress distribution gradient corresponding to the i-th data point; θ0, θ1 are the linear regression coefficients obtained by the algorithm;

[0094] S243: Based on the linear regression coefficients θ0 and θ1 obtained by solving, the deformation compensation coefficient C under the current pipe clamping state is calculated. The formula is: C = θ0 + θ1σ z , where C is the deformation compensation coefficient under the real-time pipe clamping state; σ z The axial stress distribution gradient is measured in real time under the current pipe clamping state;

[0095] S244: The current deformation compensation coefficient calculated in S243 is embedded as an attribute parameter in the pipe solid model to complete the correction of the pipe solid model; through the limitations of the above steps S241 to S244, the deformation compensation coefficient is accurately calculated and effectively assigned, which is conducive to the digital twin model to more accurately reflect the state of the pipe under the actual clamping conditions, and improve the accuracy of subsequent simulation analysis and prediction.

[0096] S3 specifically includes:

[0097] S31: A laser three-dimensional posture sensor is set in the interaction area between the laser head and the pipe surface to collect the incident angle α of the laser beam relative to the cutting surface of the pipe in real time. The incident angle α is the angle between the laser beam direction and the normal direction of the pipe surface;

[0098] S32: Use the surface reflectivity monitoring module to obtain the unit area reflectivity ρ of the laser irradiated area of ​​the pipe. The surface reflectivity monitoring module includes a multi-channel photoelectric detection array and a high-frequency sampling circuit, which can collect the reflected light intensity I at the instant of laser irradiation. r and the incident light intensity I0, and is converted to reflectivity using the following formula:

[0099] S33: Input the incident angle α and the surface reflectivity ρ into the absorption model calculation unit, and calculate the energy absorption parameter of the laser at the current incident angle based on the nonlinear relationship between the two. The formula is: η=1-ρ·cos n(α), where η is the laser energy absorption parameter; n is a fitting constant obtained by experimental calibration based on the pipe material and surface roughness; through the technical limitations of the above steps S31 to S33, the laser incident angle and surface reflectivity can be obtained in real time and accurately based on the laser three-dimensional posture and reflected light intensity information, and the actual absorption degree of laser energy can be quantified through a physical model, providing a heat input basis for subsequent thermal-mechanical coupling simulation, thereby effectively improving the accuracy of thermal field modeling and its correspondence to reality.

[0100] S4 specifically includes:

[0101] S41: importing the pipe solid model including the deformation compensation coefficient generated in S2 into the thermal-mechanical coupling simulation module as the three-dimensional geometric input basis of the object to be analyzed;

[0102] S42: mapping the energy absorption parameters calculated in S3 to the surface of the tube solid model according to the coordinates of each point on the laser scanning path, thereby forming the initial boundary conditions for the spatial distribution of the laser input heat source;

[0103] S43: Set the thermophysical properties of the pipe material in the simulation module, including thermal conductivity, specific heat capacity, and density, and determine the heat source movement trajectory based on the time history of laser processing;

[0104] S44: The finite element method is used to dynamically solve the heat transfer process of the heat source on the cutting path and calculate the instantaneous heat flux density distribution at any time t and spatial position. The formula is:

[0105] Where q(x, y, z, t) is the equivalent heat flux density at the time t and position (x, y, z); η is the energy absorption parameter of the corresponding point; P is the total power of the laser beam; r b is the laser spot radius; (x0(t), y0(t)) is the central coordinate position of the laser heat source on the surface at time t; through the definition of the above steps, high-precision thermal-mechanical coupling of the spatial distribution of laser energy and the physical structure of the pipe can be achieved, and the equivalent heat flux density distribution on the laser cutting path can be quantitatively output, providing a real physical basis for the subsequent prediction of the heat-affected zone.

