Water guided laser processing system for sheet material

Abstract

The present application provides a kind of water guide laser processing system for sheet material, comprising: laser; light splitter; focusing mirror; water guide processing head; to be processed sheet, via water jet is carried out water guide laser cutting processing;Array multi-hole support sheet, from the bottom direction is attached to the bottom of the sheet to be processed, and forms an integrated support structure to the sheet to be processed;First clamp, from the upper surface of the sheet to be processed and the lower surface of array multi-hole support sheet clamps the sheet to be processed and array multi-hole support sheet;And drainage device is located in the position below array multi-hole support sheet.This patent realizes sheet deformation control and water flow control of water guide laser system by optimizing sheet support design, accurately controls the direction and intensity of water flow, reduces the interference of water flow to sheet, improves cooling effect and laser transmission mode, effectively suppresses the deformation and displacement of sheet material, improves processing precision, stability and surface quality, solves the problems of poor sheet processing precision, unstable surface and other problems in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water-guided laser processing, in particular to a water-guided laser processing system for sheet materials. BACKGROUND

[0002] When processing sheet materials by water-guided laser, the sheet materials are prone to displacement or deformation during processing due to the diffusion effect of water flow, resulting in a decrease in processing precision. In particular, during sheet processing, the sheet is subjected to unbalanced forces due to the uneven action of water flow, and then small movements or warping occur, affecting the stability of processing. The deformation caused by water flow not only leads to irregular cutting lines and size deviations in water-guided processing, but also causes thermal stress cracks on the processed surface.

[0003] The inventors have found through long-term testing and research that the main reason for the above problems is that the diffusion effect of water flow is not effectively controlled, and the processing system lacks the ability to dynamically adapt to sheet materials, and cannot accurately compensate for the deformation or displacement caused by water flow, thus failing to meet the demand for high-precision processing of sheet materials, resulting in poor precision, poor stability, and unstable surface quality in sheet processing.

[0004] In addition, deformation, warping, and other phenomena of sheet materials cause cutting deviation in water jet processing, resulting in large deviations in cutting position size and defects, and further causing problems of unstable precision and surface quality. SUMMARY

[0005] The present application aims to provide a water-guided laser processing system for sheet materials, which optimizes sheet support, controls water flow, avoids deformation, displacement, warping, and other defects caused by water flow, and improves processing precision and surface quality.

[0006] According to a first aspect of the present application, a water-guided laser processing system for sheet materials is provided, comprising:

[0007] a laser;

[0008] a beam splitter;

[0009] a focusing mirror;

[0010] a water-guided processing head for emitting a water jet for processing by coupling a light beam with a water beam;

[0011] a sheet to be processed located below the water-guided processing head, which is subjected to water-guided laser cutting processing by the water jet;

[0012] an array of multi-hole support sheets attached to the bottom of the sheet to be processed from the bottom direction, forming an integrated support structure for the sheet to be processed;

[0013] a first clamp for clamping the workpiece and the arrayed porous support sheet from the upper surface of the workpiece and the lower surface of the arrayed porous support sheet; and

[0014] a drainage device located below the arrayed porous support sheet.

[0015] In further embodiments, the arrayed porous support sheet has a circular or regular hexagonal hole pattern.

[0016] In further embodiments, the diameter of the holes is 1-5 mm.

[0017] In further embodiments, the arrayed porous support sheet is a sheet of a material that matches the thermal expansion coefficient of the workpiece.

[0018] In further embodiments, the first clamp uses a multi-point positioning method to clamp the workpiece and the arrayed porous support sheet.

[0019] In further embodiments, the water guide laser processing system is provided with a CCD camera for capturing images of the cutting area at a set sampling frequency.

[0020] In further embodiments, the sampling frequency of the CCD camera is set to take one frame of image for every 0.1 mm movement of the water guide processing head.

[0021] In further embodiments, the control system of the water guide laser processing system is connected to the CCD camera, and the deviation of the angle of the cut from the vertical direction is calculated based on the image processing of the processing area image, as the perpendicularity deviation of the cut.

[0022] In further embodiments, the control system establishes a water guide processing state space prediction model based on a water jet impact force model, a sheet thermal deformation model, and a laser energy absorption and transmission model, with laser power, water jet pressure, and cutting speed as input vectors, and the perpendicularity deviation of the cut as an output vector.

