High-precision processing control method for ultrathin BBO crystal

Abstract

The invention provides a high-precision machining control method for an ultrathin BBO crystal, and relates to the technical field of intelligent control, and the method comprises the steps: in a virtual environment, setting the target thickness and machining precision of the ultrathin BBO crystal, and through simulation analysis, determining key parameters in an optimized machining flow, including the cutting speed, the polishing pressure and the polishing time; according to the optimized key parameters in the machining process, parameters of machining equipment are adjusted, so that the preset machining precision is achieved in the actual machining process; the machining process is simulated in the virtual environment, and machining data including the thickness change and the surface roughness of the crystal are monitored and recorded in real time; and according to the processing data, the processing process is adjusted and optimized in real time, so that the actually processed ultrathin BBO crystal meets preset requirements. According to the invention, comprehensive optimization of the processing flow and accurate determination of key parameters can be realized.

Description

Technical Field

[0001] The invention relates to the field of intelligent control technology, in particular to a high-precision processing control method for an ultra-thin BBO crystal. Background Art

[0002] With the rapid development of science and technology, ultra-thin optical crystals play an increasingly important role in various high-tech fields. Among them, ultra-thin BBO crystals have broad application prospects in laser technology, optoelectronics, and quantum information science due to their unique nonlinear optical properties. However, high-precision processing of ultra-thin BBO crystals has always been a technical challenge, and its processing quality control is crucial to achieving the excellent performance of the crystal.

[0003] Some traditional ultra-thin BBO crystal processing methods still rely on the operator's experience and skills, and lack precise theoretical guidance and quantitative parameter control during the processing. This easily leads to the difficulty of the processed crystals to meet high-precision requirements in key indicators such as thickness uniformity and surface roughness, thus seriously affecting the optical properties of the crystals and subsequent application effects. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a high-precision processing control method for an ultra-thin BBO crystal, which can achieve comprehensive optimization of the processing flow and accurate determination of key parameters.

[0005] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0006] In a first aspect, a high-precision processing control method for an ultra-thin BBO crystal is provided, the method comprising:

[0007] Establish a virtual processing environment to simulate the processing flow of ultra-thin BBO crystals, and optimize the processing flow of ultra-thin BBO crystals through genetic algorithms to obtain an optimized processing flow, which includes the selection, cutting, and polishing steps of crystal materials;

[0008] In the virtual environment, the target thickness and processing accuracy of the ultra-thin BBO crystal are set, and through simulation analysis, the key parameters in the optimized processing flow, including cutting speed, polishing pressure, and polishing time, are determined;

[0009] According to the key parameters in the optimized processing flow, adjust the parameters of the processing equipment to achieve the predetermined processing accuracy in the actual processing;

[0010] Simulate the machining process in a virtual environment, monitor and record machining data in real time, including crystal thickness changes and surface roughness;

[0011] According to the processing data, the processing process is adjusted and optimized in real time so that the ultra-thin BBO crystal actually processed meets the preset requirements.

[0012] Furthermore, the processing flow of the ultra-thin BBO crystal is optimized by genetic algorithm to obtain an optimized processing flow, including:

[0013] The key parameters of cutting speed, polishing pressure and polishing time are encoded as genes of the genetic algorithm; an initial population including multiple individuals is randomly generated, and each individual represents a set of processing parameters;

[0014] Define a fitness function, and select the corresponding individuals to enter the next generation according to the result of the fitness function; perform crossover and mutation operations on the selected individuals to generate new individuals;

[0015] The selection, crossover and mutation operations are repeated until the termination condition is met, and the final processing parameters optimized by the genetic algorithm are applied to the actual processing equipment to adjust the cutting speed, polishing pressure and polishing time of the processing equipment.

[0016] Furthermore, the calculation formula of the fitness function is:

[0017]

[0018] Among them, F is the fitness value of the individual; E t is the desired crystal thickness; T t is the actual crystal thickness obtained by processing; R s is the roughness value of the crystal surface; D m is the material removal rate deviation during crystal processing; E w is the desired processing width; T w is the actual processed width; α, β and γ are weight coefficients; σ w It is the sensitivity parameter of processing width deviation.

[0019] Furthermore, in the virtual environment, the target thickness and processing accuracy of the ultra-thin BBO crystal are set, and through simulation analysis, the key parameters in the optimized processing flow are determined, including cutting speed, polishing pressure, and polishing time, including:

[0020] Set the target thickness and processing accuracy of ultra-thin BBO crystals;

[0021] Create a 3D model of the BBO crystal to match the actual crystal size and material properties, and set the physical and chemical properties of the BBO crystal, including hardness, fracture toughness, and thermal conductivity;

[0022] By designing different simulation experiments, we explored the effects of parameters such as cutting speed, polishing pressure, and polishing time on the processing results. We ran the experiments and recorded the processing results under each experimental condition, including the final thickness and surface roughness of the crystal, to obtain simulation results.

