Light spot quality simulation optimization method based on acousto-optic deflector and galvanometer cooperative system
By constructing a dynamic spot intensity matrix and introducing a synchronization error model, the problem of quantifying and assessing the spot distortion in the acousto-optic deflector and galvanometer co-operation system was solved, achieving accurate quantification and risk reduction of spot distortion and improving system performance.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 光芯精密科技(无锡)有限公司
- Filing Date
- 2025-12-26
- Publication Date
- 2026-04-10
AI Technical Summary
In existing acousto-optic deflector and galvanometer co-operation systems, there is a lack of theoretical framework for spot distortion, the evaluation methods are incomplete, the distortion risk cannot be quantified, and the optimization scheme is difficult to adapt to dynamic working conditions under high-speed motion, resulting in spot distortion affecting system performance.
By constructing a dynamic spot intensity matrix and combining it with static spot morphology, a high-speed motion state is simulated. A kinematic delay and synchronization error model is introduced, and the distortion rate is accurately quantified by using the control variable method and the hierarchical analysis method. The synchronization error threshold is dynamically adjusted to reduce the risk of distortion.
It achieves precise quantification and scientific risk assessment of spot distortion, provides strategies to reduce the risk of systemic distortion, supports parameter optimization of high-speed scanning systems, and improves system performance.
Smart Images
Figure CN121835154A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of light spot quality simulation and optimization technology, and in particular relates to a light spot quality simulation and optimization method based on an acousto-optic deflector and galvanometer collaborative system. Background Technology
[0002] In high-end applications such as ultra-precision laser micromachining, high-speed flow cytometry, and long-range lidar scanning, the acousto-optic deflector (AOD) and galvanometer co-operated system has become the core execution unit of high-speed precision optical systems due to its nanosecond-level deflection response and large scanning field of view. The dynamic quality of the light spot in high-speed motion directly determines the core performance indicators such as processing resolution, detection sensitivity, and signal transmission signal-to-noise ratio.
[0003] As application scenarios continue to demand higher scanning speeds (such as 100kHz-level galvanometer scanning and MHz-level AOD diffraction switching) and higher positioning accuracy (such as nanometer-level repeatability positioning errors), the problem of dynamic beam distortion caused by high-speed motion is becoming increasingly prominent. Its essence is the strong coupling effect between optical propagation characteristics and kinematic properties. Specifically, the inertial delay of galvanometer rotation leads to dynamic deviation of the beam incident angle, and the nonlinear response of AOD diffraction angle and driving frequency causes beam pointing deviation. Moreover, the time-varying characteristics of the synchronization error between the two further aggravate beam stretching, trailing, and energy center of gravity shift. These complex distortion mechanisms have become the core technical bottleneck restricting the breakthrough of system performance.
[0004] Existing technologies have multiple deep-seated flaws in addressing this technological bottleneck: First, the theoretical system of distortion transformation is incomplete. Existing distortion transformation methods mostly focus on static indicators such as spot energy concentration and full width at half maximum (FWHM), lack morphological comparative analysis of dynamic and static spots, have not established an accurate distortion rate calculation model based on time step, and have not considered the morphological optimization and coordinate calibration of spot boundaries, resulting in insufficient reliability and repeatability of distortion transformation results. Secondly, the quantification of risk assessment is insufficient. Existing assessments mostly rely on empirical judgment of a single distortion threshold and have not constructed a multi-dimensional assessment system that covers distortion distribution density and distortion severity, making it impossible to quantify the impact weight of distortion risk on the core performance of the system. Third, the underlying logic of parameter optimization is missing. Existing optimization methods mostly use trial and error or static parameter adjustment, without revealing the intrinsic relationship between key variables such as synchronization error and distortion rate through the control variable method. There is a lack of critical parameter solution mechanism based on data fitting and numerical iteration, which makes it difficult for optimization schemes to adapt to dynamic working conditions under high-speed motion and unable to suppress spot distortion from the root.
[0005] Therefore, this invention provides a method for simulating and optimizing the spot quality based on a co-system of acousto-optic deflector and galvanometer. Summary of the Invention
[0006] To address the shortcomings of existing technologies, this invention provides a method for simulating and optimizing the spot quality based on an acousto-optic deflector and galvanometer collaborative system, thereby solving the aforementioned technical problems in existing technologies.
