Optical performance detection method and system applied to doublet lenses

Abstract

This invention relates to the field of lens optical performance testing technology, and particularly to a method and system for testing the optical performance of dual-effect lenses. The method includes: determining a target detection area matching at least two sets of optical functional zones of the dual-effect lens based on preset design parameters of the lens; simultaneously emitting a multi-dimensional detection beam into the area; acquiring feedback signals and extracting original feature parameters; establishing a mapping relationship between parameters and detection dimensions and detection areas; constructing an optical performance detection hypergraph containing three types of nodes and coupled hyperedges based on this mapping; inputting the hypergraph into a hypergraph neural network model; extracting high-order correlation features and eliminating nonlinear coupling interference of multi-dimensional optical parameters; obtaining correction feature parameters; and outputting a comprehensive optical performance testing result. This invention eliminates nonlinear coupling interference of multi-dimensional optical parameters, reflects the comprehensive optical performance of dual-effect lenses, and meets the requirements for simultaneous testing of multi-functional zones.

Description

Technical Field

[0001] This invention relates to the technical field of optical performance testing of lenses, and more particularly to a method and system for testing the optical performance of dual-effect lenses. Background Technology

[0002] Dual-effect lenses refer to optometric lenses that simultaneously possess at least two sets of optical functional zones and can achieve two or more optical functions, including myopia control defocus lenses, bifocal lenses, progressive multifocal lenses, etc. They are currently the mainstream application products in the field of optometry and visual health. In order to ensure product quality and usage effect, it is necessary to test their optical performance.

[0003] Existing optical lens performance testing methods have formed mature single-dimensional parameter testing schemes, which can achieve stable testing of single optical indicators such as lens refractive power and spectral transmittance. Some testing schemes can complete the sequential acquisition of multi-dimensional optical parameters of the lens through time-sharing testing, which can meet the routine testing needs of ordinary single-vision lenses.

[0004] However, for dual-effect lenses with multiple optical functional zones, the optical parameters of different optical functional zones are spatially correlated, and there is nonlinear coupling interference between the multi-dimensional optical testing parameters used to characterize the overall performance of the lens. Existing testing methods cannot effectively eliminate the influence of the above nonlinear coupling interference on the test results during the simultaneous testing of the multi-dimensional optical performance of all functional zones of dual-effect lenses, resulting in the test results failing to accurately and truly reflect the overall optical performance of dual-effect lenses. Summary of the Invention

[0005] This invention provides a method and system for testing the optical performance of dual-effect lenses, which can effectively solve the problems in the background art.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: Methods for testing the optical performance of dual-effect lenses include: Based on the preset design parameters of the dual-effect lens to be tested, the target detection area that matches at least two sets of optical functional zones of the dual-effect lens to be tested is determined. Multiple detection beams corresponding to different optical performance detection dimensions are simultaneously emitted into the target detection area. Feedback optical signals are collected and corresponding original feature parameters are extracted. A mapping relationship between the original feature parameters and the corresponding optical performance detection dimensions and the target detection area is established. An optical performance detection hypergraph is constructed based on mapping relationships, including spatial location nodes, performance dimension nodes, and signal feature nodes, as well as hyperedges that characterize the coupling relationships between nodes; The optical performance testing hypergraph is input into a preset hypergraph neural network model. High-order correlation features between nodes are extracted and nonlinear coupling interference of multi-dimensional optical parameters is eliminated to obtain the corrected target feature parameters. The comprehensive optical performance testing results of the dual-effect lens to be tested are then output.

[0007] Furthermore, methods for determining the target detection region include: The refractive correction parameters, defocus control parameters, microlens array parameters, and functional film design parameters of the dual-effect lens to be tested are obtained as preset design parameters. Determine the optical center and effective optical boundary of the lens; Using the optical center as the origin, multiple concentric field-of-view rings are formed by polar coordinate gridding. Multiple sampling points are set at equal intervals within each field-of-view ring, and all sampling points within each field-of-view ring together constitute the target detection area.

[0008] Furthermore, obtaining the preset design parameters includes: Extract standard values ​​of refractive correction parameters, defocus control parameters, microlens array parameters, and functional film design parameters from the production design documents; The production batch information is read through the lens traceability system to obtain actual production parameters and calibrate standard values. For parameters that cannot be obtained from design documents and traceability systems, non-contact optical measurement equipment is used to scan the lens surface to extract the distribution characteristics of the microlens array and the thickness and distribution range of the functional film as supplementary parameters.