[0023] The simulation results are analyzed to find the corresponding combination of cutting speed, polishing pressure and polishing time parameters.

[0024] Furthermore, crossover and mutation operations are performed on the selected individuals to generate new individuals, including:

[0025] Randomly select two individuals from the current population as parents through roulette selection;

[0026] For the two selected parent individuals, a crossover point is randomly selected;

[0027] According to the crossover point, the gene sequences of the two parents are partially exchanged. In single-point crossover, a crossover point is selected and all genes of the two parents after that point are exchanged.

[0028] After the crossover operation is completed, two new individuals will be generated;

[0029] An individual is randomly selected from the current population as the object of mutation. Among the selected individuals, a gene position is randomly selected as the mutation point. The selected mutation point is mutated. After the mutation is completed, a new individual will be generated.

[0030] Furthermore, the processing process is simulated in a virtual environment, and the processing data, including the thickness change and surface roughness of the crystal, are monitored and recorded in real time.

[0031] Deploy virtual sensors in the virtual environment to monitor the thickness change and surface roughness of the crystal in real time. During the processing simulation, the sensor data is regularly collected and stored in the database.

[0032] Set the size of the particle swarm, randomly initialize the position and speed of each particle within the range of the processing parameters, set the historical final position of each particle to its initial position, and set the global final position to the optimal position in the initial particle swarm;

[0033] For each particle, the processing parameters corresponding to its position are used to perform processing simulation in a virtual environment, and the crystal thickness and surface roughness data after processing are recorded;

[0034] The fitness value of the particle is calculated according to the crystal thickness and surface roughness data. The speed and position of each particle are updated according to the current position, speed, individual historical optimal position and global final position of the particle. If the preset number of iterations is reached, the iteration is stopped to output the processing parameter combination corresponding to the global final position.

[0035] In the second aspect, a high-precision processing control system for an ultra-thin BBO crystal comprises:

[0036] A construction module is used to establish a virtual processing environment, simulate the processing flow of ultra-thin BBO crystals, and optimize the processing flow of ultra-thin BBO crystals through genetic algorithms to obtain an optimized processing flow, which includes the steps of crystal material selection, cutting, and polishing;

[0037] The simulation analysis module is used to set the target thickness and processing accuracy of ultra-thin BBO crystals in a virtual environment. Through simulation analysis, the key parameters in the optimized processing flow, including cutting speed, polishing pressure, and polishing time, are determined;

[0038] An adjustment module is used to adjust the parameters of the processing equipment according to the key parameters in the optimized processing flow, so as to achieve the predetermined processing accuracy in the actual processing;

[0039] The monitoring module is used to simulate the processing process in a virtual environment and monitor and record the processing data in real time, including the thickness change and surface roughness of the crystal;

[0040] The optimization module is used to adjust and optimize the processing process in real time according to the processing data, so that the ultra-thin BBO crystal actually processed meets the preset requirements.

[0041] According to a third aspect, a computing device includes:

[0042] one or more processors;

[0043] The storage device is used to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method described.

[0044] In a fourth aspect, a computer-readable storage medium stores a program, and when the program is executed by a processor, the method described is implemented.

[0045] The above solution of the present invention includes at least the following beneficial effects:

[0046] By establishing a virtual environment, the processing flow can be simulated without consuming actual materials, which greatly reduces the experimental cost and material waste. At the same time, the virtual environment provides high flexibility and repeatability, which facilitates in-depth research and optimization of the processing process. As a global optimization method, genetic algorithm can efficiently search for the optimal parameter combination in the processing flow. Through genetic algorithm optimization, the processing efficiency can be significantly improved, unnecessary trial and error processes can be reduced, and the optimized processing flow can be quickly obtained. Setting clear target thickness and processing accuracy in the virtual environment makes the optimization process more targeted and goal-oriented. The key parameters determined by simulation analysis (such as cutting speed, polishing pressure, and polishing time) can provide quantitative guidance for achieving high-precision processing and ensure that the processing results meet the expected requirements. Applying the key parameters optimized in the virtual environment to the actual processing equipment can ensure the consistency of the actual processing process with the simulation process. This parameter adjustment method can significantly improve the operating efficiency and processing accuracy of the processing equipment and reduce the difficulty of operation and human errors.

[0047] By real-time monitoring and recording of processing data, the dynamic changes of the processing process can be grasped in real time, and possible problems can be discovered and corrected in a timely manner. This data-driven processing control method helps to improve the transparency and controllability of the processing process and provide data support for further optimization of the processing flow. Real-time adjustment and optimization of the processing process based on real-time monitoring processing data can ensure that the processing process always remains in the best state. This dynamic adjustment mechanism can significantly improve the stability and consistency of the processing, ensuring that the ultra-thin BBO crystal actually processed meets the preset high-precision requirements. At the same time, this optimization method also helps to improve the adaptability of the processing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a flow chart of a high-precision processing control method for an ultra-thin BBO crystal provided by an embodiment of the present invention.