[0106] S5 specifically includes:

[0107] S51: extract the peak heat flux density sequence and the corresponding heat source residence time sequence of each microelement on the cutting path from the equivalent heat flux density distribution obtained in S4, and establish a heat input time history database;

[0108] S52: Input the heat input time history database and the thermal physical properties of the pipe material (thermal conductivity, specific heat capacity, density) into the transient heat conduction analysis module to calculate the three-dimensional temperature field distribution around the cutting path; the temperature field calculation satisfies the following heat conduction control equation: Among them, ρ m is the density of the pipe; c p is the specific heat capacity; T is the temperature field distribution function; t is the time; k is the thermal conductivity; q is the equivalent heat flux density;

[0109] S53: setting a critical metallurgical phase transformation temperature threshold of 650° C. in the three-dimensional temperature field, searching for an isothermal surface that meets the threshold, and determining an initial heat-affected zone contour;

[0110] S54: performing axial and radial coordinate correction on the initial heat-affected zone profile according to the deformation compensation coefficient obtained in S2, and generating a corrected heat-affected zone profile curve;

[0111] S55: Perform cross-sectional analysis on the corrected HAZ contour curve along the cutting path, calculate the maximum radial distance between the HAZ contour curve and the kerf centerline on each section, and output the HAZ width of the cutting area. By limiting the above steps and combining the equivalent heat flux density distribution with the deformation compensation coefficient, the HAZ width of the cutting area under actual clamping deformation conditions can be accurately predicted, ensuring that the digital twin model's description of the laser heat diffusion range is consistent with the measured working conditions, thereby improving the reliability of subsequent process optimization decisions.

[0112] S54 specifically includes:

[0113] S541: Extract the original space coordinates of each boundary point in the initial heat-affected zone contour, set as (u j , r j ), where u j is the position coordinate of the jth point in the axial direction of the tube; r j is the radial distance of the point relative to the cutting center axis;

[0114] S542: Obtain the deformation compensation coefficient C calculated in S2, and perform coordinate correction on the axial position of the contour point. The coordinate after axial correction is expressed as: u j ′=u j +C·Δu, where u j ′ is the coordinate after axial correction; Δu is the average length offset caused by axial strain in the clamped state; C is the deformation compensation coefficient;

[0115] S543: At the same time, the radial position of the contour point is corrected. The coordinate after radial correction is expressed as: r j ′=r j +C·Δr, where r j ′ is the coordinate after radial correction; Δr is the average displacement deviation in the radial direction;

[0116] S544: All corrected contour points are connected in order to construct a corrected contour curve of the heat-affected zone, and the corrected contour curve is superimposed and compared with the original contour to complete the thermal response adjustment under deformation compensation.

[0117] S55 specifically includes:

[0118] S551: Along the axial direction of the laser cutting path, a series of sections perpendicular to the cutting path are selected on the heat-affected zone correction contour curve. Each section is based on the tube axial coordinate u j ' is the center of the local section coordinate system;

[0119] S552: In each local section coordinate system, obtain all intersection points of the modified contour curve and the corresponding slit center line, and measure the radial distances from these intersection points to the center line, set as r jk ′, where k represents the kth intersection point on the cross section;

[0120] S553: ​​For each section, calculate the maximum value of all radial distances to obtain the width W of the heat-affected zone on the section. j , the calculation formula is: W j =2·max k (|r jk ′|), where W j is the width of the heat-affected zone on the jth section; |r jk ′| is the absolute radial distance from the kth intersection point to the center line of the slit;

[0121] S554: The width of the heat-affected zone W on all cross sections j The heat-affected zone width distribution curve of the entire cutting path is generated by summarizing them in sequence. Through the above steps, based on the spatial relationship between the modified contour and the center line, the accurate quantitative calculation of the heat-affected zone width and the output of the full-path distribution can be achieved, providing a scientific basis for the control of the heat diffusion range and quality evaluation of the actual laser cutting process.