[0009] Furthermore, the detection beam includes at least a refractive correction detection beam, a defocus performance detection beam, a spectral transmittance detection beam, and a surface reflectance performance detection beam; Multiple probe beams are synchronously incident point-by-point on the same axis through a beam splitter and combiner assembly, and the emission timing is synchronized.

[0010] Furthermore, the beam splitter and combiner adopts an optical fiber coupling structure, integrating the refractive correction probe beam, defocus performance probe beam, spectral transmittance probe beam, and surface reflectance performance probe beam into a single coaxial probe beam.

[0011] Furthermore, the original feature parameters include: Sphere power, cylinder power, and root mean square error of wavefront in the refractive correction dimension; Defocusing amount and microlens optical efficiency in the defocusing control dimension; Visible light transmittance, blue light blocking rate, and ultraviolet light blocking rate in the spectral protection dimension; The visible light average reflectance and diffuse reflection ratio are dimensions of antireflectivity.

[0012] Furthermore, hyperedges include spatially coupled hyperedges, dimensionally coupled hyperedges, signal coupled hyperedges, and cross-domain coupled hyperedges. Each type of hyperedge connects multiple corresponding nodes with coupling relationships.

[0013] Furthermore, the hypergraph neural network model includes a feature encoding layer, a cascaded hypergraph convolution module, an interference correction branch, and a comprehensive evaluation branch; The feature encoding layer is used to linearly encode the node features of the hypergraph to generate initial node embedding vectors; The cascaded hypergraph convolution module includes at least three hypergraph convolutional layers with hyperedge attention mechanisms, used to extract high-order association features of nodes; The interference correction branch is used to fit and eliminate nonlinear coupling interference, and outputs the corrected target characteristic parameters. The comprehensive evaluation branch is used to output the optical performance test results.

[0014] Furthermore, the optical performance test results include individual performance test values ​​at each sampling point, design deviation values, pass / fail results, overall lens performance score and performance level.

[0015] On the other hand, the present invention also provides an optical performance testing system for dual-effect lenses, comprising: The region determination module is used to determine the target detection region that matches at least two sets of optical functional zones of the dual-effect lens under test, based on the preset design parameters of the dual-effect lens under test. The detection and acquisition module is used to simultaneously emit multiple detection beams corresponding to different optical performance detection dimensions into the target detection area, acquire feedback optical signals and extract corresponding original feature parameters, and establish a mapping relationship between the original feature parameters and the corresponding optical performance detection dimensions and the target detection area. The hypergraph construction module is used to construct an optical performance detection hypergraph based on mapping relationships, including spatial location nodes, performance dimension nodes, and signal feature nodes, as well as hyperedges that characterize the coupling relationships between nodes; The result output module is used to input the optical performance detection hypergraph into a preset hypergraph neural network model, extract high-order correlation features between nodes and eliminate nonlinear coupling interference of multi-dimensional optical parameters to obtain the corrected target feature parameters, and output the comprehensive optical performance detection results of the dual-effect lens to be tested.

[0016] The technical solution of this invention can achieve the following technical effects: By synchronously acquiring parameters of all functional zones through coaxial incident multi-dimensional probe beams, and combining this with a hypergraph for optical performance testing to fully characterize various coupling relationships, high-order correlation features are accurately extracted and coupling interference is eliminated through a hypergraph neural network model to obtain reliable correction feature parameters. Finally, comprehensive and accurate integrated optical performance test results are output, which overcomes the shortcomings of existing testing methods that cannot adapt to the synchronous testing of dual-effect lenses and the difficulty in eliminating coupling interference. This improves the accuracy and completeness of optical performance testing of dual-effect lenses, while adapting to the testing needs of various types of dual-effect lenses, ensuring a stable and repeatable testing process, and meeting the practical application needs of quality control of dual-effect lenses.

