CN117646272A - Control system and method for monitoring crystal growth - Google Patents
Control system and method for monitoring crystal growth Download PDFInfo
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Abstract
The invention discloses a control system and a control method for monitoring crystal growth, and relates to the technical field of crystal growth. The invention utilizes means such as an optical microscope, a super-resolution technology, a numerical simulation technology and the like to efficiently acquire, process and analyze the morphology and boundary information of the crystal, thereby realizing accurate calculation of the growth rate and the growth direction of the crystal, and effective evaluation of the target and the standard of the crystal growth, analyzing morphology change and growth mechanism in the crystal growth process, and simultaneously adjusting related parameters in the crystal growth process in real time according to the state and the abnormality of the crystal growth so as to improve the quality and the efficiency of the crystal growth.
Description
Technical Field
The invention belongs to the technical field of crystal growth, and particularly relates to a control system and a control method for monitoring crystal growth.
Background
Crystal growth is an important material preparation technology, which can produce crystal materials with excellent optical, electronic, magnetic, catalytic and other properties, and is widely applied to the fields of information, energy, environment, medicine and the like. However, crystal growth is a complex physicochemical process that is affected by a variety of factors such as temperature, pressure, flow of reaction gas, type and structure of crystal, and there are complex interactions and feedback mechanisms between these factors, resulting in difficult prediction and control of the process and result of crystal growth. In order to effectively monitor and control crystal growth, a complete crystal growth monitoring control system needs to be established, so that the real-time acquisition, processing and analysis of the morphology and boundary information of the crystal and the real-time adjustment and optimization of relevant parameters in the crystal growth process are realized.
Currently, there have been some researches and developments on crystal growth monitoring control systems, but these systems have some problems and disadvantages, which are mainly expressed in the following aspects:
(1) The information acquisition capability of the crystal growth monitoring control system is not efficient enough, and the high-resolution and high-precision acquisition of the morphology and boundary information of the crystal cannot be realized. At present, a crystal growth monitoring control system mainly relies on an optical microscope to perform in-situ imaging of crystals, but the defects of low resolution, noise interference and the like exist in the mode that the morphology and boundary information of the crystals obtained by the optical microscope are not subjected to effective post-processing. Moreover, due to physical limitation of an optical microscope, the acquired crystal image often has the problems of distortion, blurring, unclear and the like, so that the morphology and boundary information of the crystal are difficult to accurately acquire.
(2) The crystal growth monitoring control system cannot realize comprehensive and deep analysis of morphology and boundary changes in the crystal growth process. At present, most crystal growth monitoring control systems also rely on simple data calculation and evaluation, which are difficult to reflect the change rules, influence factors, sensibility and risk of the data and difficult to give effective improvement suggestions or early warning prompts, because the morphology and boundary change in the crystal growth process involve data in multiple aspects such as the growth rate, growth direction, growth mechanism, morphology characteristics, boundary parameters and the like.
(3) The crystal growth monitoring control system cannot realize effective control and optimization of morphology and boundary changes in the crystal growth process. At present, most crystal growth monitoring control systems also rely on manual formulation and execution, and the defects of low efficiency, high cost, easy human interference and the like are overcome, and the shape and boundary change in the crystal growth process involve decisions in multiple aspects, such as temperature, pressure, reaction gas flow and the like, so that the manual formulation and execution is time-consuming and labor-consuming, easy to make mistakes and difficult to ensure effects.
In view of the above, there are many problems and disadvantages in the present crystal growth monitoring control system in China, and improvement and innovation are needed.
Disclosure of Invention
In view of the above problems, the present embodiment provides a control system for monitoring crystal growth, which can achieve efficient acquisition, intelligent processing and deep analysis of morphology and boundary information of crystals, and real-time adjustment and optimization of relevant parameters in the crystal growth process, thereby improving the efficiency and quality of crystal growth. The technical scheme of the embodiment comprises the following steps:
the information acquisition module is used for carrying out in-situ imaging on the crystal in the crystal growth equipment by utilizing an optical microscope to acquire morphology and boundary information of the crystal;
The image processing module is used for receiving the morphology and boundary information of the crystal acquired by the information acquisition module and tracking the extension and contraction information of the boundary of the crystal in real time according to the super resolution technology;
the data analysis module is used for calculating the growth rate and the growth direction of the crystal according to the information output by the image processing module, comparing the growth rate and the growth direction with preset crystal growth targets and standards and analyzing the morphology change and the growth mechanism in the crystal growth process;
the control module is used for sending control signals to crystal growth equipment according to the analysis result output by the data analysis module and preset crystal growth targets and standards, and adjusting related parameters in the crystal growth process in real time, wherein the related parameters comprise temperature, pressure and reaction gas flow;
and the crystal growth equipment is used for controlling the temperature, the pressure and the flow of the reaction gas in the crystal growth process according to the control signal sent by the control module.
The method has the advantages that by utilizing an optical microscope and a super-resolution technology, high-definition imaging of the crystal and accurate detection of the boundary can be realized, so that the morphology and boundary information of the crystal can be effectively monitored; by utilizing a deep learning model and a numerical simulation technology, the calculation and prediction of the growth rate and the growth direction of the crystal can be realized, so that the growth mechanism and influence factors of the crystal are effectively analyzed; by utilizing the fuzzy control and image registration technology, the real-time adjustment and abnormality processing of relevant parameters in the crystal growth process can be realized, thereby effectively controlling the growth state and quality of the crystal.
In the preferred embodiment, the purpose of this embodiment is to further improve the accuracy and stability of crystal growth. The technical scheme of the embodiment comprises the following steps:
the system further comprises: the crystal growth simulation module is used for simulating the process and result of crystal growth by utilizing a numerical simulation technology according to the regulated relevant parameters in the crystal growth equipment and the types and structures of the crystals, so as to predict the morphology and boundary information of the crystals;
the crystal growth monitoring module is used for monitoring the state and abnormality of crystal growth in real time according to the morphology and boundary information of the crystal acquired by the information acquisition module, the morphology and boundary information of the crystal are acquired again after the relevant parameters are regulated, and the simulation result output by the crystal growth simulation module is used for timely adjusting the relevant parameters and measures in the crystal growth process.
Under the preferred implementation condition, the beneficial effect of the embodiment is that the simulation of the process and the result of the crystal growth can be realized by utilizing a numerical simulation technology, so that the morphology and the boundary information of the crystal can be effectively predicted; by utilizing an image registration technology, the comparison of the morphology and boundary information of the crystal with a simulation result can be realized, so that the growth state and the abnormality of the crystal can be effectively monitored; by timely adjusting related parameters and measures in the crystal growth process, the control of the precision and stability of the crystal growth can be realized, so that the quality and efficiency of the crystal are improved.