[0122] S6 specifically includes:

[0123] S61: Construct a multidimensional data structure including the deformation compensation coefficient C, the equivalent heat flux density distribution q(x, y, z, t), and the heat-affected zone width W(u), which correspond to the basic physical information of the geometric field, thermal field, and response field respectively;

[0124] S62: Input the multidimensional data structure into the digital twin modeling engine and establish the physical coupling mapping relationship between the model parameters through the three-field joint indexing mechanism, where:

[0125] The geometric field uses the deformation compensation coefficient C as input to control the axis diameter correction mapping of the pipe model;

[0126] The thermal field takes spatial coordinates (x, y, z) and time t as input and outputs equivalent heat flux density q;

[0127] The response field takes the axial coordinate u as input and outputs the width of the heat-affected zone W(u);

[0128] S63: By establishing the transfer function relationship between physical fields, a response prediction model driven by input variables C, q (x, y, z, t) and W (u) is formed. The functions are logically combined through the coupling kernel function to obtain a complete digital twin model of laser tube cutting equipment. The specific expression is:

[0129] M DT =F(C, q(x, y, z, t), W(u)), where, M DT represents the constructed digital twin model of laser tube cutting equipment; F( ) represents the transfer function library after integrating the three-field information, which is used to realize the simulation and prediction of processing response under input conditions; through the above steps, the coupling modeling among the three physical fields of deformation, heat input, and thermal response is realized, and a structured digital twin model expression is constructed in the form of a function, providing a unified and callable model framework for real-time response analysis, process optimization, and virtual simulation in the laser cutting process, significantly improving the engineering usability and prediction reliability of the digital twin system.

[0130] The present invention encompasses any alternatives, modifications, equivalents, and solutions that fall within the spirit and scope of the present invention. To provide a thorough understanding of the present invention, specific details are described in detail below in connection with the preferred embodiments of the present invention, but those skilled in the art will be able to fully understand the present invention without these detailed descriptions. Furthermore, to avoid unnecessary confusion regarding the essence of the present invention, well-known methods, processes, procedures, components, and circuits have not been described in detail.

[0131] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A digital twin modeling method for laser tube cutting equipment, characterized in that: The following steps are involved: S1: Obtaining the pipe clamping deformation parameters in real time through the multi-axis sensor array on the clamping mechanism, wherein the pipe clamping deformation parameters include the axial stress distribution gradient and the radial displacement deviation; S2: Perform reverse geometry reconstruction based on the pipe clamping deformation parameters to generate a pipe solid model including deformation compensation coefficients; S3: Real-time acquisition of the laser incident angle and the pipe surface reflectivity, and determination of the energy absorption parameters based on the dynamic relationship between the laser incident angle and the pipe surface reflectivity; S4: Input the tube solid model and energy absorption parameters into the thermal-mechanical coupling simulation module to calculate the equivalent heat flux density distribution on the laser cutting path; S5: Predict the width of the heat-affected zone in the cutting area based on the equivalent heat flux density distribution and deformation compensation coefficient; S6: Integrate the above deformation compensation coefficient, heat-affected zone width and equivalent heat flux density distribution to build a digital twin model of laser tube cutting equipment.

2. The digital twin modeling method for laser tube cutting equipment according to claim 1, characterized in that: Said S1 specifically includes: S11: Arrange a multi-axis sensor array in the circumferential and axial directions of the clamping mechanism, and establish a spatial coordinate system of the sensor array; S12: The axial strain signal of the pipe after clamping is collected in real time through the strain sensor in the sensor array and converted into the axial stress distribution gradient based on Hooke's law. The calculation formula of the axial stress distribution gradient is: Among them, σ z is the axial stress distribution gradient; E is the elastic modulus of the pipe material; ΔL is the axial strain of the pipe; L0 is the initial clamping length of the pipe; S13: The radial position change of the pipe is measured in real time by the displacement sensor in the sensor array to obtain the radial displacement deviation. The calculation formula of the radial displacement deviation is: δ r =r-r0, where δ r is the radial displacement deviation; r is the radial position of the pipe measured in real time; r0 is the initial radial position of the pipe.