[0023] Based on the actual measurement of the process parameters at each time step and the perpendicularity deviation of the cut, the coefficient matrix in the state space model is determined by a parameter identification method.

[0024] The sum of the squares of the perpendicularity deviation of the cut in a future prediction time domain is set as the objective function, and the process parameter constraints are determined, and the optimization is solved to obtain the input control sequence that minimizes the objective function under the process parameter constraints, and the compensation amount of the water guide laser processing process parameters is obtained, thereby ensuring the perpendicularity of the processed cut.

[0025] In a further embodiment, the step of calculating the angular deviation between the cut and the vertical direction based on the image of the processing area includes:

[0026] The image of the processing area is preprocessed to remove noise and then converted into a grayscale image;

[0027] Edge detection is used to extract the edges of grayscale images, specifically the pixels representing the cut edge contours.

[0028] The shape and direction of the cut are determined by fitting straight lines to the pixels of the cut edge contour and calculating the slope and intercept of the fitted line.

[0029] The perpendicularity deviation of the cut is calculated based on the angle between the fitted straight line and the ideal perpendicular direction.

[0030] The significant advantages of the water-guided laser processing system for thin sheet materials of the present invention are as follows:

[0031] To address the defects in processing quality caused by deformation, warping, and movement of thin sheet materials during water-guided laser processing in existing technologies, this invention proposes a water-guided laser processing system for thin sheet materials. This system utilizes an array of perforated support plates at the bottom of the sheet to be processed, which adhere to the sheet from the bottom, forming an integrated support structure. This prevents deformation of the sheet due to the impact of the water jet during processing, reducing dimensional deviations, cracks, and thermal deformation caused by sheet deformation, thus ensuring processing accuracy. Furthermore, real-time image acquisition and processing of the cutting position using a CCD camera is employed to obtain the cut perpendicularity deviation. The compensation amount for the water-guided laser processing process parameters is then obtained through a water-guided processing state space prediction model, ensuring the perpendicularity of the processed cut. This adapts to changes in the actual cutting process, corrects deviations promptly, improves processing stability, and enhances processing accuracy.

[0032] It should be understood that all combinations of the foregoing concepts and the additional concepts described in more detail below may be considered part of the inventive subject matter of this disclosure, provided that such concepts do not contradict each other. Furthermore, all combinations of the claimed subject matter are considered part of the inventive subject matter of this disclosure.

[0033] The foregoing and other aspects, embodiments, and features of the teachings of the present invention will be more fully understood from the following description in conjunction with the accompanying drawings. Other additional aspects of the invention, such as features and / or beneficial effects of exemplary embodiments, will become apparent from the following description or may be learned through practice of specific embodiments according to the teachings of the present invention. Attached Figure Description

[0034] The drawings are not intended to be drawn to scale. In the drawings, each same or like component illustrated in the various drawings can be designated with the same reference numeral. In the interest of clarity, not every component of each drawing is called out. Embodiments of various aspects of the present application will now be described, by way of example, with reference to the drawings.

[0035] Figure 1 is a system schematic diagram of a water-guided laser processing system for sheet material according to an embodiment of the present application.

[0036] Figure 2 is a schematic diagram of an array of multi-hole support sheets for a water-guided laser processing system for sheet material according to an embodiment of the present application.

[0037] Figure 3 is a schematic diagram of a clamping method for a water-guided laser processing system for sheet material according to an embodiment of the present application.

[0038] Figure 4 is a flowchart of an algorithmic process for a state space model of a water-guided laser processing system for sheet material according to an embodiment of the present application.

[0039] Figure 5 and Figure 6 respectively show schematic diagrams of processing results of a water-guided laser processing system for sheet material according to the present application and a conventional processing method. DETAILED DESCRIPTION

[0040] In order to more fully understand the technical content of the present application, specific embodiments are described below with reference to the accompanying drawings.

[0041] Aspects of the present application are described in the disclosure by reference to the accompanying drawings, in which a number of illustrative embodiments are shown. The embodiments of the present disclosure are not necessarily intended to encompass all aspects of the present application. It will be apparent, however, that the various concepts and embodiments disclosed herein and described below in more detail can be embodied in a wide variety of forms, not just the ones explicitly disclosed. Additionally, some aspects of the present disclosure can be used separately or in any appropriate combination with other aspects of the present disclosure.