[0017] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the optical performance testing method of the present invention applied to dual-effect lenses; Figure 2 This is a schematic diagram of the optical performance testing system of the present invention applied to dual-effect lenses. Detailed Implementation

[0020] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0022] like Figure 1 As shown, the optical performance testing method for dual-effect lenses of the present invention specifically includes the following steps: Step S100: Based on the preset design parameters of the dual-effect lens to be tested, determine the target detection area that matches at least two sets of optical functional zones of the dual-effect lens to be tested. Step S200: Simultaneously emit multiple detection beams corresponding to different optical performance detection dimensions to the target detection area, collect feedback optical signals and extract corresponding original feature parameters, and establish a mapping relationship between the original feature parameters and the corresponding optical performance detection dimensions and the target detection area; Step S300: Construct an optical performance detection hypergraph based on the mapping relationship, including spatial location nodes, performance dimension nodes, and signal feature nodes, as well as hyperedges that characterize the coupling relationship between nodes; Step S400: Input the optical performance detection hypergraph into the preset hypergraph neural network model, extract the high-order correlation features between nodes and eliminate the nonlinear coupling interference of multi-dimensional optical parameters to obtain the corrected target feature parameters, and output the comprehensive optical performance detection result of the dual-effect lens to be tested.

[0023] In this embodiment, the simultaneous acquisition of multi-dimensional optical parameters of all functional zones of the dual-effect lens can be achieved through the target detection area and the multi-dimensional synchronous detection beam. By using the optical performance detection hypergraph and the hypergraph neural network model, the nonlinear coupling interference of multi-dimensional optical parameters can be effectively eliminated, ensuring that the detection results truly reflect the comprehensive optical performance of the dual-effect lens. There is no need to separate the functional zones of the dual-effect lens for individual detection, nor is there a need to add an additional independent interference cancellation module. It can simultaneously take into account the spatial correlation of different functional zones of the dual-effect lens and the coupling characteristics of multi-dimensional parameters, ensuring both the operability and repeatability of the detection process, and achieving a balance between detection accuracy and detection efficiency. At the same time, it can flexibly adapt to different types of dual-effect lenses without redesigning the detection process for different lenses, thus meeting the comprehensive detection needs of dual-effect lenses.