In the preferred embodiment, the purpose of this embodiment is to further improve the accuracy and real-time of the boundary detection and tracking of the crystal. The technical scheme of the embodiment comprises the following steps:
the image processing module specifically comprises: the super-resolution network submodule is used for taking the morphology and boundary information of the crystal acquired by the information acquisition module as input according to a pre-trained deep learning model and outputting a high-resolution crystal image;
the boundary detection network submodule is used for taking the high-resolution crystal image output by the super-resolution network submodule as input and outputting a binary image of a crystal boundary according to a pre-trained deep learning model;
and the boundary tracking sub-module is used for calculating parameters of the crystal boundary in real time according to the binary image output by the boundary detection network sub-module, including the position, the length and the area, and comparing the parameters with the parameters of the previous frame to obtain the extension and contraction information of the crystal boundary.
Under the preferred implementation condition, the method has the beneficial effects that high-resolution imaging of the crystal and automatic detection of the boundary can be realized by utilizing a deep learning model, so that the quality and accuracy of the boundary information of the crystal are effectively improved; by utilizing the boundary tracking technology, the boundary of the crystal can be tracked and calculated in real time, so that the extension and contraction information of the boundary of the crystal can be effectively monitored, and the growth rate and direction of the crystal are reflected.
In the preferred embodiment, the object of the present embodiment is to further improve the accuracy and reliability of calculation and analysis of the growth rate and growth direction of the crystal. The technical scheme of the embodiment comprises the following steps:
the data analysis module specifically comprises: the growth rate calculation sub-module is used for calculating the growth rate of the crystal in different directions according to the extension and contraction information of the crystal boundary output by the boundary tracking sub-module;
the growth direction calculation sub-module is used for calculating the growth direction and crystal face orientation of the crystal according to the position and length information of the crystal boundary output by the boundary tracking sub-module;
the target comparison submodule is used for comparing information output by the growth rate calculation submodule and the growth direction calculation submodule with a preset crystal growth target and a preset standard to obtain deviation and error of crystal growth;
the morphology analysis submodule is used for analyzing morphology change and characteristics including the size, shape, surface roughness and defects of the crystal in the crystal growth process according to the morphology and boundary information of the crystal in the image processing module;
the growth mechanism analysis submodule is used for analyzing the growth mechanism and influencing factors in the crystal growth process according to the information output by the morphology analysis submodule and the types and structures of crystals, including nucleation, diffusion, dissolution, adhesion and evaporation of the crystals.
Under the preferred implementation condition, the beneficial effect of the embodiment is that by utilizing the boundary tracing and boundary detecting technology, the accurate calculation of the growth rate and the growth direction of the crystal can be realized, thereby effectively reflecting the growth state and the quality of the crystal; analysis of growth deviation and error of the crystal can be realized by utilizing target comparison, morphology analysis and growth mechanism analysis technology, so that the growth effect and influencing factors of the crystal can be effectively evaluated.
In a preferred embodiment, the aim of this embodiment is to further increase the efficiency and flexibility of real-time adjustment and optimization of relevant parameters during crystal growth. The technical scheme of the embodiment comprises the following steps:
the control module specifically comprises: the fuzzy control rule base establishing submodule is used for establishing a fuzzy control rule base of the relevant parameters of the crystal growth according to the characteristics of the crystal growth, and comprises a definition domain, a value domain, a membership function and a fuzzy control rule of fuzzy control variables;
the fuzzy inference sub-module is used for obtaining the fuzzy control quantity of the output related parameters according to the input analysis result, the preset target and standard and the fuzzy control rule base by using a fuzzy inference method;
The fuzzy inversion sub-module is used for obtaining the accurate control quantity of the output related parameters according to the fuzzy control quantity of the output related parameters by using a fuzzy inversion method;
and the parameter adjusting sub-module is used for sending control signals to a temperature controller, a pressure controller and a flow controller of the crystal growth equipment according to the output accurate control quantity of the related parameters and adjusting the related parameters in the crystal growth process in real time.
Under the preferred implementation condition, the method has the beneficial effects that the self-adaptive adjustment and optimization of relevant parameters in the crystal growth process can be realized by utilizing the fuzzy control technology, so that the uncertainty and nonlinearity of the crystal growth can be effectively adapted; by utilizing the fuzzy inversion technology, the precise control of relevant parameters in the crystal growth process can be realized, thereby effectively ensuring the precision and stability of the crystal growth.
In a preferred embodiment, the object of this embodiment is to further improve the accuracy and real-time of simulation and monitoring of the process and results of crystal growth. The technical scheme of the embodiment comprises the following steps:
the crystal growth simulation module adopts a numerical simulation technology based on a finite element method.
The crystal growth monitoring module specifically comprises: the image registration sub-module is used for obtaining a crystal image according to the morphology and boundary information of the crystal obtained by the information obtaining module, the morphology and boundary information of the crystal are re-obtained after the related parameters are adjusted, a simulation image is obtained according to a simulation result output by the crystal growth simulation module, and the crystal image and the simulation image are subjected to image registration to obtain the similarity and transformation parameters of the two images;
the crystal growth judging submodule is used for judging whether the crystal growth is consistent with a simulation result according to the similarity and the transformation parameters, and if not, analyzing deviation and reason of the crystal growth and determining the state and abnormality of the crystal growth;
and the crystal growth regulating submodule is used for timely regulating relevant parameters and measures in the crystal growth process according to the state and the abnormality of the crystal growth.
Under the preferred implementation condition, the method has the beneficial effects that the precise simulation of the process and the result of the crystal growth can be realized by utilizing the numerical simulation technology of the finite element method, so that the morphology and the boundary information of the crystal can be effectively predicted; by utilizing the image registration technology, the morphology and boundary information of the crystal can be accurately compared with the simulation result, so that the growth state and abnormality of the crystal can be effectively monitored; by timely adjusting related parameters and measures in the crystal growth process, accurate and stable control of crystal growth can be realized, so that the quality and efficiency of crystals are improved.
In the preferred embodiment, the purpose of this embodiment is to further improve the efficiency and accuracy of similarity calculation of boundary information of crystals. The technical scheme of the embodiment comprises the following steps:
the image registration sub-module calculates the similarity of two images by adopting an image registration method based on gray correlation, and adopts the following formula:
wherein S represents the similarity of two images, I 1 And I 2 The gray values of the crystal image and the analog image are represented, respectively, and i and j represent the pixel coordinates of the image.