[0042] {Example 1}

[0043] In conjunction with Figures 1-3 The water-guided laser processing system for sheet material of the illustrated embodiment includes a laser 1, a beam splitter 2, a focusing lens 3, a water-guided processing head 4, a first clamp 6, a drainage device 50, and a control system.

[0044] In conjunction with Figure 1As shown, the water guide processing head 4 is coupled with the light beam and the water beam to emit the water jet 5 for processing. The sheet 10 to be processed is clamped by the first clamp 6 and positioned below the water guide processing head 4 for water guide laser cutting processing by the water jet 5.

[0045] As shown, the arrayed porous support sheet 20 is attached to the bottom of the sheet 10 to be processed from the bottom direction to form an integrated support structure for the sheet 10 to be processed. Figure 1 Figure 2 The first clamp 6 clamps the sheet 10 to be processed and the arrayed porous support sheet 20 from the upper surface of the sheet 10 to be processed and the lower surface of the arrayed porous support sheet 20.

[0046] Especially preferably, the first clamp 6 clamps the sheet 10 to be processed and the arrayed porous support sheet 20 in a multi-point positioning manner. As shown,

[0047] Especially preferably, the first clamp 6 clamps the sheet 10 to be processed and the arrayed porous support sheet 20 in a multi-point positioning manner. As shown, Figure 2 Figure 3 Especially preferably, the first clamp 6 clamps the sheet 10 to be processed and the arrayed porous support sheet 20 in a multi-point positioning manner. As shown,

[0048] As shown, the arrayed porous support sheet 20 is attached to the bottom of the sheet 10 to be processed from the bottom direction to form an integrated support structure for the sheet 10 to be processed. Figure 1 As shown, the arrayed porous support sheet 20 is attached to the bottom of the sheet 10 to be processed from the bottom direction to form an integrated support structure for the sheet 10 to be processed.

[0049] As shown, the arrayed porous support sheet 20 is attached to the bottom of the sheet 10 to be processed from the bottom direction to form an integrated support structure for the sheet 10 to be processed.

[0050] In an especially preferred embodiment, the arrayed porous support sheet 20 is a sheet supported by a material matching the thermal expansion coefficient of the sheet 10 to be processed, especially a support material with the same thermal expansion coefficient, such as aluminum alloy, stainless steel, ceramic material, composite fiber reinforced metal material (such as CFRP sheet), etc., which can be supported by a corresponding material with a similar or the same thermal expansion coefficient.

[0051]

[0052] ​​​Based on the above embodiments, the design of this invention solves the problem of thin plate displacement and deformation caused by water flow diffusion during water-guided laser processing of thin plate materials, which in turn affects processing accuracy and surface quality. Because existing technologies fail to effectively control water flow diffusion, the thin plate material experiences uneven stress during processing, resulting in displacement or warping, especially noticeable in high-precision processing. Furthermore, existing technologies lack sufficient control over thermal stress and deformation, and lack effective dynamic compensation mechanisms, leading to instability during processing. Therefore, this invention optimizes water flow control and improves thin plate deformation through thin plate support design. It can precisely control the direction and intensity of water flow, reduce the impact of water flow diffusion, and simultaneously improve cooling efficiency, preventing deformation caused by thermal stress. This solves the problems of poor processing accuracy, poor stability, and unstable surface quality in existing thin plate technologies.

[0053] {Example 2}

[0054] In this embodiment, combined with Figure 1 As shown, the water-guided laser processing system is equipped with a CCD camera 8, which is used to capture images of the cutting area at a set sampling frequency to obtain images of the processing area.

[0055] The sampling frequency of the CCD camera 8 is set to capture one frame of image every 0.1 mm that the water-guided processing head 4 moves.

[0056] The control system of the water-guided laser processing system is connected to the CCD camera 8. Based on the image of the processing area, the angle deviation between the cut and the vertical direction is calculated and used as the verticality deviation of the cut.