[0007] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows: A method for simulating and optimizing spot quality based on an acousto-optic deflector and galvanometer co-system, comprising: In the simulation, the light field distribution under high-speed motion is simulated, the dynamic light spot morphology is acquired in real time, the dynamic light spot intensity matrix is constructed, and the light spot distortion rate corresponding to the time step under high-speed motion is determined by combining the static light spot morphology. Based on the spot distortion rate corresponding to the time step under high-speed motion, and by performing deviation analysis, the distortion risk of the spot under high-speed motion is assessed. If the risk of distortion is high, the control variable method is used to simulate and test the synchronization error value between the acousto-optic deflector and the galvanometer under high-speed motion, create a data table of synchronization error threshold spot distortion rate, and analyze the relationship between synchronization error value and spot distortion rate under high-speed motion. Based on the relationship between synchronization error and beam distortion rate under high-speed motion, a critical synchronization error value for reducing distortion risk under high-speed motion is determined. When the motion state changes to high-speed motion, the synchronization error threshold is dynamically adjusted to reduce the distortion risk under high-speed motion. In a further technical solution of the present invention, the process of constructing the dynamic spot intensity matrix is as follows: A two-dimensional rectangular coordinate system is established with the preset focal point of the processing plane as the origin. The horizontal axis is parallel to the horizontal rotation direction of the galvanometer, and the vertical axis is parallel to the vertical rotation direction of the galvanometer. A co-simulation platform is built based on OpticStudio optical simulation and MATLAB motion control simulation. The high-speed scanning trajectory and high-speed scanning speed are set. The dynamic spot intensity is calculated by using the ray tracing method combined with the finite difference time domain algorithm. The time step and total simulation time are set. The sampling point density of the spot area of the processing plane is fixed. The co-simulation is started. The AOD outputs the diffracted beam at the set frequency, and the galvanometer rotates at the appropriate angular velocity. The simulation model introduces the kinematic delay model to simulate the inertial delay of the galvanometer and the synchronization error model to simulate the deviation of the trigger signal. The dynamic spot intensity matrix of the processing plane is recorded at the set time step.
[0008] In a further technical solution of the present invention, the process for determining the spot distortion rate corresponding to the time step under high-speed motion is as follows: Keeping all optical and component parameters unchanged, only turning off the motion drive of AOD and galvanometer, the static spot intensity matrix of the processing plane is recorded; The dynamic and static major axis lengths are determined by processing and analyzing all pixel values in the dynamic and static light spot intensity matrices. The difference between the dynamic major axis length and the static major axis length is taken as the absolute value, and then the ratio is calculated with the static major axis length to obtain the spot distortion rate corresponding to the time step under high-speed motion.
[0009] In a further technical solution of the present invention, the process for determining the dynamic major axis length and the static major axis length is as follows: Normalize all pixel values in the dynamic and static spot intensity matrices, remove noise points, perform coordinate calibration, set a segmentation threshold, retain pixels in the dynamic and static spot matrices that are greater than or equal to the distribution threshold, and determine the effective spot area. Morphological optimization is performed on the effective spot area to extract the boundary pixel set of the effective spot area. Using the minimum bounding rectangle method, the boundary pixel set of the effective spot area is input, and based on the rotation calibration algorithm, all rectangle rotation angles are traversed. The area of the rectangle enclosing the point set under each rectangle rotation angle is calculated, and the rectangle with the smallest area is selected. The lengths of the two adjacent sides of the rectangle with the smallest area are recorded. The longest of the two adjacent sides of the rectangle with the smallest effective spot area corresponding to the dynamic spot matrix is recorded as the dynamic major axis length, and the longest of the two adjacent sides of the rectangle with the smallest effective spot area corresponding to the static spot matrix is recorded as the static major axis length.
