Polarization beam splitter parameter tuning method and system based on micro-nano grating

Abstract

The invention relates to the technical field of micro-nano optics, in particular to a polarization beam splitter parameter tuning method and system based on a micro-nano grating, and the method comprises the steps: obtaining test optical characteristic parameters of a polarization beam splitter to be evaluated, and judging whether the parameter tuning needs to be carried out on the polarization beam splitter to be evaluated or not according to the test optical characteristic parameters and preset optical characteristic parameters; if parameter tuning needs to be carried out on the to-be-evaluated polarization beam splitter, to-be-tuned optical characteristic parameters of the to-be-tuned polarization beam splitter are acquired; determining singular structure characteristic parameters of the polarization beam splitter needing parameter tuning according to the optical characteristic parameters to be tuned; and carrying out optimization processing on the singular structure characteristic parameters of the polarization beam splitter needing parameter tuning. According to the invention, the parameter tuning efficiency of the polarization beam splitter is effectively improved, the structural factors influencing the performance are accurately positioned, and finally the optical performance of the polarization beam splitter is ensured to meet the preset requirements.

Description

Technical Field

[0001] The present invention relates to the field of micro-nano optical technology, and in particular to a method and system for tuning parameters of a polarization beam splitter based on a micro-nano grating. Background Art

[0002] With the development of miniaturization and integration of optical devices, polarization beam splitters based on micro-nano gratings have been widely used in optical communications, optical sensing, biomedical imaging and other fields due to their advantages of small size, light weight and easy integration. However, the polarization beam splitting performance of micro-nano gratings is significantly affected by its structural parameters (such as grating period, depth, duty cycle, etc.), and slight changes in these parameters will lead to significant differences in polarization beam splitting performance. Therefore, how to quickly and accurately tune the structural parameters of micro-nano grating polarization beam splitters to meet the polarization beam splitting performance requirements in specific application scenarios has become a key issue to be solved. Traditional polarization beam splitter parameter tuning methods mainly rely on numerical simulation methods such as finite element analysis and time-domain finite difference, which require a lot of computing resources and time, and the tuning process is complicated and inefficient. In addition, these methods usually require pre-setting the target performance and approaching the target performance by repeatedly iteratively adjusting the structural parameters, which is easy to fall into the local optimal solution and difficult to obtain the global optimal solution. In view of this, the present invention proposes a method and system for tuning the parameters of a polarization beam splitter based on micro-nano gratings. Summary of the invention

[0003] The present invention overcomes the deficiencies of the prior art and provides a method and system for tuning parameters of a polarization beam splitter based on a micro-nano grating.

[0004] To achieve the above-mentioned purpose, the technical solution adopted by the present invention is:

[0005] The present invention discloses a method for tuning parameters of a polarization beam splitter based on a micro-nano grating, comprising the following steps:

[0006] Obtaining standard structural characteristic parameters corresponding to various types of polarization beam splitters, and constructing a Huffman search tree model library according to the standard structural characteristic parameters corresponding to various types of polarization beam splitters;

[0007] Obtaining a structural model diagram of the polarization beam splitter to be evaluated, importing the structural model diagram of the polarization beam splitter to be evaluated into a Huffman search tree model library for search and matching, and obtaining preset optical characteristic parameters of the polarization beam splitter to be evaluated;

[0008] Obtaining test optical characteristic parameters of the polarization beam splitter to be evaluated, and determining whether parameter tuning of the polarization beam splitter to be evaluated is required according to the test optical characteristic parameters and preset optical characteristic parameters;

[0009] If it is necessary to perform parameter tuning on the polarization beam splitter to be evaluated, the optical characteristic parameters to be tuned of the polarization beam splitter to be tuned are obtained; and the singular structural characteristic parameters of the polarization beam splitter to be tuned are determined according to the optical characteristic parameters to be tuned;

[0010] The singular structural characteristic parameters of the polarization beam splitter that needs parameter tuning are optimized so that the optical performance of the polarization beam splitter that needs parameter tuning meets the preset requirements.

[0011] Preferably, standard structural characteristic parameters corresponding to various types of polarization beam splitters are obtained, and a Huffman search tree model library is constructed according to the standard structural characteristic parameters corresponding to various types of polarization beam splitters, specifically:

[0012] Obtaining standard structural characteristic parameters corresponding to various types of polarization beam splitters, and constructing characteristic model diagrams corresponding to various types of polarization beam splitters according to the corresponding standard structural characteristic parameters; wherein the standard structural characteristic parameters include grating shape, grating width, grating spacing, and grating period;

[0013] And obtaining preset optical characteristic parameters corresponding to various types of polarization beam splitters; wherein the preset optical characteristic parameters include polarization beam splitting efficiency, extinction ratio, bandwidth, incident angle range, polarization state purity, transmittance, reflectivity, angular resolution and polarization beam splitting angle;

[0014] Constructing a Huffman tree, and recursively dividing a corresponding number of subtrees in the Huffman tree according to various types of polarization beam splitters;

[0015] Encoding preset optical characteristic parameters corresponding to various types of polarization beam splitters to assign a string of digital codes to the preset optical characteristic parameters corresponding to various types of polarization beam splitters;

[0016] The digital codes corresponding to various types of polarization beam splitters are engraved on the corresponding subtrees, and the characteristic model graphs corresponding to various types of polarization beam splitters are respectively stored on the corresponding subtrees to obtain a Huffman search tree model library.

[0017] Preferably, a structural model diagram of the polarization beam splitter to be evaluated is obtained, and the structural model diagram of the polarization beam splitter to be evaluated is imported into a Huffman search tree model library for search and matching, so as to obtain preset optical characteristic parameters of the polarization beam splitter to be evaluated, specifically:

[0018] Acquire laser point cloud data of the polarization beam splitter to be evaluated by a laser scanning device, and construct a structural model diagram of the polarization beam splitter to be evaluated according to the laser point cloud data;

[0019] Extracting the characteristic model graphs in each subtree from the Huffman search tree model library, introducing a bounding box algorithm, and calculating the degree of intersection between the structural model graph of the polarization beam splitter to be evaluated and the characteristic model graphs in each subtree based on the bounding box algorithm;

[0020] Extract the highest degree of intersection between the structural model graph of the polarization beam splitter to be evaluated and the characteristic model graphs in each subtree, and obtain the characteristic model graph to which the highest degree of intersection belongs;

[0021] The subtree corresponding to the characteristic model graph to which the highest intersection degree belongs is identified, and the digital code of the identified subtree is obtained, and the digital code of the identified subtree is interpreted to obtain the preset optical characteristic parameters of the polarization beam splitter to be evaluated.