[0024] In a specific implementation, as one example, given that the dual-effect lens has at least two sets of optical functional zones, and the optical characteristics of each functional zone differ, and multi-dimensional optical performance of each functional zone needs to be simultaneously detected and coupling interference eliminated, a target detection area matching at least two sets of optical functional zones of the dual-effect lens needs to be constructed to ensure effective simultaneous detection and interference elimination. This embodiment locates the lens optical reference based on preset design parameters and uses a gridding method adapted to the distribution characteristics of the functional zones to determine the target detection area, as detailed below: Step S110: Obtain the preset design parameters of the dual-effect lens to be tested, including refractive correction parameters, defocus control parameters, microlens array parameters, and functional coating design parameters. These four types of parameters jointly determine the optical function of the dual-effect lens and correspond to the core optical functional zones of the dual-effect lens. Among them, the refractive correction parameters directly determine the range and optical characteristics of the lens's refractive correction functional zones, and are used to delineate the detection range of the correction functional area. The defocus control parameters determine the distribution location and control intensity of the lens's defocus control functional zones, and are directly related to the sampling requirements of the defocus functional area. The microlens array parameters determine the distribution density and arrangement of the microlenses, and are used to locate the specific location of the corresponding microlens functional zones. The functional coating design parameters determine the effective working area of ​​functional coatings such as anti-reflective coatings and blue light blocking coatings on the lens surface. This area overlaps spatially with the lens's optical functional zones, and this parameter needs to be combined to ensure that the detection area covers the effective range of the coatings. The preset design parameters are obtained through multi-channel fusion. First, basic parameters are extracted from the production design documents of the dual-effect lens to be tested. These documents are provided by the lens manufacturer and contain standard values ​​of refractive correction parameters, defocus control parameters, microlens array parameters, and functional coating design parameters determined during the lens design phase. Secondly, the production batch information of the lenses is read through the lens traceability system, the actual production parameters of the lenses in that batch are matched, and the standard parameters in the design documents are calibrated to avoid parameter deviations caused by production errors. Finally, for some parameters that cannot be obtained from design documents and traceability systems, such as the microlens array parameters of some customized dual-effect lenses, a non-contact measurement method is used to obtain them. Specifically, the lens surface is scanned by optical measurement equipment to extract the distribution characteristics of the microlens array, the thickness and distribution range of the functional film layer, and then the corresponding parameters are determined. The above acquisition methods combine design standards, actual production, and measured data to ensure that the preset design parameters can truly reflect the actual design state of the dual-effect lens to be tested, so as to support the accurate division of the testing area. Step S120: Determine the optical center and effective optical boundary of the dual-effect lens to be tested using a visual positioning device. The optical center of the dual-effect lens is directly related to its own optical function, and the effective optical boundary is the range within which the lens can achieve normal optical function. The positioning of these two factors affects the accuracy of the detection area division. The visual positioning device has the advantages of non-contact, high precision, and rapid positioning, which can avoid damage to the lens surface caused by mechanical positioning, and at the same time, it can accurately capture the optical characteristics of the lens. The working process of the visual positioning device is as follows: Fix the dual-effect lens to be tested onto a special fixture, ensuring that the lens is horizontal and unobstructed; The image acquisition module of the vision positioning device simultaneously acquires images of the lens from both the front and side angles. An industrial camera can be used, with the acquisition frequency set to 50Hz to ensure the clarity and integrity of the acquired images. The image processing module preprocesses the acquired images, including grayscale conversion, noise reduction, edge enhancement, and other operations, to eliminate the interference of ambient light and reflections from the lens surface on the image. The physical boundaries of the lens are identified by an edge detection algorithm, and the optical feature extraction algorithm is used to capture the optical feature points of the lens, such as the optical refractive index change point in the central region of the lens. This feature point is determined as the optical center of the lens. Due to the functional partition design of dual-effect lenses, the optical center and the geometric center often do not coincide, so as to avoid misjudging the geometric center of the lens as the optical center. Based on the optical center, combined with the refractive correction parameters and effective optical range requirements in the preset design parameters, the areas without optical function at the edge of the lens are eliminated to determine the effective optical boundary of the lens. The determination of the effective optical boundary must ensure that all optical function zones are covered, while eliminating invalid areas at the edge to avoid redundant sampling. Step S130: Using the optical center as the origin, multiple concentric field-of-view rings are formed by polar coordinate gridding. Multiple sampling points are equidistantly set within each field-of-view ring, and all sampling points together constitute the target detection area. The optical functional zones of dual-effect lenses are mostly symmetrically distributed around the optical center, such as the refractive correction zone and the defocus control zone. Polar coordinate gridding can adapt to this symmetrical distribution feature, ensuring that each functional zone can be sampled uniformly. The polar coordinate gridding operation process is as follows: A polar coordinate system is established with the defined optical center as the origin. The polar axis of the polar coordinate system can be set arbitrarily to ensure the effective optical boundary of the covered lens. Based on the preset design parameters, determine the number of concentric field rings and the width of each field ring: Based on the defocus control parameters and microlens array parameters, the distribution range of the defocus functional zones and the microlens array is determined. This range is divided into several concentric field rings. The width of each field ring corresponds to the radial range of a functional zone, ensuring that each functional zone corresponds to at least one complete field ring, while avoiding overlap of field rings of different functional zones. Based on the refractive correction parameters and functional membrane design parameters, determine the number of sampling points within each field of view ring; increase the number of sampling points in areas where the optical characteristics of the functional zones change drastically, such as the microlens array distribution area; and reasonably reduce the number of sampling points in areas with relatively uniform optical characteristics, such as the central refractive correction area, to ensure that the distribution of sampling points matches the optical characteristics of the functional zones. The sampling points within each field of view ring are set at equal intervals, meaning that the angle between the lines connecting two adjacent sampling points and the origin is equal, ensuring the uniformity of sampling within each field of view ring and avoiding sampling blind spots. In this embodiment, by acquiring preset design parameters through multiple channels, the parameters are ensured to accurately reflect the actual design state of the lens, facilitating the division of the detection area and avoiding the disconnect between the detection area and functional partitions due to parameter deviations. Based on the core design parameters of the dual-effect lens, the optical reference of the lens is accurately obtained through visual positioning, achieving precise positioning of the optical center and effective optical boundary. A polar coordinate gridding method adapted to the symmetrical distribution characteristics of the functional partitions is adopted to match the sampling points with each optical functional partition. The division logic is highly consistent with the design logic and functional distribution of the lens, ensuring that all optical functional partitions can be fully and uniformly sampled. This avoids missing key points of functional partitions and reduces redundant sampling of non-functional areas, providing a prerequisite for eliminating nonlinear coupling interference of multi-dimensional optical parameters and improving the accuracy of detection results.