[0010] In a further technical solution of the present invention, the process of assessing the distortion risk of the light spot under high-speed motion is as follows: Based on the spot distortion rate corresponding to the time step under high-speed motion, and by performing deviation analysis, the proportion of the number of distortion steps and the ratio of spot distortion degree are determined. The Analytic Hierarchy Process (AHP) was used to set the proportion of distortion step lengths and the weight of the degree of spot distortion. The proportion of distortion step lengths and the degree of spot distortion were weighted and summed to obtain the distortion risk value. If the distortion risk value is greater than or equal to the distortion risk threshold, it indicates that the distortion risk of the light spot is high under high-speed motion; otherwise, it indicates that the distortion risk of the light spot is low under high-speed motion.
[0011] In a further technical solution of the present invention, the process for determining the proportion of the distortion step size is as follows: If the spot distortion rate corresponding to the time step is greater than the standard value of the spot distortion rate, then the corresponding time step is the distortion step. The percentage of distortion step sizes within the total simulation duration is calculated.
[0012] In a further technical solution of the present invention, the process for determining the spot distortion ratio is as follows: The difference between the spot distortion rate corresponding to the distortion step size and the standard value of the spot distortion rate is calculated to obtain the distortion rate deviation corresponding to the distortion step size. The average value of the distortion rate deviations corresponding to all distortion step sizes is summed and then compared with the standard value of the spot distortion rate to obtain the spot distortion degree ratio.
[0013] In a further technical solution of the present invention, the process of analyzing the relationship between the synchronization error value and the spot distortion rate under high-speed motion is as follows: In the co-simulation platform, all operating parameters of the high-speed motion state are first set and kept unchanged, and only the synchronization error is used as the only variable. Set the gradient scanning range and scanning step size for the synchronization error. Each scanning step size corresponds to a synchronization error value. Perform simulation based on any synchronization error value, record the spot distortion rate corresponding to the time step, and sort them to determine the spot distortion rate of the synchronization error value. The spot distortion rate of all synchronization error values is entered into a data table. The data in the data table is imported into MATLAB. A scatter plot of synchronization error versus maximum distortion rate is plotted, and linear fitting is performed to obtain the fitting formula. Based on the data in the data table and the predicted values of the fitting formula, the goodness of fit is calculated. If the goodness of fit is greater than or equal to the goodness of fit threshold, it indicates that the synchronization error value and the spot distortion rate change linearly under high-speed motion. Otherwise, it indicates that the synchronization error value and the spot distortion rate change non-linearly under high-speed motion.
[0014] In a further technical solution of the present invention, the process for determining the spot distortion rate of the synchronization error value is as follows: Sort the spot distortion rates corresponding to all time steps in descending order to obtain a spot distortion rate sequence. Extract the spot distortion rate with the first order from the spot distortion rate sequence as the spot distortion rate of the synchronization error value.
[0015] In a further technical solution of the present invention, the process for determining the critical synchronization error value is as follows: Based on the linear relationship between the synchronization error value and the beam distortion rate under high-speed motion, the standard value of the beam distortion rate is substituted into the fitting formula to obtain the critical synchronization error value. Based on the fact that the synchronization error value and the spot distortion rate change nonlinearly under high-speed motion, the critical synchronization error value is determined by numerical iteration using the fzero function in MATLAB.
[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention establishes a platform that closely matches real-world scenarios through joint simulation using OpticStudio and MATLAB. It introduces kinematic delay and synchronization error models to recreate the actual spot distortion phenomenon and accurately quantifies the spot distortion rate at each time step based on the minimum bounding rectangle method. Furthermore, it constructs a distortion risk assessment system by combining the distortion step length ratio and distortion degree ratio with the weighted analytic hierarchy process (AHP). This achieves accurate quantification and scientific risk assessment of spot distortion under high-speed motion conditions. It provides data support for identifying key time nodes of spot distortion and provides a clear decision-making basis for subsequent optimization of high-speed scanning system parameters and reduction of distortion risk, balancing the realism of simulation, the accuracy of calculation, and the comprehensiveness of assessment. 2. This invention targets high-distortion-risk scenarios and focuses on synchronization error as a key influencing factor using the controlled variable method. By employing gradient scanning and data fitting, it clarifies the relationship between synchronization error and distortion rate, thereby accurately solving for the critical synchronization error value and dynamically adjusting the threshold. Throughout the process, it balances simulation realism, data accuracy, and scheme operability. This not only achieves accurate quantification and risk prediction of spot distortion but also provides a scientific basis for optimizing the synchronization parameters of high-speed scanning systems, effectively supporting the systematic management and reduction of spot distortion risk under high-speed motion conditions. Attached Figure Description
[0017] Figure 1 This is a flowchart of the steps of the light spot quality simulation and optimization method based on the acousto-optic deflector and galvanometer cooperative system in an embodiment of the present invention; Figure 2 This is a system block diagram of the light spot quality simulation and optimization system based on the acousto-optic deflector and galvanometer collaborative system according to an embodiment of the present invention. Detailed Implementation
[0018] The technical solution of the present invention will be further described in a non-limiting manner below with reference to the accompanying drawings and specific embodiments.