3. The digital twin modeling method for laser tube cutting equipment according to claim 1, characterized in that: The S2 specifically includes: S21: Inputting the pipe clamping deformation parameters into the reverse reconstruction unit, and constructing the initial deformation point cloud data of the pipe based on the measured axial stress distribution gradient and radial displacement deviation; S22: Based on the initial deformed point cloud data, a point cloud surface reconstruction algorithm is used to perform surface fitting processing to generate a deformed surface model of the pipe; S23: Based on the deformable surface model of the pipe, the pipe solid model is constructed through the topological mapping relationship from the surface model to the solid model; S24: Based on the numerical characteristics of the axial stress distribution gradient, a linear regression algorithm is used to determine the corresponding deformation compensation coefficient, and the deformation compensation coefficient is assigned to the pipe solid model.

4. The digital twin modeling method for laser tube cutting equipment according to claim 1, characterized in that: The S24 specifically includes: S241: Based on the measured data of the axial stress distribution gradient and the corresponding actual deformation of the pipe, a linear regression data set is established, and the data set is preprocessed for standardization; S242: Using a linear regression algorithm, with minimizing the prediction error as the optimization goal, determine the fitting relationship between the axial stress distribution gradient and the deformation compensation coefficient. The specific optimization objective function is: Where J(θ) is the optimization objective function of the linear regression algorithm; m is the total number of data points in the data set; C i is the actual deformation compensation coefficient corresponding to the i-th data point; σ zi is the axial stress distribution gradient corresponding to the i-th data point; θ0, θ1 are the linear regression coefficients obtained by the algorithm; S243: Calculate the deformation compensation coefficient C in the current pipe clamping state based on the linear regression coefficients θ0 and θ1 obtained by solving; S244: The current deformation compensation coefficient calculated in S243 is embedded into the pipe solid model as an attribute parameter to complete the correction of the pipe solid model.

5. The digital twin modeling method for laser tube cutting equipment according to claim 1, characterized in that: The S3 specifically includes: S31: A laser three-dimensional posture sensor is set in the interaction area between the laser head and the pipe surface to collect the incident angle α of the laser beam relative to the cutting surface of the pipe in real time; S32: using a surface reflectivity monitoring module to obtain a unit area reflectivity ρ of the laser irradiated area of ​​the pipe; S33: Input the incident angle α and the surface reflectivity ρ into the absorption model calculation unit, and calculate the energy absorption parameter of the laser at the current incident angle based on the nonlinear relationship between the two. The formula is: η=1-ρ·cos n (α), where η is the laser energy absorption parameter and n is the fitting constant.

6. The digital twin modeling method for laser tube cutting equipment according to claim 1, characterized in that: The S4 specifically includes: S41: importing the pipe solid model including the deformation compensation coefficient generated in S2 into the thermal-mechanical coupling simulation module as the three-dimensional geometric input basis of the object to be analyzed; S42: mapping the energy absorption parameters calculated in S3 to the surface of the tube solid model according to the coordinates of each point on the laser scanning path, thereby forming the initial boundary conditions for the spatial distribution of the laser input heat source; S43: Set the thermophysical properties of the pipe material in the simulation module, including thermal conductivity, specific heat capacity, and density, and determine the heat source movement trajectory based on the time history of laser processing; S44: The finite element method is used to dynamically solve the heat transfer process of the heat source on the cutting path and calculate the instantaneous heat flux density distribution at any time t and spatial position. The formula is: Where q(x, y, z, t) is the equivalent heat flux density at the time t and position (x, y, z); η is the energy absorption parameter of the corresponding point; P is the total power of the laser beam; r b is the laser spot radius; (x0(t), y0(t)) is the center coordinate position of the laser heat source on the surface at time t.