[0049] Figure 2 It is a schematic diagram of a high-precision processing control system for an ultra-thin BBO crystal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0051] like Figure 1As shown, an embodiment of the present invention provides a high-precision processing control method for an ultra-thin BBO crystal, the method comprising the following steps:

[0052] Step 11, establishing a virtual processing environment, simulating the processing flow of the ultra-thin BBO crystal, and optimizing the processing flow of the ultra-thin BBO crystal by genetic algorithm to obtain an optimized processing flow, the processing flow including the steps of crystal material selection, cutting, and polishing;

[0053] Step 12, in a virtual environment, set the target thickness and processing accuracy of the ultra-thin BBO crystal, and determine the key parameters in the optimized processing flow, including cutting speed, polishing pressure, and polishing time, through simulation analysis;

[0054] Step 13, adjusting the parameters of the processing equipment according to the key parameters in the optimized processing flow, so as to achieve the predetermined processing accuracy in the actual processing;

[0055] Step 14, simulating the processing process in a virtual environment, and monitoring and recording the processing data in real time, including the thickness change and surface roughness of the crystal;

[0056] Step 15: According to the processing data, the processing process is adjusted and optimized in real time so that the ultra-thin BBO crystal actually processed meets the preset requirements.

[0057] In an embodiment of the present invention, by establishing a virtual environment, the processing flow can be simulated without consuming actual materials, which greatly reduces the experimental cost and material waste. At the same time, the virtual environment provides a high degree of flexibility and repeatability, which is convenient for in-depth research and optimization of the processing process. Genetic algorithm, as a global optimization method, can efficiently search for the optimal parameter combination in the processing flow. Through genetic algorithm optimization, the processing efficiency can be significantly improved, unnecessary trial and error processes can be reduced, and the optimized processing flow can be quickly obtained. Setting clear target thickness and processing accuracy in the virtual environment makes the optimization process more targeted and goal-oriented. The key parameters (such as cutting speed, polishing pressure, polishing time) determined by simulation analysis can provide quantitative guidance for achieving high-precision processing and ensure that the processing results meet the expected requirements. Applying the key parameters optimized in the virtual environment to the actual processing equipment can ensure the consistency of the actual processing process with the simulation process. This parameter adjustment method can significantly improve the operating efficiency and processing accuracy of the processing equipment, and reduce the difficulty of operation and human errors.

[0058] By real-time monitoring and recording of processing data, the dynamic changes of the processing process can be grasped in real time, and possible problems can be discovered and corrected in a timely manner. This data-driven processing control method helps to improve the transparency and controllability of the processing process and provide data support for further optimization of the processing flow. Real-time adjustment and optimization of the processing process based on real-time monitoring processing data can ensure that the processing process always remains in the best state. This dynamic adjustment mechanism can significantly improve the stability and consistency of the processing, ensuring that the ultra-thin BBO crystal actually processed meets the preset high-precision requirements. At the same time, this optimization method also helps to improve the adaptability of the processing process.

[0059] In a preferred embodiment of the present invention, step 11, establishing a virtual processing environment to simulate the processing flow of ultra-thin BBO crystals, may include:

[0060] According to the characteristics of ultra-thin BBO crystal processing, select a powerful and easy-to-operate simulation software, such as SolidWorks Simulation, ANSYS, etc., which can simulate physical processes and provide accurate results. Use CAD (computer-aided design) software, such as AutoCAD or SolidWorks, to create an accurate three-dimensional model of ultra-thin BBO crystal. This model should accurately reflect the geometry, size and material properties of the crystal. In the simulation software, set the correct material properties for the BBO crystal model, including density, hardness, elastic modulus, thermal conductivity, etc., to ensure the accuracy of the simulation. According to the actual processing equipment and process, define the cutting tools, polishing tools, etc. used in the simulation, and set their physical properties and motion trajectories. Mesh the BBO crystal model to generate a mesh for finite element analysis. The fineness of the mesh will affect the accuracy and calculation time of the simulation.

[0061] Define the boundary conditions in the simulation process, such as fixed support, load application, etc. At the same time, set the initial conditions, such as initial temperature, stress distribution, etc. According to the actual processing flow, write scripts or programs to control the processing steps in the simulation, including material selection, cutting, polishing, etc. These scripts should be able to simulate the actual processing operations and record the results of each step. Run the written processing flow script in the simulation software, observe and record various data in the simulation process, such as stress distribution, temperature change, material removal rate, etc. Compare the simulation results with the actual processing experimental data to verify the accuracy and reliability of the simulation. If necessary, the simulation model can be adjusted and optimized to improve the accuracy of the simulation. Through the above concrete steps, an accurate virtual processing environment can be established to simulate the entire processing process of ultra-thin BBO crystals.