[0022] Preferably, the test optical characteristic parameters of the polarization beam splitter to be evaluated are obtained, and it is determined whether the polarization beam splitter to be evaluated needs to be parameter tuned according to the test optical characteristic parameters and the preset optical characteristic parameters, specifically:

[0023] Performing polarization optical testing on the polarization beam splitter to be evaluated based on an optical testing device to obtain test optical characteristic parameters of the polarization beam splitter to be evaluated;

[0024] Acquiring precision performance requirement information of the polarization beam splitter to be evaluated, and determining parameter deviation value thresholds of various optical characteristic parameters of the polarization beam splitter to be evaluated according to the precision performance requirement information;

[0025] Calculating actual parameter differences between various tested optical characteristic parameters of the polarization beam splitter to be evaluated and preset optical characteristic parameters;

[0026] Determine whether one or more actual parameter differences in the polarization beam splitter to be evaluated are greater than a corresponding parameter deviation value threshold;

[0027] If one or more actual parameter differences in the polarization beam splitter to be evaluated are greater than the corresponding parameter deviation threshold, the polarization beam splitter to be evaluated is determined to be a polarization beam splitter that needs parameter tuning;

[0028] If there is no situation in the polarization beam splitter to be evaluated where the actual parameter difference is greater than the corresponding parameter deviation value threshold, the polarization beam splitter to be evaluated is determined as a polarization beam splitter that does not require parameter tuning;

[0029] The tested optical characteristic parameters include polarization splitting efficiency, extinction ratio, bandwidth, incident angle range, polarization state purity, transmittance, reflectivity, angular resolution and polarization splitting angle.

[0030] Preferably, if it is necessary to perform parameter tuning on the polarization beam splitter to be evaluated, the optical characteristic parameters to be tuned of the polarization beam splitter to be parameter tuned are obtained, specifically:

[0031] If the polarization beam splitter to be evaluated is determined to be a polarization beam splitter that requires parameter tuning, the optical characteristic parameters corresponding to the actual parameter difference values ​​that are greater than the corresponding parameter deviation value threshold are calibrated as the optical characteristic parameters to be tuned, thereby obtaining the optical characteristic parameters to be tuned of the polarization beam splitter that requires parameter tuning.

[0032] Preferably, the singular structural characteristic parameters of the polarization beam splitter that need to be parameter-tuned are determined according to the optical characteristic parameters to be tuned, specifically:

[0033] Obtaining functional specification information of the polarization beam splitter that needs parameter tuning, and obtaining the degree of linear influence of each structural characteristic parameter on each optical characteristic parameter in the polarization beam splitter that needs parameter tuning according to the functional specification information;

[0034] Each structural characteristic parameter is used as a quantitative node, and each optical characteristic parameter is used as a variable node; and the topological distance between each quantitative node and each variable node is determined according to the linear influence degree between each structural characteristic parameter and each optical characteristic parameter; wherein, the greater the linear influence degree of the structural characteristic parameter on the optical characteristic parameter, the smaller the corresponding topological distance;

[0035] Topologically connect each quantitative node with each variable node according to the linear distance between each quantitative node and each variable node, and obtain a topological structure diagram between each structural characteristic parameter and each optical characteristic parameter in the polarization beam splitter that needs parameter tuning;

[0036] Obtaining optical characteristic parameters to be tuned of the polarization beam splitter that needs parameter tuning, and retrieving a variable node corresponding to the optical characteristic parameters to be tuned in the topological structure diagram, and defining the node as a target variable node;

[0037] Obtaining the topological distance between the target variable node and the quantitative node in the topological structure diagram, and marking the quantitative node corresponding to the topological distance not greater than the preset distance threshold as the target quantitative node;

[0038] The structural characteristic parameters corresponding to the target quantitative nodes are obtained, and the singular structural characteristic parameters of the polarization beam splitter that need to be parameter tuned are obtained.

[0039] Preferably, the singular structural characteristic parameters of the polarization beam splitter that needs parameter tuning are optimized, specifically:

[0040] Obtaining a structural model diagram of a polarization beam splitter that needs parameter tuning, performing format conversion processing on the structural model diagram of the polarization beam splitter that needs parameter tuning, obtaining a finite element analysis model of the polarization beam splitter that needs parameter tuning, and importing the finite element analysis model into finite element analysis software;

[0041] Determine key variables of the finite element analysis model according to the singular structural characteristic parameters of the polarization beam splitter to be tuned, and set the excitation source parameters in the finite element analysis software;

[0042] Acquire a preset process range of the characteristic parameter of the singular structure, define an upper boundary condition and a lower boundary condition of the characteristic parameter of the singular structure according to the preset process range, and discretize a plurality of discrete parameter values ​​of the characteristic parameter of the singular structure according to the upper boundary condition and the lower boundary condition;

[0043] Replacing corresponding singular structural characteristic parameters in the finite element analysis model based on respective discrete parameter values, and performing polarization optical simulation test processing on the finite element analysis model after the parameter replacement to obtain simulated optical characteristic parameters of the finite element analysis model;

[0044] Calculating the Pearson correlation coefficient value between the simulated optical characteristic parameter and the preset optical characteristic parameter, and if the Pearson correlation coefficient value is not greater than the preset value, performing the next discrete parameter value replacement test operation, and continuously iterating this process until the obtained Pearson correlation coefficient value is greater than the preset value;

[0045] When the obtained Pearson correlation coefficient value is greater than the preset value, the discrete parameter value corresponding to the corresponding replacement test operation is used as the tuning parameter value of the singular structure characteristic parameter;

[0046] The polarization beam splitter that needs parameter tuning is tuned based on the tuning parameter value.

[0047] The present invention also discloses a polarization beam splitter parameter tuning system based on micro-nano gratings, wherein the polarization beam splitter parameter tuning system comprises a memory and a processor, wherein a polarization beam splitter parameter tuning method program is stored in the memory, and when the polarization beam splitter parameter tuning method program is executed by the processor, any one of the steps of the polarization beam splitter parameter tuning method is implemented.

[0048] The present invention solves the technical defects existing in the background technology, and has the following beneficial effects: obtaining standard structural characteristic parameters corresponding to various types of polarization beam splitters, and constructing a Huffman search tree model library according to the standard structural characteristic parameters corresponding to various types of polarization beam splitters; obtaining a structural model diagram of the polarization beam splitter to be evaluated, importing the structural model diagram of the polarization beam splitter to be evaluated into the Huffman search tree model library for search and matching, and obtaining preset optical characteristic parameters of the polarization beam splitter to be evaluated; obtaining test optical characteristic parameters of the polarization beam splitter to be evaluated, and judging whether it is necessary to perform parameter tuning on the polarization beam splitter to be evaluated according to the test optical characteristic parameters and the preset optical characteristic parameters; if it is necessary to perform parameter tuning on the polarization beam splitter to be evaluated, obtaining the optical characteristic parameters to be tuned of the polarization beam splitter to be tuned; determining the singular structural characteristic parameters of the polarization beam splitter to be tuned according to the optical characteristic parameters to be tuned; optimizing the singular structural characteristic parameters of the polarization beam splitter to be tuned, so that the optical performance of the polarization beam splitter to be tuned meets the preset requirements. The present invention effectively improves the efficiency of polarization beam splitter parameter tuning, accurately locates structural factors that affect performance, and ultimately ensures that the optical performance of the polarization beam splitter meets preset requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0050] Figure 1 is the overall method flow chart of the polarization beam splitter parameter tuning method;

[0051] Figure 2 This is a partial flow chart of the method for tuning parameters of the polarization beam splitter;

[0052] Figure 3 This is the system block diagram of the polarization beam splitter parameter tuning system. DETAILED DESCRIPTION

[0053] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0054] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0055] The present invention discloses a method for tuning parameters of a polarization beam splitter based on a micro-nano grating, such as Figure 1 As shown, the following steps are included:

[0056] S102: acquiring standard structural characteristic parameters corresponding to various types of polarization beam splitters, and constructing a Huffman search tree model library according to the standard structural characteristic parameters corresponding to various types of polarization beam splitters;

[0057] S104: obtaining a structural model diagram of the polarization beam splitter to be evaluated, importing the structural model diagram of the polarization beam splitter to be evaluated into a Huffman search tree model library for search and matching, and obtaining preset optical characteristic parameters of the polarization beam splitter to be evaluated;

[0058] S106: Acquire test optical characteristic parameters of the polarization beam splitter to be evaluated, and determine whether parameter tuning of the polarization beam splitter to be evaluated is required according to the test optical characteristic parameters and preset optical characteristic parameters;

[0059] S108: If it is necessary to perform parameter tuning on the polarization beam splitter to be evaluated, obtain the optical characteristic parameters to be tuned of the polarization beam splitter to be parameter tuned; and determine the singular structural characteristic parameters of the polarization beam splitter to be parameter tuned according to the optical characteristic parameters to be tuned;

[0060] S110: Optimizing the singular structural characteristic parameters of the polarization beam splitter that needs to be parameter-tuned, so that the optical performance of the polarization beam splitter that needs to be parameter-tuned meets preset requirements.