Under the preferred implementation condition, the method has the advantages that the quick and accurate calculation of the similarity of the two images can be realized by utilizing the image registration method of gray correlation, so that whether the crystal growth is consistent with a simulation result or not can be effectively judged, and if the crystal growth is inconsistent, the deviation and the reason of the crystal growth are analyzed, and the state and the abnormality of the crystal growth are determined.
The aim of the embodiment is to provide a control method for monitoring crystal growth, which can realize the real-time monitoring and control of the shape, boundary, speed, direction and other parameters in the crystal growth process, thereby improving the quality and efficiency of the crystal. The technical scheme of the embodiment comprises the following steps:
S1, performing in-situ imaging on a crystal by using an optical microscope to obtain morphology and boundary information of the crystal;
s2, tracking extension and contraction information of a crystal boundary in real time based on morphology and boundary information of the crystal according to a super-resolution technology;
s3, calculating the growth rate and the growth direction of the crystal according to the morphology and boundary information of the crystal and the extension and contraction information of the crystal boundary, comparing the growth rate and the growth direction with a preset crystal growth target and standard, and analyzing morphology change and growth mechanism in the crystal growth process;
s4, adjusting relevant parameters in the crystal growth process in real time according to the analysis result in the S3 and a preset crystal growth target and standard, wherein the relevant parameters comprise temperature, pressure and reaction gas flow;
s5, simulating the process and result of crystal growth by utilizing a numerical simulation technology according to the regulated related parameters and the types and structures of the crystals, so as to predict the morphology and boundary information of the crystals;
s6, re-acquiring morphology and boundary information of the crystal after the related parameters are regulated, and monitoring the state and abnormality of the crystal growth in real time according to the re-acquired morphology and boundary information of the crystal and the simulation result in S5, and timely regulating the related parameters and measures in the crystal growth process.
The method has the advantages that by utilizing an optical microscope and a super-resolution technology, high-definition imaging of the crystal and accurate detection of the boundary can be realized, so that the morphology and boundary information of the crystal can be effectively monitored; by utilizing a numerical simulation technology, the calculation and prediction of the growth rate and the growth direction of the crystal can be realized, so that the growth mechanism and influence factors of the crystal are effectively analyzed; by utilizing the fuzzy control and image registration technology, the real-time adjustment and abnormality processing of relevant parameters in the crystal growth process can be realized, thereby effectively controlling the growth state and quality of the crystal.
Drawings
Fig. 1 is a schematic diagram of a system structure in embodiment 1 of the present invention;
fig. 2 is a schematic diagram of a system structure in embodiment 2 of the present invention;
FIG. 3 is a schematic diagram of a system structure in embodiment 3 of the present invention;
fig. 4 is a schematic diagram of a system configuration in embodiment 4 of the present invention;
fig. 5 is a schematic diagram of a system configuration in embodiment 5 of the present invention;
fig. 6 is a flow chart of the method in embodiment 6 of the present invention.
Detailed Description
In order that those skilled in the art will better understand the technical solutions, the following detailed description of the technical solutions is provided with reference to examples, which are exemplary and explanatory only and should not be construed as limiting the scope of the invention in any way.
Example 1:
the embodiment provides a control system for monitoring crystal growth, the structural schematic diagram of which is shown in fig. 1, and the control system comprises the following modules:
and the information acquisition module is used for carrying out in-situ imaging on the crystal in the crystal growth equipment by utilizing the optical microscope to acquire the morphology and boundary information of the crystal. Specifically, the information acquisition module comprises an optical microscope and an image acquisition card, wherein the optical microscope is used for amplifying and observing crystals in the crystal growth equipment, and the image acquisition card is used for converting crystal images observed by the optical microscope into digital signals and transmitting the digital signals to the image processing module. The information acquisition module can realize real-time, continuous and nondestructive observation and acquisition of the crystal, acquire the information such as the size, the shape, the surface characteristics, the boundary position and the like of the crystal, and provide basic data for subsequent image processing and data analysis.
The image processing module is used for receiving the morphology and boundary information of the crystal acquired by the information acquisition module and tracking the extension and contraction information of the boundary of the crystal in real time according to the super resolution technology; the module can reconstruct the image of the crystal with high resolution and detect the boundary by using a deep learning method, thereby improving the image quality and detail of the crystal, and simultaneously, the module can accurately acquire the change information of the crystal boundary and reflect the growth speed and direction of the crystal.
The data analysis module is used for calculating the growth rate and the growth direction of the crystal according to the information output by the image processing module, comparing the growth rate and the growth direction with preset crystal growth targets and standards and analyzing the morphology change and the growth mechanism in the crystal growth process; according to the morphology and boundary information of the crystal and the extension and contraction information of the crystal boundary, the module calculates and analyzes the growth parameters of the crystal, so that the growth characteristics and rules of the crystal are reflected, and meanwhile, the growth quality and effect of the crystal can be evaluated, and whether the crystal reaches the expected target and standard is judged.
The control module is used for sending a control signal to the crystal growth equipment according to the analysis result output by the data analysis module and a preset crystal growth target and standard, and carrying out real-time adjustment on related parameters in the crystal growth process, wherein the related parameters comprise temperature, pressure and reaction gas flow; the module can utilize a fuzzy control method to control and optimize the crystal growth process in real time, so that the crystal growth can be carried out according to the expected target and standard, and meanwhile, the efficiency and stability of the crystal growth can be improved, and the abnormal and uncontrolled crystal growth is avoided.
And the crystal growth equipment is used for controlling the temperature, the pressure and the flow of the reaction gas in the crystal growth process according to the control signal sent by the control module.
The embodiment adopts a control system for monitoring the crystal growth, and the system can realize comprehensive, automatic and intelligent monitoring and control processes for the crystal growth and improve the growth quality and effect of the crystal.
Example 2:
the present embodiment provides a control system for monitoring crystal growth, which is added with a crystal growth simulation module and a crystal growth monitoring module compared with embodiment 1, so as to implement numerical simulation and real-time monitoring of crystal growth, thereby improving accuracy and efficiency of crystal growth. The structure diagram is shown in fig. 2, and comprises the following modules:
and the crystal growth simulation module is used for simulating the process and the result of crystal growth by utilizing a numerical simulation technology according to the regulated relevant parameters in the crystal growth equipment and the types and the structures of the crystals, so as to predict the morphology and the boundary information of the crystals.