[0062] In a preferred embodiment of the present invention, the processing flow of the ultra-thin BBO crystal is optimized by a genetic algorithm to obtain an optimized processing flow, including:

[0063] Encode the key parameters of cutting speed, polishing pressure and polishing time as genes of the genetic algorithm; randomly generate an initial population containing multiple individuals, each individual represents a set of processing parameters, specifically including: determine the reasonable range of cutting speed, polishing pressure and polishing time, and choose binary coding, real number coding and other methods to encode the parameters. For example, if binary coding is used, each parameter can be represented by a binary string of fixed length. The codes of the three parameters are connected in series to form a long gene string, which represents an individual (a set of processing parameters). Determine the number of individuals in the population, such as 100, and use a random number generator to randomly generate a specified number of individuals according to the coding method in step 1 to form an initial population.

[0064] Define a fitness function, and select the corresponding individuals to enter the next generation according to the result of the fitness function; perform crossover and mutation operations on the selected individuals to generate new individuals, specifically including: for each individual in the population, use the fitness function to calculate its fitness value, and according to the fitness value, use roulette wheel selection, tournament selection and other methods to select excellent individuals to enter the next generation; randomly select two selected individuals, perform crossover operations (such as single-point crossover, multi-point crossover, etc.) to generate new individuals, and perform mutation operations (such as flipping the value of a certain gene position) on the newly generated individuals or the originally selected individuals with a certain probability.

[0065] The selection, crossover and mutation operations are repeated until the termination condition is met, and the final processing parameters optimized by the genetic algorithm are applied to the actual processing equipment to adjust the cutting speed, polishing pressure and polishing time of the processing equipment. Specifically, the gene string of the final individual optimized by the genetic algorithm is decoded into actual cutting speed, polishing pressure and polishing time parameter values, the decoded parameter values ​​are input into the control system of the processing equipment, the corresponding settings of the equipment are adjusted, and the adjusted parameters are used for actual ultra-thin BBO crystal processing.

[0066] In an embodiment of the present invention, the genetic algorithm can globally search for the optimal combination of processing parameters, avoiding the blindness and time-consuming nature of the traditional trial and error method. By quickly finding the optimal cutting speed, polishing pressure and polishing time, the processing efficiency can be significantly improved, and unnecessary processing cycles and costs can be reduced. The optimized processing parameters can ensure that the stress and heat distribution of the ultra-thin BBO crystal during the processing is more uniform, thereby reducing the possibility of residual stress and cracks inside the crystal. This helps to improve the overall quality and optical properties of the crystal. The processing parameters optimized by the genetic algorithm are the best combination determined after multiple iterations and selections, so they can show higher stability and reliability in practical applications. This reduces uncertainty and risk in the processing process.

[0067] In a preferred embodiment of the present invention, the calculation formula of the fitness function is:

[0068]

[0069] Among them, F is the fitness value of the individual; E t is the desired crystal thickness; T t is the actual crystal thickness obtained by processing; R s is the roughness value of the crystal surface; D m is the material removal rate deviation during crystal processing; E w is the desired processing width; T w is the actual processed width; α, β and γ are weight coefficients; σ w It is the sensitivity parameter of processing width deviation.

[0070] In an embodiment of the present invention, the function can simultaneously consider multiple processing objectives, such as thickness accuracy, surface quality, processing efficiency, etc., to ensure that various indicators are balanced and improved during the optimization process, so as to obtain a processing parameter combination with better comprehensive performance. By adjusting the weight coefficient, the priority of each indicator can be flexibly adjusted according to actual needs. For example, in the scenario of pursuing extreme thickness accuracy, the weight of items related to thickness deviation can be increased. The exponential term and Gaussian function part contained in the function can accurately reflect the influence of processing width deviation on fitness, making the optimization process more refined and accurate. This design helps to find a parameter combination that can accurately control the processing size. Since the fitness function comprehensively considers multiple factors, the optimized processing parameters not only perform well under specific conditions, but also maintain good performance when the processing conditions change within a certain range, thereby enhancing the robustness of the processing process. By combining genetic algorithms with carefully designed fitness functions for parameter optimization, the number of trial and error times and experimental costs can be significantly reduced, and a near-optimal processing parameter combination can be quickly found, thereby improving overall processing efficiency.

[0071] In a preferred embodiment of the present invention, the target thickness and processing accuracy of the ultra-thin BBO crystal are set in a virtual environment, and the key parameters in the optimized processing flow, including cutting speed, polishing pressure, and polishing time, are determined through simulation analysis, including:

[0072] Setting the target thickness and processing accuracy of the ultra-thin BBO crystal includes: clarifying the target thickness value of the ultra-thin BBO crystal according to the application requirements or product design specifications, such as setting it to 50 microns; determining the allowable thickness deviation range during the processing, that is, the processing accuracy. For example, setting the processing accuracy to ±2 microns means that the thickness of the final product should be between 48 and 52 microns.