[0025] In some embodiments of the present invention, existing methods for acquiring multi-dimensional optical parameters typically employ a single-beam time-division incident and single-channel signal acquisition approach, i.e., sequential acquisition of probe beams of different detection dimensions. This sequential acquisition method leads to timing differences in the acquisition of optical parameters of different dimensions at the same sampling point, failing to reflect the true optical characteristics of the sampling point at the same moment. Furthermore, it is prone to additional detection errors due to factors such as minute lens displacement and ambient light fluctuations. In addition, it does not coordinate the control of multiple probe beams of different detection dimensions, nor does it establish a clear correlation between feature parameters and detection dimensions and detection areas, thus failing to establish an accurate mapping relationship and making it difficult to meet the requirements for multi-functional partitioned multi-dimensional optical performance testing of dual-effect lenses. To address the aforementioned issues, this embodiment utilizes a beam splitter and combiner to achieve coaxial, point-by-point synchronous incidence of multiple probe beams. It synchronously acquires feedback optical signals and extracts original feature parameters, thereby establishing a mapping relationship. This ensures that optical parameters of different dimensions at the same sampling point can be acquired simultaneously, avoiding timing deviations and additional detection errors. Specifically, the following operations are performed: Step S210: Configure multiple probe beams corresponding to different optical performance detection dimensions, ensuring that the multiple probe beams are coaxially and synchronously incident point-by-point through the beam splitting and combining component, and that the emission timing is synchronized. The probe beams include at least a refractive correction probe beam, a defocus performance probe beam, a spectral transmittance probe beam, and a surface reflectance performance probe beam. These four types of beams correspond to the four optical performance detection dimensions of the dual-effect lens, covering the detection requirements of the lens's main optical functions. Among them, the refractive correction probe beam is used to detect parameters related to the lens's refractive correction function, adapting to the refractive correction function zones of the dual-effect lens, and directly reflecting the lens's ability to refract and correct light. The defocus performance probe beam is used to detect parameters related to the lens's defocus control function, adapting to the defocus control function zones, and corresponding to the lens's characteristics related to the control effect of myopia progression. The spectral transmittance probe beam is used to detect the lens's ability to transmit light of different wavelengths, adapting to the spectral protection function corresponding to the functional coating layer, and reflecting the lens's spectral protection performance. The surface reflectance performance probe beam is used to detect the reflective characteristics of the lens surface, adapting to the anti-reflection function of the functional coating layer, and reflecting the lens's ability to reduce light reflection and improve visual comfort. The configuration of the multiple probe beams is as follows: a dedicated beam emitter is configured for each type of detection dimension, and the wavelength and intensity of the probe beam output by each beam emitter are adapted to the requirements of the corresponding detection dimension. For example, the refractive correction probe beam uses a visible light band beam, and the spectral transmittance probe beam uses a multi-band beam covering visible light, blue light, and ultraviolet light. The beam splitter and combiner adopts an optical fiber coupling structure, which can integrate multiple probe beams of different types into a single coaxial beam, ensuring that all probe beams can be accurately incident on the same sampling point in the target detection area, avoiding detection errors caused by different incident angles or incident position deviations. The emission timing synchronization uses a unified timing control method to coordinate the working states of each beam emitter and beam splitter / combiner component, ensuring that all probe beams are emitted and incident on the target detection area simultaneously. The synchronization accuracy of the emission timing can be set to 10μs, ensuring that multiple beams act on the same sampling point at the same time, avoiding parameter acquisition deviations caused by time-division incident, and ensuring that the acquired feedback signal can truly reflect the optical characteristics of the same sampling point under multi-dimensional detection. At the same time, according to the distribution order of sampling points in the target detection area, the coaxial probe beam is sequentially incident on each sampling point in a point-by-point scanning manner. The scanning frequency can be set to 50Hz, ensuring that each sampling point can be synchronously illuminated by multiple probe beams, and that the scanning process is without omission or repetition. Step S220: Synchronously acquire feedback optical signals from each sampling point; adopt an acquisition method that corresponds one-to-one with the detection dimension of the probe beam, and configure a dedicated acquisition unit for each detection dimension to ensure that feedback signals from different dimensions can be acquired synchronously and stored separately to avoid signal confusion; each acquisition unit includes a photodetector, a signal amplifier, and a filtering unit. The photodetector is used to convert the feedback optical signal into an electrical signal, the signal amplifier is used to amplify the weak electrical signal, and the filtering unit is used to filter interference signals such as ambient light and circuit noise to ensure that the acquired