Specifically, the crystal growth simulation module adopts a numerical simulation technology based on a finite element method, and the technology comprises the following steps:
(1) Establishing a mathematical model of crystal growth, namely a partial differential equation set, according to the types and structures of the crystals and related parameters in crystal growth equipment, and describing the changes of a temperature field, a pressure field, a concentration field, a speed field and a phase change interface in the crystal growth process;
(2) According to the mathematical model of crystal growth, geometric shapes and boundary conditions in crystal growth equipment, carrying out grid division on a calculation domain of crystal growth to obtain a series of finite elements;
(3) Discretizing a mathematical model of crystal growth according to the principle of a finite element method to obtain a series of algebraic equation sets, and describing the states and the relations of each finite element in the crystal growth process;
(4) Solving algebraic equation sets according to the regulated related parameters in the control module and initial conditions of crystal growth to obtain the temperature, pressure, concentration, speed and numerical solution of a phase change interface of each finite element in the crystal growth process;
(5) And reconstructing the process and the result of crystal growth according to the numerical solution of each finite element and the physical properties of the crystal to obtain the morphology and boundary information of the crystal.
The crystal growth simulation module can simulate and predict the process and the result of crystal growth, and provides more advanced and scientific basis for monitoring and regulating the crystal growth.
The crystal growth monitoring module is used for monitoring the state and abnormality of crystal growth in real time according to the morphology and boundary information of the crystal acquired by the information acquisition module, the morphology and boundary information of the crystal are acquired again after the relevant parameters are regulated, and the simulation result output by the crystal growth simulation module is used for timely adjusting the relevant parameters and measures in the crystal growth process.
Specifically, the crystal growth monitoring module includes the following 3 modules:
the image registration sub-module is used for obtaining a crystal image according to the morphology and boundary information of the crystal obtained by the information obtaining module, the morphology and boundary information of the crystal are re-obtained after the related parameters are adjusted, a simulation image is obtained according to the simulation result output by the crystal growth simulation module, and the crystal image and the simulation image are subjected to image registration to obtain the similarity and transformation parameters of the two images.
Specifically, the image registration submodule adopts an image registration method based on gray correlation, and the method comprises the following steps:
(1) Preprocessing the morphology and boundary information of the crystal acquired by the information acquisition module, including denoising, enhancement, filtering and other operations, so as to obtain a clear crystal image;
(2) Post-processing the simulation result output by the crystal growth simulation module, including operations such as cutting, scaling, rotating and the like, so as to obtain a simulation image matched with the size and the direction of the crystal image;
(3) The calculation of the gray correlation is performed on the crystal image and the analog image, so as to obtain the similarity of the two images, namely, the correlation coefficient of the gray values of the two images, and the transformation parameters of the two images, namely, the parameters of translation, rotation and scaling of the two images, for example, if the correlation coefficient of the gray values of the two images is 0.8, the similarity of the two images is 0.8, if the translation parameter of the two images is (10, 20), the rotation parameter is 30 degrees, the scaling parameter is 1.5, and the transformation parameters of the two images are (10, 20, 30 degrees, 1.5).
Specifically, the similarity of two images is calculated using the following formula:
wherein I is 1 And I 2 Gray values respectively representing the crystal image and the analog image, i and j representing pixel coordinates of the image;
I 1 (I, j) and I 2 (i, j) representing the gray values of the pixels of the ith row and jth column of the crystal image and the analog image, respectively;
I 1 (i,j)I 2 (i, j) represents the gray scale correlation of the pixels of the ith row and jth column of the two images, the gray scale correlation representing the product of the gray scale values of the pixels of the two images at the same position, the greater the gray scale correlation, and vice versa, the smaller the gray scale correlation if the gray scale values of the pixels of the two images at that position are similar;
S represents the overall gray level correlation degree of the two images, i.e. the similarity of the two images, and the gray level correlation coefficient represents the average value of the gray level correlation of the two images divided by the square root of the sum of the squares of the gray values of the two images, so that the influence of the size and distribution of the gray values of the two images can be eliminated, and the closer the gray level correlation coefficient is between 0 and 1, the more relevant the closer the gray level correlation coefficient is represented, and the more irrelevant the gray level correlation coefficient is represented the closer the gray level correlation coefficient is.
Specifically, the following steps are adopted to obtain transformation parameters of two images:
(1) Initializing a transformation parameter, for example, a translation parameter of (0, 0), a rotation parameter of 0 °, and a scaling parameter of 1;
(2) According to the current transformation parameters, carrying out corresponding spatial transformation on the crystal image to obtain a transformed crystal image;
(3) Calculating the correlation coefficient of the gray values of the transformed crystal image and the analog image to be used as the current similarity;
(4) According to an optimization algorithm, such as a gradient descent method, fine tuning is performed on the transformation parameters to increase the similarity;
(5) Repeating the steps (2) to (4) until the similarity reaches a preset threshold value or the transformation parameter reaches a preset range or the maximum iteration number is reached;
(6) And outputting the final transformation parameters as transformation parameters of the two images.
The image registration sub-module can realize the alignment and comparison of the crystal image and the analog image and provide more visual and objective data for the subsequent crystal growth judgment.
And the crystal growth judging submodule is used for judging whether the crystal growth is consistent with a simulation result according to the similarity and the transformation parameters, and if not, analyzing deviation and reason of the crystal growth to determine the state and abnormality of the crystal growth.
Specifically, the crystal growth judging submodule adopts a crystal growth judging method based on threshold judgment, and the method comprises the following steps:
(1) Calculating errors of crystal growth, namely differences of a crystal image and a simulation image, including shape errors, position errors, direction errors and size errors according to the similarity and the transformation parameters;
(2) Judging whether the crystal growth is consistent with the simulation result or not according to a preset error threshold value, if the error is smaller than the threshold value, considering that the crystal growth is consistent with the simulation result, and if the error is larger than the threshold value, considering that the crystal growth is inconsistent with the simulation result;
(3) The state and abnormality of crystal growth are determined by analyzing the deviation and cause of crystal growth based on the error of crystal growth, and the physical and mathematical models of crystal growth, for example, if the shape error is large, it may be caused by nucleation or dissolution unevenness of the crystal, if the position error is large, it may be caused by diffusion or evaporation instability of the crystal, if the direction error is large, it may be caused by attachment or detachment irregularity of the crystal, and if the size error is large, it may be caused by temperature or pressure inappropriateness of the crystal.
The crystal growth judging submodule can judge and analyze the state and abnormality of crystal growth and provide more timely and effective feedback for subsequent crystal growth regulation.