[0073] Create a three-dimensional model of the BBO crystal to match the three-dimensional model with the actual crystal size and material properties, and set the physical and chemical properties of the BBO crystal, including hardness, fracture toughness and thermal conductivity. Specifically, use professional three-dimensional modeling software (such as SolidWorks, AutoCAD, etc.), use precision measuring tools (such as microscopes, thickness gauges, etc.) to measure the size of the actual BBO crystal, and create a three-dimensional model that matches the actual crystal size based on the measured data in the modeling software. Set the physical and chemical properties of the BBO crystal in the model, including hardness, fracture toughness and thermal conductivity, etc. These property data can be obtained through literature search or experimental measurement.

[0074] By designing different simulation experiments to explore the effects of parameters such as cutting speed, polishing pressure, and polishing time on the processing results, run the experiments, and record the processing results under each experimental condition, including the final thickness and surface roughness of the crystal, to obtain simulation results. Specifically, it includes: using professional software that supports processing simulation (such as ANSYS, Abaqus, etc.), designing a series of simulation experiments, each experiment explores the effects of different cutting speed, polishing pressure, and polishing time combinations on the processing results. Ensure that the parameter range of the experimental design covers the scenarios that may be encountered in actual applications, import the three-dimensional model of the BBO crystal into the simulation software, and set the corresponding processing parameters (cutting speed, polishing pressure, polishing time) according to the experimental design; start the simulation program, observe and record the processing process under each experimental condition, and after the simulation is completed, record the processing results under each experimental condition, including the final thickness and surface roughness of the crystal. These data will be used for subsequent simulation result analysis.

[0075] Analyze the simulation results and find the corresponding combination of cutting speed, polishing pressure and polishing time parameters, including: organizing all the data recorded in the simulation experiment into tables or charts for easy analysis and comparison, analyzing the final thickness and surface roughness data of the crystal under different parameter combinations, and finding the parameter combination range that meets the target thickness and processing accuracy requirements. In the parameter combination that meets the requirements, further consider factors such as processing efficiency and equipment life, and select the optimal cutting speed, polishing pressure and polishing time parameter combination.

[0076] In an embodiment of the present invention, through simulation analysis, the processing results under different parameter combinations can be predicted before actual processing, so as to more accurately achieve the set target thickness and processing accuracy. This significantly reduces the processing errors caused by improper parameter settings and improves the qualified rate of products. The simulation experiment in the virtual environment replaces part of the actual processing experiment, reduces material consumption and equipment wear, and thus reduces the experimental cost. At the same time, the rapid iteration characteristics of the simulation experiment also shorten the research and development cycle, further saving time and resources. By analyzing the simulation results, the optimal combination of parameters such as cutting speed, polishing pressure and polishing time can be found. These parameters have been verified in experiments to effectively improve the processing quality and efficiency. Applying these optimized parameters to actual processing can significantly improve production efficiency. Simulating the processing flow in a virtual environment can provide a deeper understanding of the physical and chemical changes in the processing process and how these changes affect the final product quality. This understanding makes the control of the processing process more accurate and reliable, reducing uncertainty and risk. Virtual simulation technology provides a powerful tool for the optimization and innovation of the processing flow. By continuously conducting experiments and explorations in a virtual environment, new processing methods and technologies can be discovered to promote the continuous advancement of ultra-thin BBO crystal processing technology.

[0077] In a preferred embodiment of the present invention, crossover and mutation operations are performed on the selected individuals to generate new individuals, including:

[0078] Randomly select two individuals from the current population as parents through roulette selection;

[0079] For the two selected parent individuals, a crossover point is randomly selected;

[0080] According to the crossover point, the gene sequences of the two parents are partially exchanged. In single-point crossover, a crossover point is selected and all genes of the two parents after that point are exchanged.

[0081] After the crossover operation is completed, two new individuals will be generated;

[0082] An individual is randomly selected from the current population as the object of mutation. Among the selected individuals, a gene position is randomly selected as the mutation point. The selected mutation point is mutated. After the mutation is completed, a new individual will be generated.

[0083] In the embodiment of the present invention, crossover and mutation operations can effectively increase the diversity of the population. By exchanging the gene sequences of the parent individuals or changing specific genes, new individuals different from the parent can be generated, thereby enriching the gene pool of the population. This diversity helps the algorithm to explore more possible solutions in the search space and avoid falling into the local optimum. The crossover operation combines the advantages of different individuals and may produce offspring with better performance. The mutation operation helps to jump out of the current search area and explore new possible solutions. These operations together improve the global search ability of the algorithm, making it more likely to find the global optimal solution. During the execution of the genetic algorithm, the population may converge to a local optimal solution rather than the global optimal solution prematurely. Through the crossover and mutation operations, new gene combinations can be introduced to break the current equilibrium state, thereby preventing the algorithm from converging prematurely. Since the crossover and mutation operations can produce diverse individuals, the algorithm is less dependent on the selection of the initial population and parameter settings. This means that even if the initial conditions are not optimal, the algorithm is still likely to find high-quality solutions through crossover and mutation, thereby enhancing the robustness of the algorithm.