[0061] It should be noted that, first, the standard structural characteristic parameters of various types of polarization beam splitters are obtained, where the structural characteristic parameters include key factors such as grating shape, grating width, grating spacing, and grating period. These parameters are the basic description of the structure of the polarization beam splitter. These standard structural characteristic parameters corresponding to different types of polarization beam splitters are constructed into a Huffman search tree model library. The Huffman search tree has efficient search characteristics and can quickly locate and match relevant information. For the polarization beam splitter to be evaluated, its structural model diagram is obtained and imported into the constructed Huffman search tree model library for search and matching. In this way, the preset optical characteristic parameters of the polarization beam splitter to be evaluated can be obtained, and these optical characteristic parameters include polarization splitting efficiency, extinction ratio, bandwidth, incident angle range, polarization state purity, transmittance, reflectivity, angular resolution, and polarization splitting angle. This step is to use the existing model library information to make a preliminary characteristic prediction of the new polarization beam splitter. Then obtain the test optical characteristic parameters of the polarization beam splitter to be evaluated and compare them with the preset optical characteristic parameters obtained previously. Due to factors such as actual manufacturing and use environment, the tested optical characteristic parameters may be different from the preset ones. By comparing these two sets of parameters, it can be determined whether the polarization beam splitter to be evaluated needs to be parameter tuned. If parameter tuning is required, the optical characteristic parameters to be tuned of the polarization beam splitter to be parameter tuned are obtained. Then, based on these optical characteristic parameters to be tuned, the singular structural characteristic parameters of the polarization beam splitter to be parameter tuned are determined. These singular structural characteristic parameters are the key structural factors that affect the failure of the polarization beam splitter's optical performance to meet the standards. Finally, these singular structural characteristic parameters are optimized to ensure that the optical performance of the polarization beam splitter to be parameter tuned meets the preset requirements, thereby ensuring that the performance of the polarization beam splitter in actual applications meets expectations.

[0062] In summary, this polarization beam splitter parameter tuning method based on micro-nano gratings can quickly obtain the preset optical characteristic parameters of the polarization beam splitter to be evaluated by constructing a Huffman search tree model library, and judge whether to tune by comparing with the test optical characteristic parameters, and further determine and optimize the singular structure characteristic parameters, which effectively improves the efficiency of polarization beam splitter parameter tuning, accurately locates the structural factors that affect the performance, and ultimately ensures that the optical performance of the polarization beam splitter meets the preset requirements, providing an efficient and accurate solution for the design, manufacturing and performance optimization of micro-nano grating polarization beam splitters.

[0063] Preferably, standard structural characteristic parameters corresponding to various types of polarization beam splitters are obtained, and a Huffman search tree model library is constructed according to the standard structural characteristic parameters corresponding to various types of polarization beam splitters, such as Figure 2 As shown, specifically:

[0064] S202: Obtaining standard structural characteristic parameters corresponding to various types of polarization beam splitters, and constructing characteristic model diagrams corresponding to various types of polarization beam splitters according to the corresponding standard structural characteristic parameters; wherein the standard structural characteristic parameters include grating shape, grating width, grating spacing, and grating period;

[0065] S204: and obtaining preset optical characteristic parameters corresponding to various types of polarization beam splitters; wherein the preset optical characteristic parameters include polarization beam splitting efficiency, extinction ratio, bandwidth, incident angle range, polarization state purity, transmittance, reflectivity, angular resolution and polarization beam splitting angle;

[0066] S206: constructing a Huffman tree, and recursively dividing a corresponding number of subtrees in the Huffman tree according to various types of polarization beam splitters;

[0067] S208: Encoding preset optical characteristic parameters corresponding to various types of polarization beam splitters to assign a string of digital codes to the preset optical characteristic parameters corresponding to various types of polarization beam splitters;

[0068] S210: Inscribe digital codes corresponding to various types of polarization beam splitters on corresponding subtrees, and store characteristic model graphs corresponding to various types of polarization beam splitters on corresponding subtrees, respectively, to obtain a Huffman search tree model library.

[0069] It should be noted that the standard structural characteristic parameters of various types of polarization beam splitters are obtained, and these parameters cover aspects such as grating shape, grating width, grating spacing, and grating period. Based on these standard structural characteristic parameters, characteristic model diagrams corresponding to various types of polarization beam splitters are constructed. This step is to represent the structural characteristics of the polarization beam splitter in a visual or easy-to-process model diagram form, in preparation for the subsequent construction of the model library. At the same time, the preset optical characteristic parameters corresponding to various types of polarization beam splitters are obtained, and these parameters include polarization beam splitting efficiency, extinction ratio, bandwidth, incident angle range, polarization state purity, transmittance, reflectivity, angular resolution, and polarization beam splitting angle. These optical characteristic parameters are important indicators for measuring the performance of polarization beam splitters, and they need to be associated with structural characteristics when constructing the model library. Constructing a Huffman tree is one of the core steps of the entire model library construction. According to various types of polarization beam splitters, a corresponding number of subtrees are recursively cut out in the Huffman tree. The Huffman tree is a tree model with the shortest weighted path length. By cutting the subtree in this way, different types of polarization beam splitters can be effectively classified and organized, making subsequent searches and matches more efficient. The preset optical characteristic parameters corresponding to various types of polarization beam splitters are encoded and assigned a string of digital codes. This encoding method can convert complex optical characteristic parameters into a form that is easy to store and identify in the Huffman tree structure, so that the optical characteristics of each polarization beam splitter can be identified in a concise and unique way. Finally, the digital codes corresponding to various types of polarization beam splitters are engraved on the corresponding subtrees, and the characteristic model graphs corresponding to various types of polarization beam splitters are stored in the corresponding subtrees, thereby obtaining a Huffman search tree model library. This model library integrates the structural characteristics, optical characteristics and organizational structure of the polarization beam splitter, and provides a comprehensive data basis for the subsequent search, matching and evaluation of polarization beam splitters.

[0070] The Huffman search tree model library constructed through the above series of steps organically combines the structural characteristics and optical characteristics of the polarization beam splitter and organizes them in the structure of the Huffman tree. This model library can efficiently store and manage relevant information of different types of polarization beam splitters, and provide fast and accurate data support for subsequent evaluation, search and matching of polarization beam splitters, which helps to improve the work efficiency of research and applications related to polarization beam splitters. For example, it can play an important role in the design optimization, performance evaluation and troubleshooting of polarization beam splitters.