And the crystal growth regulating submodule is used for timely regulating relevant parameters and measures in the crystal growth process according to the state and the abnormality of the crystal growth.
Specifically, the crystal growth regulating submodule adopts a crystal growth regulating method based on feedback control, and the method comprises the following steps:
(1) Determining a regulation target and a strategy of crystal growth according to the state and abnormality of crystal growth, for example, if the shape error of crystal growth is large, the regulation target is to make the shape of crystal coincide with the simulation result, and the regulation strategy is to increase or decrease the probability of nucleation or dissolution of crystal;
(2) Determining a regulation parameter and a measure of crystal growth according to a regulation target and strategy of crystal growth, and a physical model and a mathematical model of crystal growth, for example, if the regulation strategy is to increase the probability of nucleation of crystals, the regulation parameter is a temperature, and the regulation measure is to decrease the temperature;
(3) And sending control signals to a temperature controller, a pressure controller and a flow controller of the crystal growth equipment according to the adjusting parameters and measures of the crystal growth and an interface of a controller of the crystal growth equipment, and adjusting related parameters in the crystal growth process in real time.
The crystal growth regulating submodule can realize real-time and self-adaptive regulation of crystal growth, and provides more flexible and intelligent guarantee for improving the quality and efficiency of crystal growth.
Example 3:
the embodiment provides a control system for monitoring crystal growth, which specifically implements an image processing module on the basis of embodiment 1, and reconstructs and tracks the morphology and boundary information of crystals in high resolution in real time.
As shown in fig. 3, the image processing module specifically includes the following 3 sub-modules:
the super-resolution network submodule is used for taking the morphology and boundary information of the crystal acquired by the information acquisition module as input according to a pre-trained deep learning model and outputting a high-resolution crystal image.
Specifically, the super-resolution network submodule adopts a super-resolution technology based on a generation countermeasure network (GAN), the technology comprises a generator and a discriminator, the generator is used for up-sampling a low-resolution crystal image into a high-resolution crystal image, the discriminator is used for judging whether the crystal image output by the generator is real, and the generator can generate a more real and clear crystal image through countermeasure training of the generator and the discriminator. The super-resolution network sub-module can improve the resolution and quality of the crystal image and provide more accurate data for subsequent boundary detection and tracking.
The boundary detection network sub-module is used for taking the high-resolution crystal image output by the super-resolution network sub-module as input and outputting a binary image of the crystal boundary according to a pre-trained deep learning model.
Specifically, the boundary detection network submodule adopts a boundary detection technology based on a Convolutional Neural Network (CNN), the technology comprises an encoder and a decoder, the encoder is used for carrying out feature extraction and dimension reduction on a high-resolution crystal image, the decoder is used for carrying out up-sampling and reconstruction on a feature image output by the encoder, and finally, a binary image of a crystal boundary is output, wherein the pixel value of the crystal boundary is 1, and the pixel value of a background is 0. The boundary detection network submodule can realize automatic and accurate detection of the crystal boundary and provide more clear data for subsequent boundary tracking.
And the boundary tracking sub-module is used for calculating parameters of the crystal boundary in real time according to the binary image output by the boundary detection network sub-module, including the position, the length and the area, and comparing the parameters with the parameters of the previous frame to obtain the extension and contraction information of the crystal boundary.
Specifically, the boundary tracking submodule adopts a boundary tracking technology based on contour tracking, and the technology comprises the following steps:
(1) Performing edge detection on the binary image output by the boundary detection network sub-module to obtain an edge point set of the crystal boundary;
(2) Contour extraction is carried out on the edge point set to obtain a contour curve of the crystal boundary;
(3) Parameterizing the contour curve to obtain the position, length and area of the crystal boundary;
(4) And comparing parameters of the crystal boundaries of the current frame and the previous frame to obtain extension and contraction information of the crystal boundaries.
The boundary tracking sub-module can realize real-time and continuous tracking of the crystal boundary and provide more dynamic data for subsequent data analysis.
Example 4:
the present embodiment provides a control system for monitoring crystal growth, which specifically implements a data analysis module on the basis of embodiment 3, so as to improve the accuracy and reliability of calculation and analysis of the growth rate and growth direction of crystals.
As shown in fig. 4, the data analysis module specifically includes the following 5 sub-modules:
and the growth rate calculation sub-module is used for calculating the growth rate of the crystal in different directions according to the extension and contraction information of the crystal boundary output by the boundary tracking sub-module.
Specifically, the growth rate calculation submodule adopts a growth rate calculation method based on boundary change, and the method comprises the following steps:
(1) Determining the growth direction and crystal face orientation of the crystal according to the position and length information of the crystal boundary;
(2) Calculating the boundary variation of the crystal in each growth direction according to the extension and contraction information of the crystal boundary;
(3) The growth rate of the crystal in each growth direction was calculated in μm/s based on the amount of change in the crystal boundary and the image sampling time interval.
The growth rate calculation sub-module can realize real-time and accurate measurement of the crystal growth rate, and provides more effective data for the subsequent control module.
And the growth direction calculation sub-module is used for calculating the growth direction and crystal face orientation of the crystal according to the position and length information of the crystal boundary output by the boundary tracking sub-module.
Specifically, the growth direction calculation submodule adopts a growth direction calculation method based on boundary curvature, and the method comprises the following steps:
(1) Determining the main axis direction and the minor axis direction of the crystal according to the position and the length information of the crystal boundary;
(2) Calculating the curvature radius of the crystal boundary in the main axis direction and the minor axis direction according to the contour curve of the crystal boundary;
(3) And calculating the growth direction and the crystal face orientation of the crystal according to the curvature radius of the crystal boundary, wherein the growth direction is the direction with smaller curvature radius, and the crystal face orientation is the direction with larger curvature radius.
The growth direction calculation sub-module can realize automatic and accurate calculation of the crystal growth direction and crystal face orientation, and provides more critical data for subsequent target comparison and morphology analysis.
And the target comparison submodule is used for comparing the information output by the growth rate calculation submodule and the growth direction calculation submodule with a preset crystal growth target and a preset standard to obtain the deviation and the error of crystal growth.
Specifically, the target comparison submodule adopts a target comparison method based on error analysis, and the method comprises the following steps:
(1) Determining expected values of crystal growth, including expected growth rate, growth direction and crystal plane orientation, according to preset crystal growth targets and criteria;
(2) Determining an actual value of crystal growth according to information output by the growth rate calculation sub-module and the growth direction calculation sub-module, wherein the actual value comprises an actual growth rate, a growth direction and a crystal face orientation;
(3) And calculating deviation and error of crystal growth according to the expected value and the actual value, wherein the deviation and error comprises deviation of growth rate, deviation of growth direction and deviation of crystal face orientation.