[0084] In a preferred embodiment of the present invention, step 13, adjusting the parameters of the processing equipment according to the key parameters in the optimized processing flow so as to achieve a predetermined processing accuracy in the actual processing process, may include:

[0085] Obtain the optimized key processing parameters from the previous simulation analysis and optimization process, including cutting speed, polishing pressure, polishing time, etc. Perform a comprehensive inspection of the processing equipment to be used to ensure that the equipment is in good working condition; prepare and adjust the auxiliary tools, fixtures and consumables required for processing as needed. Set new cutting speed parameters in the control system of the equipment according to the optimization results. If the equipment supports stepless speed regulation, adjust it accurately to the optimized value; if the equipment is graded speed regulation, select the gear closest to the optimized value. Adjust the pressure control device of the polishing machine to ensure that the pressure applied to the BBO crystal during polishing matches the optimized parameters, which involves adjusting the set value of the air pressure or hydraulic system. Set a new polishing time in the control program of the polishing machine. Ensure that the time setting is accurate to meet the optimized processing requirements.

[0086] In a preferred embodiment of the present invention, the processing process is simulated in a virtual environment, and the processing data, including the thickness change and surface roughness of the crystal, are monitored and recorded in real time, including:

[0087] Deploy virtual sensors in the virtual environment to monitor the thickness change and surface roughness of the crystal in real time. During the processing simulation, the sensor data is regularly collected and stored in the database.

[0088] Set the size of the particle swarm, randomly initialize the position and speed of each particle within the range of the processing parameters, set the historical final position of each particle to its initial position, and set the global final position to the optimal position in the initial particle swarm;

[0089] For each particle, the processing parameters corresponding to its position are used to perform processing simulation in a virtual environment, and the crystal thickness and surface roughness data after processing are recorded;

[0090] The fitness value of the particle is calculated according to the crystal thickness and surface roughness data. The speed and position of each particle are updated according to the current position, speed, individual historical optimal position and global final position of the particle. If the preset number of iterations is reached, the iteration is stopped to output the processing parameter combination corresponding to the global final position.

[0091] In an embodiment of the present invention, by simulating the processing process in a virtual environment, there is no need to perform actual physical processing, thereby saving a lot of material costs, equipment use costs and time costs. At the same time, virtual experiments can be quickly iterated, further accelerating the R&D cycle. Deploying virtual sensors can monitor the thickness changes and surface roughness of crystals in real time, which are essential for evaluating processing quality and optimizing processing processes. By storing these data in a database, subsequent data analysis and processing can be conveniently performed. The particle swarm optimization algorithm has a powerful global search capability and can efficiently find the optimal or approximately optimal combination of processing parameters within the range of processing parameters. This helps to improve the accuracy and efficiency of the processing process. The particle swarm optimization algorithm adapts to changes in the search space by continuously updating the speed and position of each particle, so that the search strategy can be adaptively adjusted to find a better solution. This adaptability enables the algorithm to flexibly respond to different processing scenarios and problems. Since the simulation in the virtual environment is controllable and repeatable, it can ensure that the conditions of each experiment are consistent, thereby eliminating the experimental errors caused by differences in the environment, equipment or operation in actual processing. This helps to obtain more accurate and reliable experimental results. Before actual processing, simulation and optimization in a virtual environment can pre-identify and solve potential problems, thereby reducing the risks and uncertainties that may be encountered during the actual processing.

[0092] In the embodiment of the present invention, the calculation formula of the fitness value is:

[0093]

[0094] Among them, w1, w2 and w3 represent weight coefficients; Tactual Indicates the actual measured crystal thickness; T target Indicates the preset target crystal thickness; σ T represents the standard deviation of the acceptable thickness error range; R represents the surface roughness of the crystal measured by the virtual sensor, which is a positive number used to evaluate the smoothness of the crystal surface; R ref Represents the reference roughness value, which is used to standardize the surface roughness; n represents the parameter that controls the steepness of the Sigmoid function. A larger n value will make the function close to R in roughness. ref The change is more dramatic when the crystal size is larger than the crystal size. A represents the value of an additional indicator, such as the size uniformity of the crystal, which can be the difference between the maximum size and the minimum size. A max Indicates the maximum acceptable size difference.