[0071] Preferably, a structural model diagram of the polarization beam splitter to be evaluated is obtained, and the structural model diagram of the polarization beam splitter to be evaluated is imported into a Huffman search tree model library for search and matching, so as to obtain preset optical characteristic parameters of the polarization beam splitter to be evaluated, specifically:

[0072] Acquire laser point cloud data of the polarization beam splitter to be evaluated by a laser scanning device, and construct a structural model diagram of the polarization beam splitter to be evaluated according to the laser point cloud data;

[0073] Extracting the characteristic model graphs in each subtree from the Huffman search tree model library, introducing a bounding box algorithm, and calculating the degree of intersection between the structural model graph of the polarization beam splitter to be evaluated and the characteristic model graphs in each subtree based on the bounding box algorithm;

[0074] Extract the highest degree of intersection between the structural model graph of the polarization beam splitter to be evaluated and the characteristic model graphs in each subtree, and obtain the characteristic model graph to which the highest degree of intersection belongs;

[0075] The subtree corresponding to the characteristic model graph to which the highest intersection degree belongs is identified, and the digital code of the identified subtree is obtained, and the digital code of the identified subtree is interpreted to obtain the preset optical characteristic parameters of the polarization beam splitter to be evaluated.

[0076] It should be noted that the laser point cloud data of the polarization beam splitter to be evaluated is obtained by using a laser scanning device. Laser point cloud data is a three-dimensional data representation form, which contains the coordinate information of a large number of points on the surface of an object. According to these laser point cloud data, a structural model diagram of the polarization beam splitter to be evaluated is constructed. This structural model diagram can accurately reflect the geometric structural characteristics of the polarization beam splitter to be evaluated, and is the basis for subsequent search and matching. In the Huffman search tree model library, it is necessary to extract the feature model diagrams in each subtree. Then the bounding box algorithm is introduced. The bounding box algorithm is an algorithm for quickly calculating the spatial relationship between two objects. Based on this algorithm, the intersection between the structural model diagram of the polarization beam splitter to be evaluated and the feature model diagram in each subtree is calculated. The intersection degree can be understood as a quantitative indicator of the similarity or matching degree between two model diagrams. Among the calculated intersection degrees between the structural model diagram of the polarization beam splitter to be evaluated and the feature model diagram in each subtree, the highest intersection degree is extracted. The feature model diagram corresponding to this highest intersection degree is the model diagram that is most similar in structure to the polarization beam splitter to be evaluated. By obtaining the characteristic model graph with the highest degree of intersection, the model that best matches the structure of the polarization beam splitter to be evaluated in the Huffman search tree model library is found. The subtree corresponding to the characteristic model graph with the highest degree of intersection is identified, and then the digital code of the identified subtree is obtained. Since the preset optical characteristic parameters corresponding to various types of polarization beam splitters are engraved on the subtree in the form of digital codes when the model library was previously constructed, the preset optical characteristic parameters of the polarization beam splitter to be evaluated can be obtained by interpreting the digital code of the identified subtree. This step realizes the mapping from the structural model graph to the optical characteristic parameters, and the corresponding optical characteristic parameters are found through the similarity of the structure.

[0077] Through the above steps, based on the structural model diagram of the polarization beam splitter to be evaluated, the Huffman search tree model library can be used to calculate the degree of intersection with the help of the bounding box algorithm to find the most matching feature model diagram, and then obtain the preset optical characteristic parameters of the polarization beam splitter to be evaluated. This method realizes the rapid and accurate derivation from the structural information of the polarization beam splitter to be evaluated to the optical characteristic parameters, provides an important basis for subsequent operations such as determining whether the polarization beam splitter needs parameter tuning, and improves the efficiency of the polarization beam splitter performance evaluation and optimization process.

[0078] Preferably, the test optical characteristic parameters of the polarization beam splitter to be evaluated are obtained, and it is determined whether the polarization beam splitter to be evaluated needs to be parameter tuned according to the test optical characteristic parameters and the preset optical characteristic parameters, specifically:

[0079] Performing polarization optical testing on the polarization beam splitter to be evaluated based on an optical testing device to obtain test optical characteristic parameters of the polarization beam splitter to be evaluated;

[0080] Acquiring precision performance requirement information of the polarization beam splitter to be evaluated, and determining parameter deviation value thresholds of various optical characteristic parameters of the polarization beam splitter to be evaluated according to the precision performance requirement information;

[0081] Calculating actual parameter differences between various tested optical characteristic parameters of the polarization beam splitter to be evaluated and preset optical characteristic parameters;

[0082] Determine whether one or more actual parameter differences in the polarization beam splitter to be evaluated are greater than a corresponding parameter deviation value threshold;

[0083] If one or more actual parameter differences in the polarization beam splitter to be evaluated are greater than the corresponding parameter deviation threshold, the polarization beam splitter to be evaluated is determined to be a polarization beam splitter that needs parameter tuning;

[0084] If there is no situation in the polarization beam splitter to be evaluated where the actual parameter difference is greater than the corresponding parameter deviation value threshold, the polarization beam splitter to be evaluated is determined as a polarization beam splitter that does not require parameter tuning;

[0085] The tested optical characteristic parameters include polarization splitting efficiency, extinction ratio, bandwidth, incident angle range, polarization state purity, transmittance, reflectivity, angular resolution and polarization splitting angle.

[0086] It should be noted that, first, a polarization optical test is performed on the polarization beam splitter to be evaluated based on an optical test device, so as to obtain the test optical characteristic parameters of the polarization beam splitter to be evaluated. These test optical characteristic parameters cover multiple aspects such as polarization beam splitting efficiency, extinction ratio, bandwidth, incident angle range, polarization state purity, transmittance, reflectivity, angular resolution and polarization beam splitting angle. These parameters comprehensively describe the performance of the polarization beam splitter in actual testing. Then, the accuracy performance requirement information of the polarization beam splitter to be evaluated is obtained, and the parameter deviation value threshold of each optical characteristic parameter of the polarization beam splitter to be evaluated is determined based on this information. This threshold is set according to the specific accuracy performance requirements, and it represents the allowable fluctuation range of each optical characteristic parameter while meeting the application requirements. The actual parameter difference between each test optical characteristic parameter of the polarization beam splitter to be evaluated and the preset optical characteristic parameter is calculated. The preset optical characteristic parameter is the theoretical optical characteristic parameter obtained by model matching, while the test optical characteristic parameter is obtained by actual measurement. By calculating the difference between the two, the degree of deviation between the actual performance and the theoretical performance can be evaluated. Determine whether there is a situation in which the difference of one or more actual parameters in the polarization beam splitter to be evaluated is greater than the corresponding parameter deviation value threshold. If this situation exists, it means that the deviation between the actual performance and the theoretical performance exceeds the allowable range, and the polarization beam splitter to be evaluated is determined to be a polarization beam splitter that needs parameter tuning; if this situation does not exist, that is, the deviation between the actual performance and the theoretical performance is within the allowable range, the polarization beam splitter to be evaluated is determined to be a polarization beam splitter that does not need parameter tuning.

[0087] Through the above steps, it is possible to accurately determine whether the polarization beam splitter to be evaluated needs parameter tuning based on the test optical characteristic parameters and preset optical characteristic parameters of the polarization beam splitter to be evaluated, combined with the accuracy performance requirement information. This method comprehensively considers the actual test results, theoretical expectations, and accuracy requirements, and provides a scientific and reasonable judgment mechanism for the performance evaluation of the polarization beam splitter, which helps to ensure that the performance of the polarization beam splitter in actual applications meets the expected requirements and improves the accuracy of the quality control and performance optimization of the polarization beam splitter.