7. The digital twin modeling method for laser tube cutting equipment according to claim 1, characterized in that: The S5 specifically includes: S51: extract the peak heat flux density sequence and the corresponding heat source residence time sequence of each microelement on the cutting path from the equivalent heat flux density distribution obtained in S4, and establish a heat input time history database; S52: Inputting the heat input time history database and the thermophysical property parameters of the pipe material into a transient heat conduction analysis module to calculate the three-dimensional temperature field distribution around the cutting path; S53: setting a critical metallurgical phase transformation temperature threshold of 650° C. in the three-dimensional temperature field, searching for an isothermal surface that meets the threshold, and determining an initial heat-affected zone contour; S54: performing axial and radial coordinate correction on the initial heat-affected zone profile according to the deformation compensation coefficient obtained in S2, and generating a corrected heat-affected zone profile curve; S55: performing cross-sectional analysis on the corrected heat-affected zone contour curve along the cutting path, calculating the maximum radial distance between the heat-affected zone contour curve and the slit centerline on each section, and outputting the heat-affected zone width of the cutting area.

8. The digital twin modeling method for laser tube cutting equipment according to claim 8, characterized in that: The S54 specifically includes: S541: Extract the original space coordinates of each boundary point in the initial heat-affected zone contour, set as (u j , r j ), where u j is the position coordinate of the jth point in the axial direction of the tube; r j is the radial distance of the point relative to the cutting center axis; S542: Obtain the deformation compensation coefficient C calculated in S2, and perform coordinate correction on the axial position of the contour point. The coordinate after axial correction is expressed as: u j ′=u j +C·Δu, where u j ′ is the coordinate after axial correction; Δu is the average length offset caused by axial strain in the clamped state; C is the deformation compensation coefficient; S543: At the same time, the radial position of the contour point is corrected. The coordinate after radial correction is expressed as: r j ′=r j +C·Δr, where r j ′ is the coordinate after radial correction; Δr is the average displacement deviation in the radial direction; S544: All corrected contour points are connected in order to construct a corrected contour curve of the heat-affected zone, and the corrected contour curve is superimposed and compared with the original contour to complete the thermal response adjustment under deformation compensation.

9. The digital twin modeling method for laser tube cutting equipment according to claim 9, characterized in that: The S55 specifically includes: S551: Along the axial direction of the laser cutting path, a series of sections perpendicular to the cutting path are selected on the heat-affected zone correction contour curve. Each section is based on the tube axial coordinate u j ' is the center of the local section coordinate system; S552: In each local section coordinate system, obtain all intersection points of the modified contour curve and the corresponding slit center line, and measure the radial distances from these intersection points to the center line, set as r jk ′, where k represents the kth intersection point on the cross section; S553: ​​For each section, calculate the maximum value of all radial distances to obtain the width W of the heat-affected zone on the section. j , the calculation formula is: W j =2·max k (|r jk ′|), where W j is the width of the heat-affected zone on the jth section; |r jk ′| is the absolute radial distance from the kth intersection point to the center line of the slit; S554: The width of the heat-affected zone W on all cross sections j The heat affected zone width distribution curve of the entire cutting path is generated by summarizing them one by one.

10. The digital twin modeling method for laser tube cutting equipment according to claim 1, characterized in that: The S6 specifically includes: S61: Construct a multidimensional data structure including the deformation compensation coefficient C, the equivalent heat flux density distribution q(x, y, z, t), and the heat-affected zone width W(u), which correspond to the basic physical information of the geometric field, thermal field, and response field respectively; S62: Input the multidimensional data structure into the digital twin modeling engine and establish the physical coupling mapping relationship between model parameters through the three-field joint indexing mechanism; S63: By establishing the transfer function relationship between physical fields, a response prediction model driven by input variables C, q (x, y, z, t) and W (u) is formed. The functions are logically combined through the coupling kernel function to obtain a complete digital twin model of laser tube cutting equipment. The specific expression is: M DT =F(C, q(x, t, z, t), W(u)), where, M DT represents the constructed digital twin model of laser tube cutting equipment; F() represents the transfer function library after integrating the three-field information, which is used to realize the simulation and prediction of processing response under input conditions.

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