[0095] In the above step 15, the processing process is adjusted and optimized in real time according to the processing data so that the ultra-thin BBO crystal actually processed meets the preset requirements, which may include:

[0096] During the processing, sensors and monitoring systems are used to collect key processing data in real time, including but not limited to cutting speed, cutting depth, cutting temperature, material removal rate, etc., while monitoring the real-time thickness, surface roughness, and possible additional indicators (such as dimensional uniformity) of the crystal. The collected data is compared and analyzed with the preset target values ​​to identify deviations and anomalies; statistical methods are used to analyze the data and identify the key factors affecting the processing quality. Based on the results of the data analysis, a feedback control system is designed that can dynamically adjust the processing parameters according to the current processing status.

[0097] For example, if the actual thickness is greater than the target thickness, the system can automatically reduce the cutting depth or increase the cutting speed. Use optimization algorithms (such as genetic algorithms, particle swarm optimization, etc.) to automatically adjust processing parameters to maximize the fitness value. According to the output of feedback control and optimization algorithms, adjust the parameter settings of the processing machine tool, such as the speed, feed rate, cutting depth, etc. of the cutting tool in real time. Ensure that the adjustment process is smooth and does not affect the stability and safety of the processing process. After each adjustment, the processed crystal is quality inspected to verify whether the adjustment effect meets the preset requirements. Record the parameter changes, quality inspection results, and fitness values ​​of each adjustment for subsequent analysis and continuous improvement. Based on the results and data analysis of each processing, continuously optimize the processing parameters and feedback control strategies. Establish a continuous improvement cycle to gradually approach the preset processing requirements through multiple iterations. Set abnormal thresholds during the processing process, and trigger the early warning mechanism when the data exceeds these thresholds. For abnormal situations that cannot be adjusted automatically, promptly notify the operator for manual intervention.

[0098] Through the above-mentioned specific implementation process, it can be ensured that the processing process can be dynamically adjusted and optimized according to real-time data, so as to produce ultra-thin BBO crystals that meet the preset requirements.

[0099] like Figure 2 As shown, an embodiment of the present invention further provides a high-precision processing control system for an ultra-thin BBO crystal, comprising:

[0100] A construction module is used to establish a virtual processing environment, simulate the processing flow of ultra-thin BBO crystals, and optimize the processing flow of ultra-thin BBO crystals through genetic algorithms to obtain an optimized processing flow, which includes the steps of crystal material selection, cutting, and polishing;

[0101] The simulation analysis module is used to set the target thickness and processing accuracy of ultra-thin BBO crystals in a virtual environment. Through simulation analysis, the key parameters in the optimized processing flow, including cutting speed, polishing pressure, and polishing time, are determined;

[0102] An adjustment module is used to adjust the parameters of the processing equipment according to the key parameters in the optimized processing flow, so as to achieve the predetermined processing accuracy in the actual processing;

[0103] The monitoring module is used to simulate the processing process in a virtual environment and monitor and record the processing data in real time, including the thickness change and surface roughness of the crystal;

[0104] The optimization module is used to adjust and optimize the processing process in real time according to the processing data, so that the ultra-thin BBO crystal actually processed meets the preset requirements.

[0105] It should be noted that the system is a system corresponding to the above method, and all implementation methods in the above method embodiment are applicable to this embodiment and can achieve the same technical effect.

[0106] The embodiment of the present invention further provides a computing device, comprising: a processor, a memory storing a computer program, wherein when the computer program is executed by the processor, the method described above is executed. All implementations in the above method embodiment are applicable to this embodiment and can achieve the same technical effect.

[0107] The embodiment of the present invention also provides a computer-readable storage medium storing instructions, which, when executed on a computer, enable the computer to execute the method described above. All implementations in the above method embodiment are applicable to this embodiment and can achieve the same technical effect.

[0108] The above is 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 the scope of protection of the present invention.

Claims

1. A high-precision processing control method for ultra-thin BBO crystal, characterized in that: The method comprises: Establish a virtual processing environment to simulate the processing flow of ultra-thin BBO crystals, and optimize the processing flow of ultra-thin BBO crystals through genetic algorithms to obtain an optimized processing flow, which includes the selection, cutting, and polishing steps of crystal materials; In the virtual environment, the target thickness and processing accuracy of the ultra-thin BBO crystal are set, and through simulation analysis, the key parameters in the optimized processing flow, including cutting speed, polishing pressure, and polishing time, are determined; According to the key parameters in the optimized processing flow, adjust the parameters of the processing equipment to achieve the predetermined processing accuracy in the actual processing; Simulate the machining process in a virtual environment, monitor and record machining data in real time, including crystal thickness changes and surface roughness; According to the processing data, the processing process is adjusted and optimized in real time so that the ultra-thin BBO crystal actually processed meets the preset requirements.