The target comparison sub-module can realize the target and actual comparison of the crystal growth and provide more definite guidance for the subsequent control module.
The morphology analysis submodule is used for analyzing morphology change and characteristics including the size, shape, surface roughness and defects of the crystal in the crystal growth process according to the morphology and boundary information of the crystal in the image processing module.
Specifically, the morphology analysis submodule adopts a morphology analysis method based on image characteristics, and the method comprises the following steps:
(1) Calculating the size of the crystal according to the position and length information of the crystal boundary, wherein the size comprises the length of the long axis, the length of the short axis and the area of the crystal;
(2) Calculating the shape of the crystal according to the contour curve of the crystal boundary, wherein the shape comprises roundness, ellipticity and rectangularity of the crystal;
(3) Calculating the surface roughness of the crystal according to the curvature radius of the crystal boundary, wherein the surface roughness comprises the average curvature, the maximum curvature and the minimum curvature of the crystal;
(4) And detecting defects of the crystal, including cracks, holes and impurities of the crystal, according to the edge point set of the crystal boundary.
The morphology analysis submodule can realize comprehensive and detailed analysis of morphology change and characteristics in the crystal growth process, and provides more abundant data for subsequent growth mechanism analysis.
The growth mechanism analysis submodule is used for analyzing the growth mechanism and influencing factors in the crystal growth process according to the information output by the morphology analysis submodule and the types and structures of crystals, including nucleation, diffusion, dissolution, adhesion and evaporation of the crystals.
Specifically, the growth mechanism analysis submodule adopts a growth mechanism analysis method based on a physical model, and the method comprises the following steps:
(1) Determining physical properties of the crystal according to the type and structure of the crystal, including density, melting point, thermal conductivity, surface tension and lattice constant of the crystal;
(2) Establishing a physical model of crystal growth according to the physical properties of the crystal, the temperature, the pressure and the flow of reaction gas in crystal growth equipment, wherein the physical model comprises thermodynamic and kinetic equations of crystal growth;
(3) And analyzing a growth mechanism and influencing factors in the crystal growth process according to the physical model of crystal growth and information output by the morphology analysis submodule, wherein the factors comprise nucleation, diffusion, dissolution, adhesion and evaporation of crystals.
The growth mechanism analysis submodule can realize deep and scientific analysis of growth mechanisms and influence factors in the crystal growth process, and provides more theoretical support for subsequent crystal growth simulation and monitoring.
Example 5:
the embodiment provides a control system for monitoring crystal growth, which specifically implements a control module on the basis of embodiment 1, so as to improve the efficiency and flexibility of real-time adjustment and optimization of relevant parameters in the crystal growth process.
As shown in fig. 5, the control module specifically includes the following 4 sub-modules:
the fuzzy control rule base establishing submodule is used for establishing a fuzzy control rule base of the relevant parameters of the crystal growth according to the characteristics of the crystal growth, and the fuzzy control rule base comprises a definition domain, a value domain, a membership function and a fuzzy control rule of fuzzy control variables.
Specifically, the fuzzy control rule base building sub-module builds the fuzzy control rule base by adopting the following steps:
(1) According to the characteristics of crystal growth, determining fuzzy control variables of relevant parameters of crystal growth, wherein the input variables comprise deviations and errors of crystal growth, including deviations of growth rate, deviations of growth direction and deviations of crystal face orientation, and the output variables comprise relevant parameters of the crystal growth process, including temperature, pressure and reaction gas flow;
(2) Determining the definition domain and the value domain of the fuzzy control variable according to the value range of the related parameters of the crystal growth;
(3) Determining membership functions of fuzzy control variables, for example, membership functions of deviations of growth rates are triangular functions, divided into five fuzzy subsets, namely negative large (NB), negative Small (NS), zero (ZE), positive Small (PS) and positive large (PB), according to characteristics of the crystal growth related parameters;
(4) The fuzzy control rule is determined based on the rule and experience of crystal growth, for example, if the deviation of the growth rate is negative, the temperature should be increased, the pressure should be decreased, and the reaction gas flow should be increased.
The fuzzy control rule base establishment submodule can realize fuzzification and regularization of relevant parameters of crystal growth, and provides more flexible and adaptive data for subsequent fuzzy reasoning and inversion.
And the fuzzy inference sub-module is used for obtaining the fuzzy control quantity of the output related parameters according to the input analysis result, the preset target and standard and the fuzzy control rule base by using a fuzzy inference method.
Specifically, the fuzzy inference sub-module adopts a fuzzy inference method based on a maximum and minimum method, and the method comprises the following steps:
(1) Calculating the membership of the input variable on each fuzzy subset according to the input analysis result, namely the deviation and error of the crystal growth and the membership function of the fuzzy control variable;
(2) According to the fuzzy control rule base and the membership degree of the input variable on each fuzzy subset, calculating the activation degree of each fuzzy control rule, namely the minimum value of the membership degree of the front part and the back part of the rule;
(3) Calculating the membership of the output variable on each fuzzy subset according to the activation degree of each fuzzy control rule and the membership function of the output variable, namely the minimum value of the membership of the back part of the rule and the activation degree of the rule;
(4) And calculating the fuzzy control quantity of the output variable, namely the central value of each fuzzy subset and the weighted average value of the membership degree, according to the membership degree of the output variable on each fuzzy subset and the value range of the output variable.
The fuzzy inference sub-module can realize fuzzy control of the related parameters of the crystal growth and provide more reasonable and optimized data for the subsequent fuzzy inversion.
And the fuzzy inversion sub-module is used for obtaining the accurate control quantity of the output related parameters according to the fuzzy control quantity of the output related parameters by using a fuzzy inversion method.
Specifically, the fuzzy inversion submodule adopts a fuzzy inversion method based on an optimization method, and the method comprises the following steps:
(1) According to the fuzzy control quantity of the output related parameter and the membership function of the fuzzy control variable, establishing a fuzzy inversion model of the output variable, namely a nonlinear objective function, wherein the objective is to minimize the square sum of the difference value between the fuzzy control quantity of the output variable and the accurate control quantity of the output variable;
(2) According to the fuzzy inversion model of the output variable and the value range of the output variable, solving the accurate control quantity of the output variable by utilizing an optimization algorithm, for example, the accurate control quantity of the temperature can be solved by a gradient descent method or a Newton method and the like;
(3) And performing amplitude limiting processing on the output variable according to the accurate control quantity of the output variable and the value range of the output variable, namely setting the accurate control quantity of the output variable as the maximum value or the minimum value of the output variable if the accurate control quantity of the output variable exceeds the value range of the output variable.