[0019] Example 1 like Figure 1 As shown in the figure, an embodiment of the present invention provides a method for simulating and optimizing the spot quality based on an acousto-optic deflector and galvanometer collaborative system, which includes the following steps: Step 1: Simulate the light field distribution under high-speed motion in the simulation, obtain the dynamic spot shape in real time, construct the dynamic spot intensity matrix, and combine it with the static spot shape to determine the spot distortion rate corresponding to the time step under high-speed motion. A two-dimensional rectangular coordinate system is established with the preset focal point of the processing plane as the origin. The horizontal axis (X-axis) is parallel to the horizontal rotation direction of the galvanometer, and the vertical axis (Y-axis) is parallel to the vertical rotation direction of the galvanometer (or the diffraction scanning direction of the AOD, which must be consistent with the system's motion direction). Based on optical simulation OpticStudio, a co-simulation platform is built by combining motion control simulation MATLAB. The high-speed scanning trajectory and high-speed scanning speed are set to match the actual application scenario. The dynamic spot intensity is calculated by using the ray tracing method combined with the finite difference time domain algorithm. The time step and total simulation time are set. The sampling point density of the spot area of the processing plane is fixed to ensure that the morphological details are not lost. The co-simulation is started. The AOD outputs the diffracted beam at the set frequency, and the galvanometer rotates at the appropriate angular velocity. The simulation model introduces the kinematic delay model that simulates the inertial delay of the galvanometer and the synchronization error model that simulates the deviation of the trigger signal. The dynamic spot intensity matrix of the processing plane is recorded at the set time step, and each time step corresponds to one dynamic spot shape. It should be noted that in high-speed motion, the incident angle of the beam changes dynamically with the rotation of the galvanometer, and the AOD diffraction angle is adjusted in real time with the frequency. The simulation model restores dynamic distortion phenomena such as beam stretching, trailing, and energy shift by coupling the optical propagation equation and the kinematic equation. Keeping all optical and component parameters unchanged, only turning off the motion drive of AOD and galvanometer, the static spot intensity matrix of the processing plane is recorded as a reference for comparison of dynamic spot morphology; It should be noted that both the dynamic spot intensity matrix and the static spot intensity matrix are pixel matrices. Each pixel value in the dynamic spot intensity matrix corresponds to the dynamic spot intensity, and each pixel value in the static spot intensity matrix corresponds to the static spot intensity. The horizontal axis elements in both the dynamic spot intensity matrix and the static spot intensity matrix are the physical coordinates of the X direction of the processing plane, and the vertical axis elements are the physical coordinates of the Y direction of the processing plane. Normalize all pixel values in the dynamic and static spot intensity matrices, remove noise points, perform coordinate calibration, set a segmentation threshold, retain pixels in the dynamic and static spot matrices that are greater than or equal to the distribution threshold, and determine the effective spot area. Morphological optimization of the effective spot area is performed. Morphological optimization includes traversing the binarized image, removing edge burrs through erosion processing, traversing the image using the same structuring element, restoring the original size of the main body outline of the spot through dilation processing, and using MATLAB's bwboundaries function and Zemax's light field contour analysis module to extract the boundary pixel set of the effective spot area. Using the minimum bounding rectangle method, the set of boundary pixels of the effective spot area is input. Based on the rotation calibration algorithm, all rectangle rotation angles (0°-180°) are traversed, and the area of the rectangle enclosing the point set under each rectangle rotation angle is calculated. The rectangle with the smallest area is selected, and the lengths of the two adjacent sides of the rectangle with the smallest area are recorded. The longest of the two adjacent sides of the rectangle with the smallest effective spot area corresponding to the dynamic spot matrix is recorded as the dynamic major axis length, and the longest of the two adjacent sides of the rectangle with the smallest effective spot area corresponding to the static spot matrix is recorded as the static major axis length. The difference between the dynamic major axis length and the static major axis length is taken as the absolute value, and then the ratio is calculated with the static major axis length to obtain the spot distortion rate corresponding to the time step under high-speed motion.