[0088] Preferably, if it is necessary to perform parameter tuning on the polarization beam splitter to be evaluated, the optical characteristic parameters to be tuned of the polarization beam splitter to be parameter tuned are obtained, specifically:

[0089] If the polarization beam splitter to be evaluated is determined to be a polarization beam splitter that requires parameter tuning, the optical characteristic parameters corresponding to the actual parameter difference values ​​that are greater than the corresponding parameter deviation value threshold are calibrated as the optical characteristic parameters to be tuned, thereby obtaining the optical characteristic parameters to be tuned of the polarization beam splitter that requires parameter tuning.

[0090] Preferably, the singular structural characteristic parameters of the polarization beam splitter that need to be parameter-tuned are determined according to the optical characteristic parameters to be tuned, specifically:

[0091] Obtaining functional specification information of the polarization beam splitter that needs parameter tuning, and obtaining the degree of linear influence of each structural characteristic parameter on each optical characteristic parameter in the polarization beam splitter that needs parameter tuning according to the functional specification information;

[0092] Each structural characteristic parameter is used as a quantitative node, and each optical characteristic parameter is used as a variable node; and the topological distance between each quantitative node and each variable node is determined according to the linear influence degree between each structural characteristic parameter and each optical characteristic parameter; wherein, the greater the linear influence degree of the structural characteristic parameter on the optical characteristic parameter, the smaller the corresponding topological distance;

[0093] Topologically connect each quantitative node with each variable node according to the linear distance between each quantitative node and each variable node, and obtain a topological structure diagram between each structural characteristic parameter and each optical characteristic parameter in the polarization beam splitter that needs parameter tuning;

[0094] Obtaining optical characteristic parameters to be tuned of the polarization beam splitter that needs parameter tuning, and retrieving a variable node corresponding to the optical characteristic parameters to be tuned in the topological structure diagram, and defining the node as a target variable node;

[0095] Obtaining the topological distance between the target variable node and the quantitative node in the topological structure diagram, and marking the quantitative node corresponding to the topological distance not greater than the preset distance threshold as the target quantitative node;

[0096] The structural characteristic parameters corresponding to the target quantitative nodes are obtained, and the singular structural characteristic parameters of the polarization beam splitter that need to be parameter tuned are obtained.

[0097] It should be noted that when the polarization beam splitter to be evaluated is determined to require parameter tuning, the optical characteristic parameters corresponding to the actual parameter difference value greater than the corresponding parameter deviation value threshold are calibrated as the optical characteristic parameters to be tuned. This is a direct and reasonable judgment method, because those optical characteristic parameters with large deviations between the actual values ​​and the preset values ​​are the objects that need to be adjusted and optimized, which clarifies the focus of subsequent parameter tuning work.

[0098] First, obtain the functional specification information of the polarization beam splitter that needs to be parameter tuned, and obtain the linear influence degree between each structural characteristic parameter and each optical characteristic parameter. This step is the basis for establishing the relationship between structural characteristics and optical characteristics. The linear influence degree can reflect the influence law of changes in structural characteristics on optical characteristics. Take each structural characteristic parameter as a quantitative node and each optical characteristic parameter as a variable node. Determine the topological distance between each quantitative node and each variable node according to the linear influence degree (the greater the linear influence degree, the smaller the topological distance). Then, topologically connect each quantitative node with each variable node according to these topological distances, so as to obtain the topological structure diagram between each structural characteristic parameter and each optical characteristic parameter in the polarization beam splitter that needs to be parameter tuned. This topological structure diagram intuitively shows the network of mutual relationships between structural characteristic parameters and optical characteristic parameters. Obtain the optical characteristic parameters to be tuned of the polarization beam splitter that needs to be parameter tuned, retrieve the variable nodes corresponding to these optical characteristic parameters to be tuned in the topological structure diagram, and define them as target variable nodes. This step is to locate the nodes related to the optical characteristics that need to be tuned in the topological structure. In the topological structure diagram, the topological distance between the target variable node and the quantitative node is obtained, and the quantitative node corresponding to the topological distance not greater than the preset distance threshold is marked as the target quantitative node. This step is to screen out the quantitative nodes that are closely related to the target variable node through the topological distance. Finally, the structural characteristic parameters corresponding to the target quantitative node are obtained. These structural characteristic parameters are the singular structural characteristic parameters of the polarization beam splitter that need to be parameter tuned. Through such a series of steps, the structural characteristic parameters that have an important influence on the optical characteristics that need to be tuned are found from the relationship network between structural characteristics and optical characteristics.

[0099] Through the above steps, after determining that the polarization beam splitter needs to be tuned, the optical characteristic parameters to be tuned can be accurately found, and the singular structure characteristic parameters closely related to the optical characteristic parameters to be tuned can be further determined by constructing a topological structure, analyzing topological relationships, etc. This method establishes a complete logical chain from the optical characteristic parameter deviation to the optical characteristic parameters to be tuned, and then to the singular structure characteristic parameters, providing an accurate basis for targeted parameter tuning of the polarization beam splitter, helping to improve the efficiency and accuracy of parameter tuning of the polarization beam splitter, thereby better meeting its functional requirements.

[0100] Preferably, the singular structural characteristic parameters of the polarization beam splitter that needs parameter tuning are optimized, specifically:

[0101] Obtaining a structural model diagram of a polarization beam splitter that needs parameter tuning, performing format conversion processing on the structural model diagram of the polarization beam splitter that needs parameter tuning, obtaining a finite element analysis model of the polarization beam splitter that needs parameter tuning, and importing the finite element analysis model into finite element analysis software;

[0102] Determine key variables of the finite element analysis model according to the singular structural characteristic parameters of the polarization beam splitter to be tuned, and set the excitation source parameters in the finite element analysis software;

[0103] Acquire a preset process range of the characteristic parameter of the singular structure, define an upper boundary condition and a lower boundary condition of the characteristic parameter of the singular structure according to the preset process range, and discretize a plurality of discrete parameter values ​​of the characteristic parameter of the singular structure according to the upper boundary condition and the lower boundary condition;

[0104] Replacing corresponding singular structural characteristic parameters in the finite element analysis model based on respective discrete parameter values, and performing polarization optical simulation test processing on the finite element analysis model after the parameter replacement to obtain simulated optical characteristic parameters of the finite element analysis model;

[0105] Calculating the Pearson correlation coefficient value between the simulated optical characteristic parameter and the preset optical characteristic parameter, and if the Pearson correlation coefficient value is not greater than the preset value, performing the next discrete parameter value replacement test operation, and continuously iterating this process until the obtained Pearson correlation coefficient value is greater than the preset value;

[0106] When the obtained Pearson correlation coefficient value is greater than the preset value, the discrete parameter value corresponding to the corresponding replacement test operation is used as the tuning parameter value of the singular structure characteristic parameter;

[0107] The polarization beam splitter that needs parameter tuning is tuned based on the tuning parameter value.