[0057] As an optional embodiment, the step of calculating the angle deviation between the cut and the vertical direction based on the image of the processing area includes:

[0058] The image of the processing area is preprocessed to remove noise and then converted into a grayscale image;

[0059] Edge detection is used to extract the edges of grayscale images, specifically the pixels representing the cut edge contours.

[0060] The shape and direction of the cut are determined by fitting straight lines to the pixels of the cut edge contour and calculating the slope and intercept of the fitted line.

[0061] The perpendicularity deviation of the cut is calculated based on the angle between the fitted straight line and the ideal perpendicular direction.

[0062] In this embodiment, a high-resolution CCD camera captures images of the cut area at a set sampling frequency (e.g., one frame is captured for every 0.1mm movement) to obtain digital image signals.

[0063] The captured digital images are transmitted to the image processing module in the control system via a high-speed communication interface. Image preprocessing can employ existing denoising algorithms for image denoising followed by grayscale conversion. Denoising can be achieved using methods such as median filtering to remove interference factors such as salt-and-pepper noise and Gaussian noise from the image.

[0064] Then, the color image is converted to a grayscale image through grayscale processing, which reduces the amount of data and highlights the edge information of the image, preparing for subsequent edge detection and shape analysis.

[0065] Furthermore, the Canny edge detection algorithm is used to process the preprocessed grayscale image. First, Gaussian filtering is applied to smooth the image to reduce the impact of noise on edge detection. Then, the gradient magnitude and direction of the image are calculated. Pixels at the cut edges are extracted through non-maximum suppression and double threshold detection.

[0066] For example, the kernel size of the Gaussian filter can be selected according to the image noise level; in this example, 3*3 pixels is selected. The high and low threshold settings of the dual threshold are adjusted according to the image contrast and edge strength. The low threshold can be set between 20-50 gray values, and the high threshold can be set between 50-100 gray values ​​to ensure that the cut edge can be detected accurately, while reducing false detections and false negatives.

[0067] After extracting the edge pixels of the cut, a least squares method is used to fit a straight line to the edge points. By calculating the slope and intercept of the fitted line, the approximate shape and direction of the cut are determined. Then, based on the angle between the fitted line and the ideal vertical direction (such as the y-axis of the image coordinate system), the perpendicularity deviation of the cut is calculated. For example, for a fitted line y = fx + b, its slope f reflects the degree of inclination of the line. By calculating arctan(f), the angle between the line and the x-axis is obtained, and then the angle deviation with the vertical direction is calculated, which is the perpendicularity deviation of the cut.

[0068] As an optional embodiment, the control system establishes a water-guided processing state-space prediction model based on the water jet impact force model, the thin plate thermal deformation model, and the laser energy absorption and transfer model, with laser power, water jet pressure, and cutting speed as input vectors and the perpendicularity deviation of the cut as the output vector.

[0069] Based on the process parameters obtained at each time step by actual measurement and the perpendicularity deviation of the cut, the coefficient matrix in the state space model is determined by parameter identification method.

[0070] The objective function is set as minimizing the sum of squares of the perpendicularity deviation of the cut within a future prediction time domain, and the process parameter constraints are determined. The optimization solution is then obtained to obtain the input control sequence that minimizes the objective function under the process parameter constraints. The compensation amount of the water-guided laser processing process parameters is obtained, thereby ensuring the perpendicularity of the processed cut.

[0071] Combination Figure 4 As shown, in this embodiment, a state-space model for water-guided laser cutting is constructed by combining the thermal deformation model of the thin plate, the water jet impact force model, the laser energy absorption and transfer model, and the motion model of the water-guided processing head, comprehensively considering their mutual influence on the cut perpendicularity. An optimization problem is solved to calculate the compensation amount of the process parameters required to maintain the cut perpendicularity within the target range over a future time step (e.g., the next 10-100ms). The objective function of the optimization problem is chosen to minimize the cut perpendicularity deviation, and the constraints include the value range of process parameters such as laser power, water jet pressure, and cutting speed, as well as the motion limitations of the water-guided processing head.