[0020] Step 2: Based on the spot distortion rate corresponding to the time step under high-speed motion, perform deviation analysis to assess the distortion risk of the spot under high-speed motion. The standard value of the spot distortion rate is set by those skilled in the art based on historical experience. If the spot distortion rate corresponding to the time step is greater than the standard value of the spot distortion rate, the corresponding time step is recorded as the distortion step. If the spot distortion rate corresponding to the time step is less than or equal to the standard value of the spot distortion rate, then the corresponding time step is recorded as the normal step. The percentage of distortion step lengths within the total simulation time is calculated. The difference between the spot distortion rate corresponding to the distortion step length and the standard value of the spot distortion rate is calculated to obtain the distortion rate deviation corresponding to the distortion step length. The distortion rate deviations corresponding to all distortion step lengths are summed and averaged, and then the ratio is calculated with the standard value of the spot distortion rate to obtain the spot distortion degree ratio. The Analytic Hierarchy Process (AHP) was used to set the proportion of distortion step lengths and the weight of the degree of spot distortion. The proportion of distortion step lengths and the degree of spot distortion were weighted and summed to obtain the distortion risk value. If the distortion risk value is greater than or equal to the distortion risk threshold, it indicates that the distortion risk of the light spot is high under high-speed motion. If the distortion risk value is less than the distortion risk threshold, it means that the distortion risk of the light spot is low under high-speed motion. The technical solution of this invention is as follows: Simulate the light field distribution under high-speed motion conditions, acquire dynamic spot morphology in real time, construct a dynamic spot intensity matrix, and determine the spot distortion rate corresponding to the time step under high-speed motion conditions by combining the static spot morphology; based on the spot distortion rate corresponding to the time step under high-speed motion conditions, perform deviation analysis to assess the distortion risk of the spot under high-speed motion conditions; this invention builds a platform that fits the actual scenario through joint simulation using OpticStudio and MATLAB, introduces a kinematic delay and synchronization error model to restore the real spot distortion phenomenon, and accurately quantifies the spot distortion rate at each time step based on the minimum bounding rectangle method; then, through the dual indicators of distortion step length ratio and distortion degree ratio, combined with the analytic hierarchy process (AHP) to construct a distortion risk assessment system, it achieves accurate quantification and scientific risk assessment of spot distortion under high-speed motion conditions. This provides data support for identifying key time nodes of spot distortion and provides a clear decision-making basis for subsequent optimization of high-speed scanning system parameters and reduction of distortion risk, taking into account the realism of simulation, the accuracy of calculation, and the comprehensiveness of assessment.