The fuzzy inversion sub-module can realize accurate control of the parameters related to the crystal growth and provide finer and reliable data for subsequent parameter adjustment.
And the parameter adjusting sub-module is used for sending control signals to a temperature controller, a pressure controller and a flow controller of the crystal growth equipment according to the output accurate control quantity of the related parameters and adjusting the related parameters in the crystal growth process in real time.
Specifically, the parameter adjustment sub-module adopts a parameter adjustment method based on proportional-integral-derivative (PID), and the method comprises the following steps:
(1) Calculating the deviation of the relevant parameter, namely the difference between the expected value and the actual value, according to the output accurate control quantity of the relevant parameter and the real-time measured value of the relevant parameter in the crystal growth equipment;
(2) Calculating the control quantity of the relevant parameters, namely the magnitude of the control signal, according to the deviation of the relevant parameters and preset proportional coefficient, integral coefficient and differential coefficient;
(3) And sending control signals to a temperature controller, a pressure controller and a flow controller of the crystal growth equipment according to the control quantity of the related parameters and an interface of a controller of the crystal growth equipment, and adjusting the related parameters in the crystal growth process in real time.
The parameter adjusting submodule can realize real-time and accurate adjustment of the related parameters of crystal growth, and provides more effective and stable guarantee for improving the quality and efficiency of crystal growth.
Example 6:
the present embodiment provides a control method for monitoring crystal growth, the flow chart of which is shown in fig. 6, comprising the following steps:
s1, performing in-situ imaging on the crystal by using an optical microscope, and acquiring morphology and boundary information of the crystal, wherein the step is used for providing original image data for subsequent image processing and data analysis and observing real-time change of the crystal.
S2, based on the morphology and boundary information of the crystal, tracking the extension and contraction information of the boundary of the crystal in real time according to the super-resolution technology, wherein the step is used for improving the resolution and definition of the image and acquiring the dynamic information of the boundary of the crystal so as to calculate the growth rate and the growth direction of the crystal.
S3, calculating the growth rate and the growth direction of the crystal according to the morphology and boundary information of the crystal and the extension and contraction information of the crystal boundary, comparing the growth rate and the growth direction with preset crystal growth targets and standards, analyzing morphology change and growth mechanism in the crystal growth process, and evaluating the quality and the efficiency of crystal growth and exploring the principle and influencing factors of crystal growth.
S4, according to the analysis result in the S3 and a preset crystal growth target and standard, adjusting relevant parameters in the crystal growth process in real time, wherein the relevant parameters comprise temperature, pressure and reaction gas flow, and the step is used for optimizing and adjusting the crystal growth condition according to the actual condition of crystal growth so as to improve the stability and controllability of crystal growth.
S5, simulating the process and result of crystal growth by utilizing a numerical simulation technology according to the regulated related parameters and the type and structure of the crystal, so as to predict the morphology and boundary information of the crystal, wherein the step is used for simulating and predicting the process and result of crystal growth according to a theoretical model of crystal growth, so as to verify the correctness and feasibility of crystal growth.
S6, re-acquiring morphology and boundary information of the crystal after the related parameters are regulated, monitoring the state and abnormality of the crystal growth in real time according to the re-acquired morphology and boundary information of the crystal and the simulation result in S5, and timely regulating related parameters and measures in the crystal growth process, wherein the step is used for monitoring and judging the state and abnormality of the crystal growth and feeding back and regulating the parameters and measures of the crystal growth according to the actual morphology and boundary information of the crystal and the simulated expected morphology and boundary information.
The embodiment provides a control method for monitoring crystal growth, which utilizes means such as an optical microscope, a super-resolution technology, a numerical simulation technology and the like to efficiently acquire, process and analyze morphology and boundary information of crystals, so as to realize accurate calculation of growth rate and growth direction of the crystals, and effective evaluation of targets and standards of crystal growth, analyze morphology change and growth mechanism in the crystal growth process, and simultaneously regulate relevant parameters in the crystal growth process in real time according to the state and abnormality of the crystal growth to improve the quality and efficiency of the crystal growth.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. The principles and embodiments of the present invention are described herein by applying specific examples, and the above examples are only used to help understand the method and core idea of the present invention. The foregoing is merely illustrative of the preferred embodiments of this invention, and it is noted that there is objectively no limit to the specific structure disclosed herein, since numerous modifications, adaptations and variations can be made by those skilled in the art without departing from the principles of the invention, and the above-described features can be combined in any suitable manner; such modifications, variations and combinations, or the direct application of the inventive concepts and aspects to other applications without modification, are contemplated as falling within the scope of the present invention.
Claims (9)
1. A control system for monitoring crystal growth, comprising:
the information acquisition module is used for carrying out in-situ imaging on the crystal in the crystal growth equipment by utilizing an optical microscope to acquire morphology and boundary information of the crystal;
the image processing module is used for receiving the morphology and boundary information of the crystal acquired by the information acquisition module and tracking the extension and contraction information of the boundary of the crystal in real time according to the super resolution technology;
the data analysis module is used for calculating the growth rate and the growth direction of the crystal according to the information output by the image processing module, comparing the growth rate and the growth direction with preset crystal growth targets and standards and analyzing the morphology change and the growth mechanism in the crystal growth process;
the control module is used for sending control signals to crystal growth equipment according to the analysis result output by the data analysis module and preset crystal growth targets and standards, and adjusting related parameters in the crystal growth process in real time, wherein the related parameters comprise temperature, pressure and reaction gas flow;
and the crystal growth equipment is used for controlling the temperature, the pressure and the flow of the reaction gas in the crystal growth process according to the control signal sent by the control module.
2. The control system for monitoring crystal growth according to claim 1, wherein the system further comprises:
the crystal growth simulation module is used for simulating the process and result of crystal growth by utilizing a numerical simulation technology according to the regulated relevant parameters in the crystal growth equipment and the types and structures of the crystals, so as to predict the morphology and boundary information of the crystals;
the crystal growth monitoring module is used for monitoring the state and abnormality of crystal growth in real time according to the morphology and boundary information of the crystal acquired by the information acquisition module, the morphology and boundary information of the crystal are acquired again after the relevant parameters are regulated, and the simulation result output by the crystal growth simulation module is used for timely adjusting the relevant parameters and measures in the crystal growth process.