[0072] The construction of a thin plate thermal deformation model as an example includes the following steps:

[0073] Based on Fourier's law of heat conduction, the heat conduction equation for thin sheet materials is obtained as follows:

[0074]

[0075] Where ρ represents the density of the thin plate material, c represents the specific heat capacity, T represents the temperature field, t represents time, k represents the thermal conductivity, and q represents the heat source term, i.e., the laser energy input;

[0076] In the case of a two-dimensional thin plate (assuming uniform temperature along the thickness direction of the plate), the heat conduction equation can be further equivalently represented as:

[0077]

[0078] The equation is solved by discretization using the finite difference method or the finite element method, and the temperature distribution T(x, y, t) of the thin plate at different locations and times is obtained.

[0079] Furthermore, based on the coefficient of thermal expansion α of the thin plate material, the relationship between the thermal deformation ΔL and the temperature change ΔT is obtained as follows:

[0080] ΔL=αLΔT;

[0081] Where L is the original length before deformation;

[0082] For any point (x, y) on the thin plate, the thermal deformation in the x and y directions is expressed as follows:

[0083] Δx=αxΔT(x, y, t), Δy=αyΔT(x, y, t);

[0084] This allows us to obtain the shape changes of the thin plate caused by thermal deformation.

[0085] As an example of water jet impact force construction, the steps include:

[0086] The momentum equation for the water jet is established as follows:

[0087]

[0088] Where, ρ w This indicates the density of water. The vector represents the water jet velocity, p represents pressure, and μ represents the velocity vector. w The dynamic viscosity of water is represented by the momentum equation; by solving the momentum equation, the velocity and pressure distribution of the water jet at different locations can be obtained.

[0089] When a water jet impacts a thin sheet material, according to the momentum theorem, the impact force is expressed as:

[0090]

[0091] Where A is the contact area between the water jet and the thin plate. It is the normal vector of the thin plate surface.

[0092] Furthermore, the impact force of the water jet at different positions on the thin plate surface is integrated to obtain the total water jet impact force and its torque, thereby analyzing its influence on the deformation of the thin plate and the perpendicularity of the cut.

[0093] The construction of an example laser energy absorption and transfer model includes the following steps:

[0094] Regarding the absorption of laser energy by thin sheet materials, according to Beer-Lambert's law, the intensity of the laser within the thin sheet is expressed as:

[0095]

[0096] Where I0 is the incident laser intensity, α m is the absorption coefficient of the thin plate material to the laser, and z is the coordinate along the thickness direction of the thin plate. The energy Q absorbed by the laser along the thickness direction of the thin plate is calculated by integration:

[0097]

[0098] Where d is the thickness of the sheet;

[0099] The absorbed laser energy is partly used to melt and vaporize the material, and partly transferred within the thin plate through heat conduction; based on the latent heat of fusion L of the thin plate material... m and latent heat of vaporization L υ The energy required to melt and vaporize the material is calculated, and the remaining energy causes the temperature of the thin plate to rise, further affecting the thermal deformation.

[0100] The construction of a motion model for a water-guided machining head, as an example, includes the following steps:

[0101] Based on Newton's second law, the equations of motion for the water-guided machining head motion platform are constructed as follows:

[0102]

[0103] Where m is the mass of the machining head motion platform and load. It is the displacement vector of the worktable, F m It is the platform motor driving force, It is friction. It is the cutting force, that is, the impact force of the water jet.

[0104] Furthermore, by solving the equations, the motion trajectory, velocity, and acceleration of the worktable are obtained.

[0105] Combination Figure 4 As shown, based on the established model, the key variables in the above model are combined into a state vector:

[0106]

[0107] This includes variables related to the temperature field of the thin plate, the water jet impact force, the stage displacement, and the water jet velocity. The input vector includes the laser power P and the water jet pressure p. w Cutting speed υ c Process parameters, output vector This indicates the perpendicularity deviation of the cut.

[0108] Therefore, a state-space model is established:

[0109]

[0110] Where A, B, and C are coefficient matrices, and These are the process noise and measurement noise vectors, respectively, and k represents the time step index.

[0111] By systematically identifying the coefficient matrix of the established multi-factor correlation model, the coefficient matrices A, B, and C in the state-space model can be determined using experimental data and the least squares parameter identification method. For example, under different combinations of laser power, water jet pressure, and cutting speed, the temperature change of the thin plate, the water jet impact force, the table movement, and the perpendicularity deviation of the cut can be measured. Then, model parameters can be fitted based on these data, enabling the model to accurately describe the actual cutting process.