[0021] Example 2 like Figure 1 As shown in the figure, a method for simulating and optimizing the spot quality based on an acousto-optic deflector and galvanometer cooperative system according to an embodiment of the present invention further includes the following steps: Step 3: If the distortion risk is high, use the controlled variable method to simulate and test the synchronization error value between the acousto-optic deflector and the galvanometer under high-speed motion, create a data table of synchronization error threshold spot distortion rate, and analyze the relationship between synchronization error value and spot distortion rate under high-speed motion. In the co-simulation platform, all working parameters of the high-speed motion state are first set and kept unchanged, and only the synchronization error is used as the only variable to ensure that the change in the spot distortion rate is only caused by the synchronization error. In the MATLAB motion control simulation module, the synchronization error model is set to a mode where fixed values can be manually input, ensuring that only one specific synchronization error value is output for each simulation, which facilitates accurate correspondence to the spot distortion rate. Create a data table for synchronization error and spot distortion rate to record the statistical results of spot distortion rate corresponding to each synchronization error value; Set the gradient scanning range and scanning step size for the synchronization error. Each scanning step size corresponds to a synchronization error value. Perform simulation based on any synchronization error value and record the spot distortion rate corresponding to the time step. Sort the spot distortion rates corresponding to all time steps in descending order to obtain the spot distortion rate sequence. Extract the first spot distortion rate from the spot distortion rate sequence as the spot distortion rate of the synchronization error value. The spot distortion rate of all synchronization error values is entered into a data table. The data in the data table is imported into MATLAB. A scatter plot of synchronization error versus maximum distortion rate is plotted, and linear fitting is performed to obtain the fitting formula. Based on the data in the data table and the predicted values of the fitting formula, the goodness of fit is calculated. If the goodness of fit is greater than or equal to the goodness of fit threshold, it indicates that the synchronization error value and the spot distortion rate change linearly under high-speed motion. If the goodness of fit is less than the goodness of fit threshold, it indicates that the synchronization error value and the spot distortion rate change non-linearly under high-speed motion.
[0022] Step 4: Based on the relationship between the synchronization error value and the spot distortion rate under high-speed motion, determine the critical synchronization error value to reduce the distortion risk under high-speed motion. When the motion state changes to high-speed motion, dynamically adjust the synchronization error threshold to reduce the distortion risk under high-speed motion. Based on the linear relationship between the synchronization error value and the beam distortion rate under high-speed motion, the standard value of the beam distortion rate is substituted into the fitting formula to obtain the critical synchronization error value. Based on the fact that the synchronization error value and the spot distortion rate change nonlinearly under high-speed motion, the critical synchronization error value is determined by numerical iteration using the fzero function in MATLAB. The critical synchronization error value is used as the synchronization error threshold under high-speed motion. When the motion state changes to high-speed motion, the synchronization error threshold is dynamically adjusted to reduce the risk of distortion under high-speed motion. The technical solution of this invention is as follows: If the distortion risk is high, the controlled variable method is used to simulate and test the synchronization error value of the acousto-optic deflector and the galvanometer under high-speed motion conditions, and a data table of the synchronization error threshold spot distortion rate is created to analyze the relationship between the synchronization error value and the spot distortion rate under high-speed motion conditions. Based on the relationship between the synchronization error value and the spot distortion rate under high-speed motion conditions, the critical synchronization error value for reducing distortion risk under high-speed motion conditions is determined. When the motion state changes to a high-speed motion state, the synchronization error threshold is dynamically adjusted to reduce the distortion risk under high-speed motion conditions. This invention focuses on the key influencing factor of synchronization error in high-distortion risk scenarios using the controlled variable method. Through gradient scanning and data fitting, the relationship type between synchronization error and distortion rate is clarified, and the critical synchronization error value is accurately solved and the threshold is dynamically adjusted. The entire process takes into account the simulation realism, data accuracy, and scheme operability. It not only achieves accurate quantification and risk prediction of spot distortion, but also provides a scientific basis for the optimization of synchronization parameters of high-speed scanning systems, effectively supporting the systematic control and reduction of spot distortion risk under high-speed motion conditions.
[0023] Example 3 Based on the same inventive concept as the spot quality simulation and optimization method based on an acousto-optic deflector and galvanometer cooperative system in the foregoing embodiments, such as Figure 2 As shown, this application provides a spot quality simulation and optimization system based on an acousto-optic deflector and galvanometer cooperative system, wherein the system specifically includes: Distortion rate determination module: Simulates the light field distribution under high-speed motion in the simulation, obtains the dynamic spot shape in real time, constructs the dynamic spot intensity matrix, and combines the static spot shape to determine the spot distortion rate corresponding to the time step under high-speed motion. Distortion risk assessment module: Based on the spot distortion rate corresponding to the time step under high-speed motion, and by performing deviation analysis, the distortion risk of the spot under high-speed motion is assessed. Simulation test module: If the distortion risk is high, the controlled variable method is used to simulate and test the synchronization error value between the acousto-optic deflector and the galvanometer under high-speed motion. A data table of synchronization error threshold spot distortion rate is created to analyze the relationship between synchronization error value and spot distortion rate under high-speed motion. Dynamic adjustment module: Based on the relationship between the synchronization error value and the spot distortion rate under high-speed motion, the critical synchronization error value for reducing distortion risk under high-speed motion is determined. When the motion state changes to high-speed motion, the synchronization error threshold is dynamically adjusted to reduce the distortion risk under high-speed motion.