3. The control system for monitoring crystal growth according to claim 1, wherein the image processing module specifically comprises:
the super-resolution network submodule is used for taking the morphology and boundary information of the crystal acquired by the information acquisition module as input according to a pre-trained deep learning model and outputting a high-resolution crystal image;
the boundary detection network submodule is used for taking the high-resolution crystal image output by the super-resolution network submodule as input and outputting a binary image of a crystal boundary according to a pre-trained deep learning model;
And the boundary tracking sub-module is used for calculating parameters of the crystal boundary in real time according to the binary image output by the boundary detection network sub-module, including the position, the length and the area, and comparing the parameters with the parameters of the previous frame to obtain the extension and contraction information of the crystal boundary.
4. A control system for monitoring crystal growth according to claim 3, wherein the data analysis module comprises:
the growth rate calculation sub-module is used for calculating the growth rate of the crystal in different directions according to the extension and contraction information of the crystal boundary output by the boundary tracking sub-module;
the growth direction calculation sub-module is used for calculating the growth direction and crystal face orientation of the crystal according to the position and length information of the crystal boundary output by the boundary tracking sub-module;
the target comparison submodule is used for comparing information output by the growth rate calculation submodule and the growth direction calculation submodule with a preset crystal growth target and a preset standard to obtain deviation and error of crystal growth;
the morphology analysis submodule is used for analyzing morphology change and characteristics including the size, shape, surface roughness and defects of the crystal in the crystal growth process according to the morphology and boundary information of the crystal in the image processing module;
The growth mechanism analysis submodule is used for analyzing the growth mechanism and influencing factors in the crystal growth process according to the information output by the morphology analysis submodule and the types and structures of crystals, including nucleation, diffusion, dissolution, adhesion and evaporation of the crystals.
5. The control system for monitoring crystal growth according to claim 1, wherein the control module specifically comprises:
the fuzzy control rule base establishing submodule is used for establishing a fuzzy control rule base of the relevant parameters of the crystal growth according to the characteristics of the crystal growth, and comprises a definition domain, a value domain, a membership function and a fuzzy control rule of fuzzy control variables;
the fuzzy inference sub-module is used for obtaining the fuzzy control quantity of the output related parameters according to the input analysis result, the preset target and standard and the fuzzy control rule base by using a fuzzy inference method;
the fuzzy inversion sub-module is used for obtaining the accurate control quantity of the output related parameters according to the fuzzy control quantity of the output related parameters by using a fuzzy inversion method;
and the parameter adjusting sub-module is used for sending control signals to a temperature controller, a pressure controller and a flow controller of the crystal growth equipment according to the output accurate control quantity of the related parameters and adjusting the related parameters in the crystal growth process in real time.
6. The control system for monitoring crystal growth according to claim 2, wherein the crystal growth simulation module employs a numerical simulation technique based on a finite element method.
7. The control system for monitoring crystal growth according to claim 2, wherein the crystal growth monitoring module specifically comprises:
the image registration sub-module is used for obtaining a crystal image according to the morphology and boundary information of the crystal obtained by the information obtaining module, the morphology and boundary information of the crystal are re-obtained after the related parameters are adjusted, a simulation image is obtained according to a simulation result output by the crystal growth simulation module, and the crystal image and the simulation image are subjected to image registration to obtain the similarity and transformation parameters of the two images;
the crystal growth judging submodule is used for judging whether the crystal growth is consistent with a simulation result according to the similarity and the transformation parameters, and if not, analyzing deviation and reason of the crystal growth and determining the state and abnormality of the crystal growth;
and the crystal growth regulating submodule is used for timely regulating relevant parameters and measures in the crystal growth process according to the state and the abnormality of the crystal growth.
8. The control system for monitoring crystal growth according to claim 7, wherein the image registration submodule calculates the similarity of two images by using an image registration method based on gray correlation, and the following formula is adopted:
Wherein S represents the similarity of two images, I 1 And I 2 Gray values representing a crystal image and an analog image, respectively, i and j representing the imagesIs defined in the image data.
9. A control method for monitoring crystal growth, comprising the steps of:
s1, performing in-situ imaging on a crystal by using an optical microscope to obtain morphology and boundary information of the crystal;
s2, tracking extension and contraction information of a crystal boundary in real time based on morphology and boundary information of the crystal according to a super-resolution technology;
s3, calculating the growth rate and the growth direction of the crystal according to the morphology and boundary information of the crystal and the extension and contraction information of the crystal boundary, comparing the growth rate and the growth direction with a preset crystal growth target and standard, and analyzing morphology change and growth mechanism in the crystal growth process;
s4, adjusting relevant parameters in the crystal growth process in real time according to the analysis result in the S3 and a preset crystal growth target and standard, wherein the relevant parameters comprise temperature, pressure and reaction gas flow;
s5, simulating the process and result of crystal growth by utilizing a numerical simulation technology according to the regulated related parameters and the types and structures of the crystals, so as to predict the morphology and boundary information of the crystals;
S6, re-acquiring morphology and boundary information of the crystal after the related parameters are regulated, and monitoring the state and abnormality of the crystal growth in real time according to the re-acquired morphology and boundary information of the crystal and the simulation result in S5, and timely regulating the related parameters and measures in the crystal growth process.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108754599A (en) * | 2018-05-31 | 2018-11-06 | 西安理工大学 | A kind of silicon monocrystal growth temprature control method based on finite element numerical simulation |
| US20200291541A1 (en) * | 2019-03-11 | 2020-09-17 | Zing Semiconductor Corporation | Method, device, system, and computer storage medium for crystal growing control |
| CN111754516A (en) * | 2020-05-25 | 2020-10-09 | 沈阳工程学院 | Intelligent control method for rutile single crystal growth based on computer vision feedback |
-
2023
- 2023-12-08 CN CN202311679377.XA patent/CN117646272B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108754599A (en) * | 2018-05-31 | 2018-11-06 | 西安理工大学 | A kind of silicon monocrystal growth temprature control method based on finite element numerical simulation |
| US20200291541A1 (en) * | 2019-03-11 | 2020-09-17 | Zing Semiconductor Corporation | Method, device, system, and computer storage medium for crystal growing control |
| CN111754516A (en) * | 2020-05-25 | 2020-10-09 | 沈阳工程学院 | Intelligent control method for rutile single crystal growth based on computer vision feedback |
Non-Patent Citations (1)
| Title |
|---|
| 段连飞等: "无人机载SAR图像信息提取技术", vol. 2016, 30 April 2016, 西北工业大学出版社, pages: 51 * |
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