[0112] Set the prediction time domain N p and control time domain N u The prediction time domain refers to the number of time steps in which the algorithm predicts the future behavior of the system; for example, setting N... p =10, meaning the system state is predicted for the next 10 time steps. The control time domain refers to the number of time steps in which future control input changes are determined at the current moment, such as N. u =5 indicates a strategy for determining the changes in control inputs such as laser power and water jet pressure over the next 5 time steps.

[0113] Furthermore, by solving the optimization problem, the optimal control input sequence is obtained, and the compensation amount of the process parameters is determined.

[0114] As an optional embodiment, the objective function is set to minimize the sum of squares of the verticality deviation of the cut over a future period (prediction time domain), i.e.:

[0115]

[0116] in, For reference cut perpendicularity (usually set to 0), Q k This is a weight matrix used to adjust the weights of deviations at different time steps. The closer to the current time step, the greater the weight, so as to pay more attention to the correction of recent deviations.

[0117] To control the magnitude of input variation, a penalty term is also included.

[0118]

[0119] Among them, R k The weight matrix is ​​used to control changes in the input and prevent drastic fluctuations in the control input.

[0120] Further determine the constraints on process parameters, including constraints on laser power, water jet pressure, and cutting speed.

[0121] For example, laser power P min ≤P≤P max ;

[0122] Water jet pressure p w，min ≤p w ≤pw,max ;

[0123] Cutting speed υ c,min ≤υ c ≤υ c，max .

[0124] Platform motion constraints: including the platform's maximum acceleration a max Maximum speed υ max wait, υ c，k ≤υ max .

[0125] Then, optimization algorithms such as Quadratic Programming (QP) or interior-point methods are used to solve the above optimization problem. Under the constraints, the control input sequence that minimizes the objective function is sought. in This refers to the compensation amount for process parameters such as laser power, water jet pressure, and cutting speed that need to be adjusted at the current moment.

[0126] For example, when using the interior-point method, the optimization problem is first transformed into a standard form. Then, a series of linear equations and linear programming problems are solved iteratively to gradually approach the optimal solution. In each iteration, the position of the current solution is used to determine whether it is within the feasible region. If it is on the boundary, special handling is used to maintain the feasibility of the iteration until the convergence condition is met, and the optimal control input sequence is obtained.

[0127] As an optional embodiment, the parameters of the prediction model can be further corrected periodically based on the differences between the measurement data and the actual cutting process, so as to achieve feedback and model correction.

[0128] As an optional embodiment, at each time step, the state vector in the prediction model is corrected using the measured values ​​of the actual cut perpendicularity deviation and other relevant state variables obtained by means of a laser interferometer and a machine vision system.

[0129] State estimation methods such as Kalman filtering can be used to update the state vector based on the difference between the measured and predicted values.

[0130]

[0131] in, The predicted state vector based on the previous time step: K is the predicted output vector based on the previous time step. k This is the Kalman gain matrix.

[0132] The Kalman gain matrix is ​​obtained by solving the Riccati equation, which is determined based on the covariance matrix of the system noise and the measurement noise, thus minimizing the mean square error of the state estimation.

[0133] Based on the discrepancies between measured data and the actual cutting process, the parameters of the prediction model can be periodically revised. For example, if a significant deviation is found between the actual cut perpendicularity and the model's prediction, potential error sources in the model should be examined, such as the accuracy of the thermal conductivity parameter in the heat deformation model or the reasonableness of the water jet velocity distribution assumptions in the water jet impact model. These parameters can be adjusted through experimental data or simulation analysis to better adapt the model to changes in the actual cutting process. For instance, if the thermal conductivity parameter is found to be inaccurate, thermal conductivity can be re-measured by conducting heat conduction experiments on the thin plate material at different temperatures, and the thermal conductivity parameter in the heat deformation model can be updated to improve the accuracy of the model's predictions.

[0134] {Example 3}

[0135] Combination Figure 5 , Figure 6 As shown, according to the aforementioned embodiment 1 of the present invention, a water-guided laser processing system with optimized support for thin plate materials is designed. By optimizing the thin plate support design, the deformation control of the thin plate and the water flow control of the water-guided laser system are realized. The direction and intensity of the water flow are precisely controlled, the interference of the water flow on the thin plate is reduced, the cooling effect and laser transmission mode are improved, and the deformation and displacement of the thin plate material are effectively suppressed. This solves the problems of poor processing accuracy and surface instability of thin plates in the prior art.