[0108] It should be noted that the structural model diagram of the polarization beam splitter to be parameter tuned is obtained, and the format is converted to obtain the finite element analysis model, which is then imported into the finite element analysis software. This step is to convert the structural model of the polarization beam splitter into a form suitable for finite element analysis. The finite element analysis software can perform accurate numerical simulation calculations on the model to provide a computing platform for subsequent parameter optimization. According to the singular structural characteristic parameters of the polarization beam splitter to be tuned, the key variables of the finite element analysis model are determined. These key variables are the parts that need to be focused on and adjusted in the finite element analysis. At the same time, the excitation source parameters are set in the finite element analysis software. The excitation source parameters simulate the external excitation conditions in actual work, making the simulation closer to the real situation. The preset process range of the singular structural characteristic parameters is obtained, and the upper boundary conditions and lower boundary conditions of the singular structural characteristic parameters are defined according to this range, and then several discrete parameter values ​​are discretized within this range. The discretization process is to explore the value space of the singular structural characteristic parameters through a finite number of parameter values ​​in order to find the optimal parameter value. The corresponding singular structure characteristic parameters in the finite element analysis model are replaced based on each discrete parameter value, and then the finite element analysis model after the replacement parameters is subjected to polarization optical simulation test processing to obtain the simulated optical characteristic parameters. Then the Pearson correlation coefficient value between the simulated optical characteristic parameters and the preset optical characteristic parameters is calculated. The Pearson correlation coefficient is used to measure the linear correlation between two variables, and is used here to evaluate the closeness between the simulation results and the preset requirements. If the Pearson correlation coefficient value is not greater than the preset value, it means that the simulation results do not meet the requirements, and the next discrete parameter value replacement test operation is performed, and this process is continuously iterated until the obtained Pearson correlation coefficient value is greater than the preset value. This iterative process searches in the value space of the discrete parameter value to find the parameter value that meets the requirements. When the Pearson correlation coefficient value is greater than the preset value, the discrete parameter value corresponding to the corresponding replacement test operation is used as the tuning parameter value of the singular structure characteristic parameter. Finally, based on this tuning parameter value, the polarization beam splitter that needs to be parameter tuned is tuned, so that the optical performance of the polarization beam splitter meets the preset requirements.

[0109] Through the above steps, the singular structural characteristic parameters of the polarization beam splitter that needs parameter tuning can be effectively optimized. From building a finite element analysis model to setting parameters, discrete values, simulation testing, iterative search, and finally determining the tuning parameter values ​​and performing tuning processing, the entire process forms a complete parameter optimization process. This method can find the optimal structural parameter values ​​that make the optical performance of the polarization beam splitter meet the preset requirements through precise numerical simulation and iterative search under the premise of meeting the preset process range, thereby improving the accuracy and efficiency of the polarization beam splitter parameter tuning and ensuring the performance of the polarization beam splitter in practical applications.

[0110] The polarization beam splitter parameter tuning method further includes the following steps:

[0111] Obtaining a structural model diagram of the polarization beam splitter to be evaluated, performing feature extraction processing on the structural model diagram, and obtaining feature information of defects in the polarization beam splitter to be evaluated; the defects include micropores, microcracks, burrs, depressions, and protrusions; the feature information includes defect locations and defect types;

[0112] Acquire the position coordinate information of each defect in the polarization beam splitter to be evaluated according to the characteristic information; introduce the Lagrange interpolation method, and regard each defect as a data point according to the position coordinate information of each defect in the polarization beam splitter to be evaluated;

[0113] The position coordinates of each defect are numbered in a preset order, and the Lagrange interpolation operation is performed on the horizontal coordinate and the vertical coordinate in the position coordinate information of each defect;

[0114] Multiply the ordinate value corresponding to each abscissa point by the Lagrange basis function, and add all the product results to obtain the Lagrange interpolation result in the abscissa direction; similarly, perform the same operation on the ordinate to obtain the Lagrange interpolation result in the ordinate direction.

[0115] The Lagrangian interpolation results in the horizontal and vertical directions are combined to construct a Lagrangian interpolation curve of the defects in the polarization beam splitter to be evaluated;

[0116] Acquire precision performance requirement information of the polarization beam splitter to be evaluated, and determine the limit defect concentration value of each sub-region position in the polarization beam splitter to be evaluated according to the precision performance requirement information;

[0117] Fitting the limit defect concentration value of each sub-region position in the polarization beam splitter to be evaluated into the Lagrangian interpolation curve according to the position coordinate relationship of each sub-region position;

[0118] Compare the defect concentration value of each sub-region position on the fitted Lagrange interpolation curve with the limit defect concentration value of the sub-region. If the defect concentration value on the curve is greater than the limit defect concentration value, it means that the defect at the sub-region position does not meet the requirements and is marked as a defective sub-region position.

[0119] Acquire production equipment that is production-related to the defect sub-region position, and acquire real-time production parameter information of the production equipment, calculate the difference between the real-time production parameter information and the preset production parameter information, and obtain a production parameter deviation value;

[0120] The real-time production parameter information corresponding to the production parameter deviation value greater than the preset deviation value threshold is adjusted and optimized.

[0121] It should be noted that the structural model diagram of the polarization beam splitter to be evaluated is obtained, and the characteristic information of the defects (such as micropores, microcracks, etc.) therein, including the defect location and type, is obtained through feature extraction processing. Based on the defect location information, its coordinates are obtained, and each defect is regarded as a data point. After numbering in a preset order, the horizontal and vertical coordinates are respectively subjected to Lagrangian interpolation operations. The interpolation results in the horizontal and vertical coordinate directions are combined to obtain the Lagrangian interpolation curve of the defect. This step converts the discrete defect location information into a continuous curve representation, which helps to analyze the overall distribution of defects in the polarization beam splitter. The accuracy performance requirement information of the polarization beam splitter to be evaluated is obtained, the limit defect concentration value of each sub-region position is determined, and then it is fitted into the Lagrangian interpolation curve according to the sub-region position coordinate relationship. This makes the curve not only contain the defect location information, but also incorporates the tolerance information of the defect concentration in different regions, which provides a basis for subsequent judgment of whether the defects meet the requirements. Compare the defect concentration value of each sub-region on the fitted Lagrangian interpolation curve with the limit defect concentration value. If the value on the curve is greater than the limit value, the defect of the sub-region does not meet the requirements and is marked as the defect sub-region position. This judgment is based on the previously constructed curve and the set limit value, and can accurately find the area that does not meet the requirements. For the marked defect sub-region position, find the production equipment with production relevance to it and obtain its real-time production parameter information. Calculate the difference between the real-time production parameter and the preset production parameter to obtain the production parameter deviation value. If the deviation value is greater than the preset deviation value threshold, adjust and optimize the corresponding real-time production parameter. This step establishes the connection between product defects and the production process, and improves product quality by adjusting production parameters. Through the steps of this method, the defect analysis of the polarization beam splitter to be evaluated can be comprehensively carried out, from defect feature extraction to construction of interpolation curve, and then to judgment whether the defect meets the requirements, and finally traced back to the production equipment and adjusted the parameters. Not only can the sub-region that does not meet the requirements be accurately found, but also the problem can be solved from the source of production, and the production quality and product qualification rate of the polarization beam splitter can be improved.