2. The high-precision processing control method for ultra-thin BBO crystal according to claim 1 is characterized in that: The processing flow of ultra-thin BBO crystals is optimized by genetic algorithm to obtain the optimized processing flow, including: The key parameters of cutting speed, polishing pressure and polishing time are encoded as genes of the genetic algorithm; an initial population including multiple individuals is randomly generated, and each individual represents a set of processing parameters; Define a fitness function, and select the corresponding individuals to enter the next generation according to the result of the fitness function; perform crossover and mutation operations on the selected individuals to generate new individuals; The selection, crossover and mutation operations are repeated until the termination condition is met, and the final processing parameters optimized by the genetic algorithm are applied to the actual processing equipment to adjust the cutting speed, polishing pressure and polishing time of the processing equipment.

3. The high-precision processing control method for ultra-thin BBO crystal according to claim 2 is characterized in that: The calculation formula of the fitness function is: Among them, F is the fitness value of the individual; E t is the desired crystal thickness; T t is the actual crystal thickness obtained by processing; R s is the roughness value of the crystal surface; D m is the material removal rate deviation during crystal processing; E w is the desired processing width; T w is the actual processed width; α, β and γ are weight coefficients; σ w It is the sensitivity parameter of processing width deviation.

4. The high-precision processing control method for ultra-thin BBO crystal according to claim 3 is characterized in that: In the virtual environment, the target thickness and processing accuracy of the ultra-thin BBO crystal are set. Through simulation analysis, the key parameters in the optimized processing flow are determined, including cutting speed, polishing pressure, and polishing time, including: Set the target thickness and processing accuracy of ultra-thin BBO crystals; Create a 3D model of the BBO crystal to match the actual crystal size and material properties, and set the physical and chemical properties of the BBO crystal, including hardness, fracture toughness, and thermal conductivity; By designing different simulation experiments, we explored the effects of parameters such as cutting speed, polishing pressure, and polishing time on the processing results. We ran the experiments and recorded the processing results under each experimental condition, including the final thickness and surface roughness of the crystal, to obtain simulation results. The simulation results are analyzed to find the corresponding combination of cutting speed, polishing pressure and polishing time parameters.

5. The high-precision processing control method for ultra-thin BBO crystal according to claim 4, characterized in that: Perform crossover and mutation operations on the selected individuals to generate new individuals, including: Randomly select two individuals from the current population as parents through roulette selection; For the two selected parent individuals, a crossover point is randomly selected; According to the crossover point, the gene sequences of the two parents are partially exchanged. In single-point crossover, a crossover point is selected and all genes of the two parents after that point are exchanged. After the crossover operation is completed, two new individuals will be generated; An individual is randomly selected from the current population as the object of mutation. Among the selected individuals, a gene position is randomly selected as the mutation point. The selected mutation point is mutated. After the mutation is completed, a new individual will be generated.

6. The high-precision processing control method for ultra-thin BBO crystal according to claim 5, characterized in that: Simulate the machining process in a virtual environment, monitor and record machining data in real time, including crystal thickness change, surface roughness, including: Deploy virtual sensors in the virtual environment to monitor the thickness change and surface roughness of the crystal in real time. During the processing simulation, the sensor data is regularly collected and stored in the database. Set the size of the particle swarm, randomly initialize the position and speed of each particle within the range of the processing parameters, set the historical final position of each particle to its initial position, and set the global final position to the optimal position in the initial particle swarm; For each particle, the processing parameters corresponding to its position are used to perform processing simulation in a virtual environment, and the crystal thickness and surface roughness data after processing are recorded; The fitness value of the particle is calculated according to the crystal thickness and surface roughness data. The speed and position of each particle are updated according to the current position, speed, individual historical optimal position and global final position of the particle. If the preset number of iterations is reached, the iteration is stopped to output the processing parameter combination corresponding to the global final position.

7. A high-precision processing control system for ultra-thin BBO crystals, characterized in that: Applied to the method according to any one of claims 1 to 6, comprising: A construction module is used to establish a virtual processing environment, simulate the processing flow of ultra-thin BBO crystals, and optimize the processing flow of ultra-thin BBO crystals through genetic algorithms to obtain an optimized processing flow, which includes the steps of crystal material selection, cutting, and polishing; The simulation analysis module is used to set the target thickness and processing accuracy of ultra-thin BBO crystals in a virtual environment. Through simulation analysis, the key parameters in the optimized processing flow, including cutting speed, polishing pressure, and polishing time, are determined; An adjustment module is used to adjust the parameters of the processing equipment according to the key parameters in the optimized processing flow, so as to achieve the predetermined processing accuracy in the actual processing; The monitoring module is used to simulate the processing process in a virtual environment and monitor and record the processing data in real time, including the thickness change and surface roughness of the crystal; The optimization module is used to adjust and optimize the processing process in real time according to the processing data, so that the ultra-thin BBO crystal actually processed meets the preset requirements.

8. A computing device, characterized in that include: one or more processors; A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the method as claimed in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program, which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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