[0024] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and various changes and modifications can be made without departing from the spirit and scope of the invention; all such changes and modifications will fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.
Claims
1. A method for simulating and optimizing spot quality based on an acousto-optic deflector and galvanometer co-system, characterized in that, include: In the simulation, the light field distribution under high-speed motion is simulated, the dynamic light spot morphology is obtained in real time, the dynamic light spot intensity matrix is constructed, and the light spot distortion rate corresponding to the time step under high-speed motion is determined by combining the static light spot morphology. Based on the spot distortion rate corresponding to the time step under high-speed motion, and by performing deviation analysis, the distortion risk of the spot under high-speed motion is assessed. If the risk of distortion is high, the control variable method is used to simulate and test the synchronization error value between the acousto-optic deflector and the galvanometer under high-speed motion, create a data table of synchronization error threshold spot distortion rate, and analyze the relationship between synchronization error value and spot distortion rate under high-speed motion. Based on the relationship between synchronization error value and spot distortion rate under high-speed motion, the critical synchronization error value for reducing distortion risk under high-speed motion is determined. When the motion state changes to high-speed motion, the synchronization error threshold is dynamically adjusted to reduce the distortion risk under high-speed motion.
2. The method for simulating and optimizing the spot quality based on an acousto-optic deflector and galvanometer cooperative system according to claim 1, characterized in that, The process of constructing the dynamic spot intensity matrix is as follows: A two-dimensional rectangular coordinate system is established with the preset focal point of the processing plane as the origin. The horizontal axis is parallel to the horizontal rotation direction of the galvanometer, and the vertical axis is parallel to the vertical rotation direction of the galvanometer. A co-simulation platform is built based on OpticStudio optical simulation and MATLAB motion control simulation. The high-speed scanning trajectory and high-speed scanning speed are set. The dynamic spot intensity is calculated by using the ray tracing method combined with the finite difference time domain algorithm. The time step and total simulation time are set. The sampling point density of the spot area of the processing plane is fixed. The co-simulation is started. The AOD outputs the diffracted beam at the set frequency, and the galvanometer rotates at the appropriate angular velocity. The simulation model introduces the kinematic delay model to simulate the inertial delay of the galvanometer and the synchronization error model to simulate the deviation of the trigger signal. The dynamic spot intensity matrix of the processing plane is recorded at the set time step.
3. The method for simulating and optimizing the spot quality based on an acousto-optic deflector and galvanometer cooperative system according to claim 2, characterized in that, The process for determining the spot distortion rate corresponding to the time step under high-speed motion is as follows: Keeping all optical and component parameters unchanged, only turning off the motion drive of AOD and galvanometer, the static spot intensity matrix of the processing plane is recorded; The dynamic and static major axis lengths are determined by processing and analyzing all pixel values in the dynamic and static light spot intensity matrices. The difference between the dynamic major axis length and the static major axis length is taken as the absolute value, and then the ratio is calculated with the static major axis length to obtain the spot distortion rate corresponding to the time step under high-speed motion.
4. The method for simulating and optimizing the spot quality based on an acousto-optic deflector and galvanometer cooperative system according to claim 3, characterized in that, The process for determining the dynamic major axis length and the static major axis length is as follows: Normalize all pixel values in the dynamic and static spot intensity matrices, remove noise points, perform coordinate calibration, set a segmentation threshold, retain pixels in the dynamic and static spot matrices that are greater than or equal to the distribution threshold, and determine the effective spot area. Morphological optimization is performed on the effective spot area to extract the boundary pixel set of the effective spot area. Using the minimum bounding rectangle method, the boundary pixel set of the effective spot area is input, and based on the rotation calibration algorithm, all rectangle rotation angles are traversed. The area of the rectangle enclosing the point set under each rectangle rotation angle is calculated, and the rectangle with the smallest area is selected. The lengths of the two adjacent sides of the rectangle with the smallest area are recorded. The longest of the two adjacent sides of the rectangle with the smallest effective spot area corresponding to the dynamic spot matrix is recorded as the dynamic major axis length, and the longest of the two adjacent sides of the rectangle with the smallest effective spot area corresponding to the static spot matrix is recorded as the static major axis length.