[0122] The polarization beam splitter parameter tuning method further includes the following steps:

[0123] Obtain standard texture feature images of the polarization beam splitter to be evaluated when it works under various characteristic environmental conditions through a big data network;

[0124] Performing matrix transformation processing on each standard texture feature image, obtaining a standard grayscale co-occurrence matrix corresponding to each standard texture feature image, and obtaining a standard grayscale co-occurrence matrix when the polarization beam splitter to be evaluated works under various characteristic environmental conditions;

[0125] Performing robustness tests on the polarization beam splitter to be evaluated under various characteristic environmental conditions, and obtaining actual texture feature images corresponding to the polarization beam splitter to be evaluated under various characteristic environmental conditions;

[0126] Performing matrix transformation processing on each actual texture feature image to obtain an actual gray-level co-occurrence matrix corresponding to the actual texture feature image, and obtaining an actual gray-level co-occurrence matrix when the polarization beam splitter to be evaluated works under various characteristic environmental conditions;

[0127] The structural similarity index between the actual gray-level co-occurrence matrix and the standard gray-level co-occurrence matrix of the polarization beam splitter to be evaluated when working under various characteristic environmental conditions is calculated respectively;

[0128] If the structural similarity indexes between the actual gray-level co-occurrence matrix and the standard gray-level co-occurrence matrix of the polarization beam splitter to be evaluated when working under various characteristic environmental conditions are greater than a preset index threshold, the polarization beam splitter to be evaluated is determined as a polarization beam splitter that does not require parameter tuning;

[0129] If the structural similarity index between the actual gray-level co-occurrence matrix and the standard gray-level co-occurrence matrix of the polarization beam splitter to be evaluated when working under one or more characteristic environmental conditions is not greater than a preset index threshold, the polarization beam splitter to be evaluated is determined to be a polarization beam splitter that requires parameter tuning.

[0130] It should be noted that the standard texture feature images of the polarization beam splitter to be evaluated when working under various characteristic environmental conditions are obtained by using the big data network. These characteristic environmental conditions include different temperatures, humidity, light intensity, etc. Then, each standard texture feature image is subjected to matrix transformation processing, where matrix transformation is an operation to convert image data into a form that is easier to analyze. Through this processing, the standard grayscale co-occurrence matrix corresponding to each standard texture feature image is obtained. The grayscale co-occurrence matrix is ​​a matrix used to describe the texture features of an image, which can reflect the spatial distribution relationship of the grayscale in the image. In this way, the standard grayscale co-occurrence matrix of the polarization beam splitter to be evaluated when working under various characteristic environmental conditions is obtained, and these matrices will be used as the basis for subsequent judgments. The polarization beam splitter to be evaluated is subjected to robustness tests of various characteristic environmental conditions, and the actual texture feature images corresponding to the polarization beam splitter to be evaluated under various characteristic environmental conditions are obtained during the test process. Similar to obtaining the standard texture feature image, each actual texture feature image is subjected to matrix transformation processing, so as to obtain the actual grayscale co-occurrence matrix corresponding to the actual texture feature image, and obtain the actual grayscale co-occurrence matrix of the polarization beam splitter to be evaluated when working under various characteristic environmental conditions. This step is to obtain the texture feature data of the polarization beam splitter in the actual working environment. The structural similarity index between the actual grayscale co-occurrence matrix and the standard grayscale co-occurrence matrix of the polarization beam splitter to be evaluated when working under various characteristic environmental conditions is calculated respectively. The structural similarity index is an indicator to measure the similarity between two images (here, the texture features represented by the grayscale co-occurrence matrix). If the structural similarity index between the actual grayscale co-occurrence matrix and the standard grayscale co-occurrence matrix of the polarization beam splitter to be evaluated when working under various characteristic environmental conditions is greater than the preset index threshold, it means that under various environmental conditions, the actual texture features of the polarization beam splitter are very similar to the standard texture features, that is, its performance is relatively stable under different environments, so the polarization beam splitter to be evaluated is judged as a polarization beam splitter that does not require parameter tuning. On the contrary, if the structural similarity index between the actual grayscale co-occurrence matrix and the standard grayscale co-occurrence matrix when working under one or more characteristic environmental conditions is not greater than the preset index threshold, it indicates that under these environmental conditions, the performance of the polarization beam splitter may have deviated and parameter tuning is required, so the polarization beam splitter to be evaluated is judged as a polarization beam splitter that requires parameter tuning. By obtaining the standard and actual texture feature images of the polarization beam splitter to be evaluated under different characteristic environmental conditions, converting them into grayscale co-occurrence matrices and calculating the structural similarity index, the performance stability of the polarization beam splitter in different environments can be effectively evaluated, and it can be accurately determined whether the polarization beam splitter needs parameter tuning. This provides a new approach based on texture feature analysis for the performance evaluation and optimization of the polarization beam splitter, which helps to improve the reliability and stability of the polarization beam splitter in complex environments.

[0131] The present invention also discloses a polarization beam splitter parameter tuning system based on micro-nano gratings, such as Figure 3 As shown, the polarization beam splitter parameter tuning system includes a memory 45 and a processor 55. The memory 45 stores a polarization beam splitter parameter tuning method program. When the polarization beam splitter parameter tuning method program is executed by the processor 55, any one of the steps of the polarization beam splitter parameter tuning method is implemented.

[0132] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for tuning parameters of a polarization beam splitter based on micro-nano grating, characterized in that: The following steps are involved: Obtaining standard structural characteristic parameters corresponding to various types of polarization beam splitters, and constructing a Huffman search tree model library according to the standard structural characteristic parameters corresponding to various types of polarization beam splitters; Obtaining a structural model diagram of the polarization beam splitter to be evaluated, importing the structural model diagram of the polarization beam splitter to be evaluated into a Huffman search tree model library for search and matching, and obtaining preset optical characteristic parameters of the polarization beam splitter to be evaluated; Obtaining test optical characteristic parameters of the polarization beam splitter to be evaluated, and determining whether parameter tuning of the polarization beam splitter to be evaluated is required according to the test optical characteristic parameters and preset optical characteristic parameters; If it is necessary to perform parameter tuning on the polarization beam splitter to be evaluated, the optical characteristic parameters to be tuned of the polarization beam splitter to be tuned are obtained; and the singular structural characteristic parameters of the polarization beam splitter to be tuned are determined according to the optical characteristic parameters to be tuned; The singular structural characteristic parameters of the polarization beam splitter that needs parameter tuning are optimized so that the optical performance of the polarization beam splitter that needs parameter tuning meets the preset requirements.

2. The method for tuning parameters of a polarization beam splitter based on micro-nano grating according to claim 1, characterized in that: Obtain standard structural characteristic parameters corresponding to various types of polarization beam splitters, and construct a Huffman search tree model library according to the standard structural characteristic parameters corresponding to various types of polarization beam splitters, specifically: Obtaining standard structural characteristic parameters corresponding to various types of polarization beam splitters, and constructing characteristic model diagrams corresponding to various types of polarization beam splitters according to the corresponding standard structural characteristic parameters; wherein the standard structural characteristic parameters include grating shape, grating width, grating spacing, and grating period; And obtaining preset optical characteristic parameters corresponding to various types of polarization beam splitters; wherein the preset optical characteristic parameters include polarization beam splitting efficiency, extinction ratio, bandwidth, incident angle range, polarization state purity, transmittance, reflectivity, angular resolution and polarization beam splitting angle; Constructing a Huffman tree, and recursively dividing a corresponding number of subtrees in the Huffman tree according to various types of polarization beam splitters; Encoding preset optical characteristic parameters corresponding to various types of polarization beam splitters to assign a string of digital codes to the preset optical characteristic parameters corresponding to various types of polarization beam splitters; The digital codes corresponding to various types of polarization beam splitters are engraved on the corresponding subtrees, and the characteristic model graphs corresponding to various types of polarization beam splitters are respectively stored on the corresponding subtrees to obtain a Huffman search tree model library.