[0136] exist Figure 6 The processing results show that the cut edges are not smooth, and there are burrs and gaps. (Comparison) Figure 5 As shown, the cut edges processed by the design proposed in this invention have a smooth transition and are free from defects such as chipping, burrs, cracks, and gaps. It can be seen that the water-guided laser processing system for thin plate materials designed by this invention can significantly improve processing accuracy, stability, and surface quality.

[0137] While the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the invention. Those skilled in the art can make various modifications and refinements without departing from the spirit and scope of the invention. Therefore, the scope of protection of the present invention shall be determined by the claims.

Claims

1. A water-guided laser processing system for thin sheet materials, characterized in that, include: Laser (1); Beam splitter (2); Focusing lens (3); A water-guided machining head (4) is used to eject a water jet for machining by coupling a beam with a water jet (5). The thin plate (10) to be processed, located below the water-guided processing head (4), is subjected to water-guided laser cutting via the water jet (5); An array of porous support plates (20) are attached to the bottom of the plate to be processed (10) from the bottom direction to form an integral support structure for the plate to be processed (10); The first clamp (6) clamps the thin plate (10) to be processed and the arrayed porous support plate (20) from the upper surface of the thin plate (10) to be processed and the lower surface of the arrayed porous support plate (20); as well as A drainage device (50) located below the array of porous support plates (20); The water-guided laser processing system is equipped with a CCD camera (8) for capturing images of the cutting area at a set sampling frequency to obtain images of the processing area. The control system of the water-guided laser processing system is connected to the CCD camera (8). Based on the image of the processing area, the angle deviation between the cut and the vertical direction is calculated and used as the verticality deviation of the cut. The control system establishes a state-space prediction model for water-guided processing based on the water jet impact force model, the thin plate thermal deformation model, and the laser energy absorption and transfer model. The laser power, water jet pressure, and cutting speed are used as input vectors, and the perpendicularity deviation of the cut is used as the output vector. Based on the process parameters obtained at each time step by actual measurement and the perpendicularity deviation of the cut, the coefficient matrix in the state space model is determined by parameter identification method. The objective function is set as minimizing the sum of squares of the perpendicularity deviation of the cut within a future prediction time domain, and the process parameter constraints are determined. The optimization solution is then obtained to obtain the input control sequence that minimizes the objective function under the process parameter constraints. The compensation amount of the water-guided laser processing process parameters is obtained, thereby ensuring the perpendicularity of the processed cut.

2. The water-guided laser processing system for thin sheet materials according to claim 1, characterized in that, The perforated array support plate (20) has circular or regular hexagonal perforations.

3. The water-guided laser processing system for thin sheet materials according to claim 2, characterized in that, Its features are, The diameter of the hole is set to 1-5 mm.

4. The water-guided laser processing system for thin sheet materials according to claim 1, characterized in that, The array of porous support plates (20) is a thin plate supported by a material whose coefficient of thermal expansion matches that of the thin plate (10) to be processed.

5. The water-guided laser processing system for thin sheet materials according to claim 4, characterized in that, The first fixture (6) uses a multi-point positioning method to clamp the thin plate (10) to be processed and the array of perforated support thin plate (20).

6. The water-guided laser processing system for thin sheet materials according to any one of claims 1-5, characterized in that, The sampling frequency of the CCD camera (8) is set to capture one frame of image every 0.1 mm that the water-guided processing head (4) moves.

7. The water-guided laser processing system for thin sheet materials according to claim 1, characterized in that, The step of calculating the angle deviation between the cut and the vertical direction based on the image of the processing area includes: The image of the processing area is preprocessed to remove noise and then converted into a grayscale image; Edge detection is used to extract the edges of grayscale images, specifically the pixels representing the cut edge contours. The shape and direction of the cut are determined by fitting straight lines to the pixels of the cut edge contour and calculating the slope and intercept of the fitted line. The perpendicularity deviation of the cut is calculated based on the angle between the fitted straight line and the ideal perpendicular direction.

Images