5. The method for simulating and optimizing the spot quality based on an acousto-optic deflector and galvanometer cooperative system according to claim 3, characterized in that, The process for assessing the distortion risk of the light spot under high-speed motion is as follows: Based on the spot distortion rate corresponding to the time step under high-speed motion, and by performing deviation analysis, the proportion of the number of distortion steps and the ratio of spot distortion degree are determined. The Analytic Hierarchy Process (AHP) was used to set the proportion of distortion step lengths and the weight of the degree of spot distortion. The proportion of distortion step lengths and the degree of spot distortion were weighted and summed to obtain the distortion risk value. If the distortion risk value is greater than or equal to the distortion risk threshold, it indicates that the distortion risk of the light spot is high under high-speed motion; otherwise, it indicates that the distortion risk of the light spot is low under high-speed motion.
6. The method for simulating and optimizing the spot quality based on an acousto-optic deflector and galvanometer cooperative system according to claim 5, characterized in that, The process for determining the proportion of the distortion step size is as follows: If the spot distortion rate corresponding to the time step is greater than the standard value of the spot distortion rate, then the corresponding time step is the distortion step. The percentage of distortion step sizes within the total simulation duration is calculated.
7. The method for simulating and optimizing the spot quality based on an acousto-optic deflector and galvanometer cooperative system according to claim 6, characterized in that, The process for determining the spot distortion ratio is as follows: The difference between the spot distortion rate corresponding to the distortion step size and the standard value of the spot distortion rate is calculated to obtain the distortion rate deviation corresponding to the distortion step size. The average value of the distortion rate deviations corresponding to all distortion step sizes is summed and then compared with the standard value of the spot distortion rate to obtain the spot distortion degree ratio.
8. The method for simulating and optimizing the spot quality based on an acousto-optic deflector and galvanometer cooperative system according to claim 6, characterized in that, The process of analyzing the relationship between synchronization error and spot distortion rate under high-speed motion is as follows: In the co-simulation platform, all operating parameters under high-speed motion are first set and kept unchanged, with only the synchronization error as the sole variable. Set the gradient scanning range and scanning step size for the synchronization error. Each scanning step size corresponds to a synchronization error value. Perform simulation based on any synchronization error value, record the spot distortion rate corresponding to the time step, and sort them to determine the spot distortion rate of the synchronization error value. The spot distortion rate of all synchronization error values is entered into a data table. The data in the data table is imported into MATLAB. A scatter plot of synchronization error versus maximum distortion rate is plotted, and linear fitting is performed to obtain the fitting formula. Based on the data in the data table, and combined with the predicted values of the fitting formula, the goodness of fit is calculated. If the goodness of fit is greater than or equal to the goodness of fit threshold, it indicates that the synchronization error value and the spot distortion rate change linearly under high-speed motion; otherwise, it indicates that the synchronization error value and the spot distortion rate change non-linearly under high-speed motion.
9. The method for simulating and optimizing the spot quality based on an acousto-optic deflector and galvanometer cooperative system according to claim 8, characterized in that, The process for determining the spot distortion rate of the synchronization error value is as follows: Sort the spot distortion rates corresponding to all time steps in descending order to obtain a spot distortion rate sequence. Extract the spot distortion rate with the first order from the spot distortion rate sequence as the spot distortion rate of the synchronization error value.
10. The method for simulating and optimizing the spot quality based on an acousto-optic deflector and galvanometer cooperative system according to claim 8, characterized in that, The process for determining the critical synchronization error value is as follows: Based on the linear relationship between the synchronization error value and the beam distortion rate under high-speed motion, the standard value of the beam distortion rate is substituted into the fitting formula to obtain the critical synchronization error value. Based on the fact that the synchronization error value and the spot distortion rate change nonlinearly under high-speed motion, the critical synchronization error value is determined by numerical iteration using the fzero function in MATLAB.