3. The method for tuning parameters of a polarization beam splitter based on micro-nano grating according to claim 1, characterized in that: Obtain a structural model diagram of the polarization beam splitter to be evaluated, import the structural model diagram of the polarization beam splitter to be evaluated into the Huffman search tree model library for search and matching, and obtain preset optical characteristic parameters of the polarization beam splitter to be evaluated, specifically: Acquire laser point cloud data of the polarization beam splitter to be evaluated by a laser scanning device, and construct a structural model diagram of the polarization beam splitter to be evaluated according to the laser point cloud data; Extracting the characteristic model graphs in each subtree from the Huffman search tree model library, introducing a bounding box algorithm, and calculating the degree of intersection between the structural model graph of the polarization beam splitter to be evaluated and the characteristic model graphs in each subtree based on the bounding box algorithm; Extract the highest degree of intersection between the structural model graph of the polarization beam splitter to be evaluated and the characteristic model graphs in each subtree, and obtain the characteristic model graph to which the highest degree of intersection belongs; The subtree corresponding to the characteristic model graph to which the highest intersection degree belongs is identified, and the digital code of the identified subtree is obtained, and the digital code of the identified subtree is interpreted to obtain the preset optical characteristic parameters of the polarization beam splitter to be evaluated.

4. The method for tuning parameters of a polarization beam splitter based on micro-nano grating according to claim 1, characterized in that: Obtain the test optical characteristic parameters of the polarization beam splitter to be evaluated, and determine whether it is necessary to perform parameter tuning on the polarization beam splitter to be evaluated based on the test optical characteristic parameters and the preset optical characteristic parameters, specifically: Performing polarization optical testing on the polarization beam splitter to be evaluated based on an optical testing device to obtain test optical characteristic parameters of the polarization beam splitter to be evaluated; Acquiring precision performance requirement information of the polarization beam splitter to be evaluated, and determining parameter deviation value thresholds of various optical characteristic parameters of the polarization beam splitter to be evaluated according to the precision performance requirement information; Calculating actual parameter differences between various tested optical characteristic parameters of the polarization beam splitter to be evaluated and preset optical characteristic parameters; Determine whether one or more actual parameter differences in the polarization beam splitter to be evaluated are greater than a corresponding parameter deviation value threshold; If one or more actual parameter differences in the polarization beam splitter to be evaluated are greater than the corresponding parameter deviation threshold, the polarization beam splitter to be evaluated is determined to be a polarization beam splitter that needs parameter tuning; If there is no situation in the polarization beam splitter to be evaluated where the actual parameter difference is greater than the corresponding parameter deviation value threshold, the polarization beam splitter to be evaluated is determined as a polarization beam splitter that does not require parameter tuning; The tested optical characteristic parameters include polarization splitting efficiency, extinction ratio, bandwidth, incident angle range, polarization state purity, transmittance, reflectivity, angular resolution and polarization splitting angle.

5. The method for tuning parameters of a polarization beam splitter based on micro-nano grating according to claim 4, characterized in that: If it is necessary to perform parameter tuning on the polarization beam splitter to be evaluated, obtain the optical characteristic parameters to be tuned of the polarization beam splitter to be tuned, specifically: If the polarization beam splitter to be evaluated is determined to be a polarization beam splitter that requires parameter tuning, the optical characteristic parameters corresponding to the actual parameter difference values ​​that are greater than the corresponding parameter deviation value threshold are calibrated as the optical characteristic parameters to be tuned, thereby obtaining the optical characteristic parameters to be tuned of the polarization beam splitter that requires parameter tuning.

6. The method for tuning parameters of a polarization beam splitter based on micro-nano grating according to claim 1, characterized in that: The singular structural characteristic parameters of the polarization beam splitter that need to be parameter-tuned are determined according to the optical characteristic parameters to be tuned, specifically: Obtaining functional specification information of the polarization beam splitter that needs parameter tuning, and obtaining the degree of linear influence of each structural characteristic parameter on each optical characteristic parameter in the polarization beam splitter that needs parameter tuning according to the functional specification information; Each structural characteristic parameter is used as a quantitative node, and each optical characteristic parameter is used as a variable node; The topological distance between each quantitative node and each variable node is determined according to the linear influence degree between each structural characteristic parameter on each optical characteristic parameter; wherein, the greater the linear influence degree of the structural characteristic parameter on the optical characteristic parameter, the smaller the corresponding topological distance; Topologically connect each quantitative node with each variable node according to the linear distance between each quantitative node and each variable node, and obtain a topological structure diagram between each structural characteristic parameter and each optical characteristic parameter in the polarization beam splitter that needs parameter tuning; Obtaining optical characteristic parameters to be tuned of the polarization beam splitter that needs parameter tuning, and retrieving a variable node corresponding to the optical characteristic parameters to be tuned in the topological structure diagram, and defining the node as a target variable node; Obtaining the topological distance between the target variable node and the quantitative node in the topological structure diagram, and marking the quantitative node corresponding to the topological distance not greater than the preset distance threshold as the target quantitative node; The structural characteristic parameters corresponding to the target quantitative nodes are obtained, and the singular structural characteristic parameters of the polarization beam splitter that need to be parameter tuned are obtained.

7. The method for tuning parameters of a polarization beam splitter based on micro-nano grating according to claim 1, characterized in that: The singular structural characteristic parameters of the polarization beam splitter that needs parameter tuning are optimized, specifically: Obtaining a structural model diagram of a polarization beam splitter that needs parameter tuning, performing format conversion processing on the structural model diagram of the polarization beam splitter that needs parameter tuning, obtaining a finite element analysis model of the polarization beam splitter that needs parameter tuning, and importing the finite element analysis model into finite element analysis software; Determine key variables of the finite element analysis model according to the singular structural characteristic parameters of the polarization beam splitter to be tuned, and set the excitation source parameters in the finite element analysis software; Acquire a preset process range of the characteristic parameter of the singular structure, define an upper boundary condition and a lower boundary condition of the characteristic parameter of the singular structure according to the preset process range, and discretize a plurality of discrete parameter values ​​of the characteristic parameter of the singular structure according to the upper boundary condition and the lower boundary condition; Replacing corresponding singular structural characteristic parameters in the finite element analysis model based on respective discrete parameter values, and performing polarization optical simulation test processing on the finite element analysis model after the parameter replacement to obtain simulated optical characteristic parameters of the finite element analysis model; Calculating the Pearson correlation coefficient value between the simulated optical characteristic parameter and the preset optical characteristic parameter, and if the Pearson correlation coefficient value is not greater than the preset value, performing the next discrete parameter value replacement test operation, and continuously iterating this process until the obtained Pearson correlation coefficient value is greater than the preset value; When the obtained Pearson correlation coefficient value is greater than the preset value, the discrete parameter value corresponding to the corresponding replacement test operation is used as the tuning parameter value of the singular structure characteristic parameter; The polarization beam splitter that needs parameter tuning is tuned based on the tuning parameter value.

8. A polarization beam splitter parameter tuning system based on micro-nano grating, characterized in that: The polarization beam splitter parameter tuning system includes a memory and a processor, wherein the memory stores a polarization beam splitter parameter tuning method program, and when the polarization beam splitter parameter tuning method program is executed by the processor, the steps of the polarization beam splitter parameter tuning method as described in any one of claims 1 to 7 are implemented.

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