electrical signal can truly reflect the characteristics of the feedback optical signal; During the acquisition process, when multiple coaxial probe beams are incident on a sampling point in the target detection area, the lens generates a corresponding optical response to each probe beam, forming a feedback optical signal. The photodetector corresponding to each detection dimension synchronously captures the feedback optical signal of the corresponding dimension, converts it into an electrical signal, and transmits it to the signal amplifier of the corresponding acquisition unit for amplification. Then, the interference signal is filtered by the filtering unit to obtain a clean electrical signal. The processed electrical signal is classified and stored according to the sampling point number and detection dimension, and the acquisition time is recorded to ensure that the feedback signal of each sampling point and each detection dimension can be traced. During the acquisition process, the sampling frequency of each acquisition unit is controlled to match the scanning frequency of the probe beam to ensure that the feedback signal of each sampling point can be completely acquired without signal loss. Step S230: Extract the corresponding original feature parameters from the acquired feedback optical signal; The original characteristic parameters of the refractive correction dimension include spherical power, cylindrical power, and root mean square error of the wavefront. The extraction method is as follows: from the feedback electrical signal of the refractive correction probe beam, the change in the refraction angle of the beam after passing through the lens is analyzed. Combined with the incident characteristics of the beam, the spherical power and cylindrical power are extracted to characterize the lens's refractive correction ability. Through wavefront sensing technology, the wavefront distortion of the feedback beam is analyzed, and the root mean square error of the wavefront is extracted to characterize the uniformity of the lens's refractive correction. The original characteristic parameters of the defocus control dimension include defocus amount and microlens optical efficiency. The extraction method is as follows: from the feedback electrical signal of the defocus performance detection beam, the focusing offset of the beam after passing through the defocus functional zone of the lens is analyzed to extract the defocus amount, which is used to characterize the defocus control strength of the lens; by analyzing the intensity distribution of the feedback signal and combining it with the design distribution characteristics of the microlens, the effective ratio of the microlens to the detection beam is calculated to extract the microlens optical efficiency, which is used to characterize the actual working effect of the microlens array. The original characteristic parameters of the spectral protection dimension include visible light transmittance, blue light blocking rate, and ultraviolet light blocking rate. The extraction method is as follows: from the feedback electrical signal of the spectral transmittance detection beam, the signal intensity of different wavelength bands is separated, and the signal transmission ratio of the visible light band, blue light band, and ultraviolet light band is calculated to obtain the visible light transmittance, blue light blocking rate, and ultraviolet light blocking rate, which are used to characterize the lens's ability to transmit and block light of different wavelengths. The original characteristic parameters of the antireflection performance dimension include the average visible light reflectance and the diffuse reflection ratio. The extraction method is as follows: from the feedback electrical signal of the surface reflectance performance probe beam, the specular reflection signal and the diffuse reflection signal are separated. The ratio of the average intensity of the reflected signal in the visible light band to the intensity of the incident signal is calculated to obtain the average visible light reflectance. The proportion of the diffuse reflection signal intensity to the total reflection signal intensity is calculated to obtain the diffuse reflection ratio, which is used to characterize the antireflection effect of the lens surface. After all the original feature parameters are extracted, their validity is verified, outliers are removed, and the original feature parameters are ensured to truly reflect the optical performance of the lens. Step S240: Establish the mapping relationship between the original feature parameters and the corresponding optical performance detection dimensions and target detection areas; the mapping relationship is established using the sampling points of the target detection area as the association points, and is implemented by data association modeling to ensure that each original feature parameter can be clearly mapped to a specific detection dimension and a specific sampling point. The implementation method is as follows: Each sampling point is assigned a unique location identifier, recording its coordinates within the target detection area; each detection dimension is assigned a unique dimension identifier, clarifying its corresponding original feature parameter type; the location identifier, dimension identifier, and corresponding original feature parameter are associated and stored to form a three-dimensional mapping table, where the horizontal axis represents the sampling point location identifier, the vertical axis represents the detection dimension identifier, and the table content represents the corresponding original feature parameter values; simultaneously, parameter traceability information is embedded in the mapping relationship, including the feedback signal acquisition time, probe beam emission parameters, signal processing parameters, etc., corresponding to the original feature parameter, ensuring that the original feature parameter can be traced back to the specific acquisition and processing stage during retrieval, verification, and analysis.

[0026] In this embodiment, to meet the requirement of multi-dimensional optical performance testing of dual-effect lenses, a detection beam corresponding to the optical performance testing dimension is configured. Multiple detection beams are integrated into a coaxial beam using a beam splitter and combiner. Unified timing control is used to achieve synchronous point-to-point incidence of multiple beams. Feedback optical signals are collected and processed in a one-to-one correspondence with the testing dimension. The original feature parameters of each dimension are extracted from the signals and their validity is verified. Finally, a mapping relationship between the original feature parameters and the testing dimension and target testing area is established to support the overall analysis and result output of optical performance. This ensures that the testing process is operable and repeatable, and truly reflects the optical performance of each functional zone of the dual-effect lens.

[0027] In a specific implementation, as one example, existing methods for processing the correspondence between feature parameters and detection dimensions and detection areas typically employ simple data association, failing to systematically characterize the coupling relationships between parameters. This approach only reflects parameter information at a single dimension and location, unable to capture higher-order relationships between spatial location, performance dimensions, and signal characteristics, and also unable to distinguish different types of coupling interference sources. This embodiment constructs an optical performance detection hypergraph based on the mapping relationship between feature parameters and corresponding optical performance detection dimensions and target detection areas. By characterizing the coupling relationships between various elements, the hypergraph neural network model can extract higher-order correlation features, thereby eliminating nonlinear coupling interference. The specific implementation steps are as follows: Step S310: Construct the nodes of the optical performance detection hypergraph, including spatial location nodes, performance dimension nodes, and signal feature nodes. The construction of the three types of nodes is based on the mapping relationship. Each node is assigned a unique identifier and associated with traceability information. The construction of spatial location nodes uses each sampling point in the target detection area as an independent spatial location node. The coordinate information of the sampling point, the optical functional zone identifier, and the identifiers of all corresponding original feature parameters are extracted from the mapping relationship to complete the binding of node association information. The optical parameters of different sampling points of the dual-effect lens are different, and the sampling points in the same functional zone have spatial correlation. The construction of nodes separately can accurately locate the optical characteristics of each position for spatial coupling correlation characterization. The performance dimension nodes are constructed with refractive correction, defocus control, spectral protection, and antireflection optical performance testing dimensions as independent performance dimension nodes. Each node is associated with all original feature parameter types of the corresponding dimension, as well as the spatial location node identifier of all sampling points under that dimension. These four types of optical performance testing dimensions cover the core optical functions of dual-effect lenses, and there is nonlinear coupling interference between parameters of different dimensions. Constructing nodes separately can clarify the association boundary of parameters of each dimension and be used for identification of dimensional coupling interference. The construction of signal feature nodes uses each original feature parameter as an independent signal feature node. Each node is associated with a corresponding performance dimension node identifier, a spatial location node identifier, and traceability information such as feedback signal acquisition time and signal processing parameters. Each parameter corresponds to the specific optical performance of the lens and is the basic unit for characterizing the comprehensive performance. There is a coupling relationship between different signal feature nodes. Constructing nodes separately can accurately capture the relationship between parameters and provide a target for eliminating signal coupling interference. Step S320: Construct the hyperedges of the optical performance detection hypergraph, including spatially coupled hyperedges, dimensionally coupled hyperedges, signal coupled hyperedges, and cross-domain coupled hyperedges. Each type of hyperedge connects multiple corresponding nodes with coupling relationships. The construction of the spatial coupling hyperedge is based on the functional partition identifier of the sampling points in the mapping relationship. All spatial location nodes within the same optical functional partition are connected by a spatial coupling hyperedge, and spatial location nodes in different functional partitions are connected by independent spatial coupling hyperedges. The optical parameters of the sampling points within the same functional partition of the dual-effect lens have a spatial distribution pattern. This hyperedge can accurately characterize this spatial correlation and is used to identify spatial dimensional coupling interference. The construction of the dimensional coupling hyperedge is based on the optical properties of the dual-effect lens and the physical meaning of the original feature parameters. Signal feature nodes under different performance dimension nodes with coupling correlation are connected by a dimensional coupling hyperedge. For example, the spherical power node of the refractive correction dimension and the defocus amount node of the defocus control dimension, and the blue light blocking rate node of the spectral protection dimension and the visible light average reflectance node of the antireflection performance dimension are all connected by the dimensional coupling hyperedge. Nonlinear coupling interference between multi-dimensional detection parameters is the core factor affecting detection accuracy. This hyperedge can clarify the coupling correlation between different dimensional parameters and is used to specifically eliminate inter-dimensional coupling interference. The construction of the signal coupling hyperedge is based on the performance dimension identifier of the signal feature nodes. All signal feature nodes under the same performance dimension are connected by a signal coupling hyperedge. For example, the three signal feature nodes of spherical power, cylindrical power, and root mean square error of wavefront under the refractive correction dimension are connected by a signal coupling hyperedge, and the three types of original feature parameter nodes under the spectral protection dimension are connected by another signal coupling hyperedge. Different original feature parameters under the same performance dimension are used to characterize the optical performance of that dimension. There is an inherent correlation between the parameters. The hyperedge can characterize the coupling relationship between the parameters within the same dimension and avoid incomplete interference elimination. The construction of the cross-domain coupling hyperedge is based on the numerical correlation of each signal feature parameter in the mapping relationship and the synergistic characteristics of the optical functions of the dual-effect lens. Signal feature nodes that have coupling correlations across optical functional zones and performance dimensions are connected by a cross-domain coupling hyperedge. For example, the microlens optical efficiency node in the defocus control functional zone and the wavefront root mean square error node in the refractive correction functional zone, and the ultraviolet light blocking rate node in the spectral protection functional zone and the diffuse reflection ratio node in the antireflection functional zone are all connected by the cross-domain coupling hyperedge. The optical parameters of different functional zones and different performance dimensions of the dual-effect lens have cross-domain synergistic effects. This hyperedge can capture such cross-domain coupling correlations and ensure that the characterization of coupling interference is not missed. Step S330: Integrate nodes and hyperedges to form a complete optical performance testing hypergraph; assign unique identifiers to all nodes and hyperedges, clarify the type of hyperedge, the identifiers of the connected nodes, and the basis for association, and establish a hypergraph association index to enable queryable and traceable association relationships between nodes and hyperedges; conduct association rationality verification during the integration process, and eliminate hyperedges with incorrect associations, such as avoiding connecting spatial location nodes of different functional zones through the same spatial coupling hyperedge, and avoiding connecting signal feature nodes without coupling associations through dimensional coupling hyperedges, to ensure that the hypergraph truly and accurately represents the coupling association characteristics of the optical parameters of dual-effect lenses.

[0028] In this embodiment, based on the established mapping relationship between feature parameters and detection dimensions and target detection areas, spatial location nodes, performance dimension nodes, and signal feature nodes are constructed. Spatial coupling hyperedges, dimensional coupling hyperedges, signal coupling hyperedges, and cross-domain coupling hyperedges are constructed in categories. After integration and verification, a complete optical performance detection hypergraph is formed. This hypergraph accurately locates the core elements of dual-effect lens detection through three types of nodes and comprehensively represents different types of coupling relationships through four types of hyperedges. The construction of all nodes and hyperedges corresponds to clear optical characteristics and mapping relationships, ensuring that the characterization results are true and accurate. It can clearly present the coupling characteristics of the optical parameters of dual-effect lenses and adapt to the needs of multi-dimensional optical performance detection of dual-effect lenses.

[0029] In a specific implementation, as one example, existing conventional neural network models cannot adapt to complex coupling relationships, struggle to extract high-order correlation features, and cannot specifically eliminate coupling interference, resulting in insufficient detection accuracy. Therefore, it is necessary to construct a hypergraph neural network model adapted to the detection requirements of dual-effect lenses to achieve high-order correlation feature extraction, coupling interference elimination, and accurate detection result output. This embodiment constructs a hypergraph neural network model containing a feature encoding layer, a cascaded hypergraph convolution module, an interference correction branch, and a comprehensive evaluation branch. The optical performance detection hypergraph is input into the model to complete feature extraction, interference elimination, and result output. The specific implementation steps are as follows: Step S410: Construct a hypergraph neural network model, which includes a feature encoding layer, a cascaded hypergraph convolution module, an interference correction branch, and a comprehensive evaluation branch; The feature encoding layer is constructed using the optical performance detection hypergraph as input. It transforms the attribute information of spatial location nodes, performance dimension nodes, and signal feature nodes into vector forms that the model can recognize, thereby achieving digital encoding of node features. The encoding process does not introduce complex calculations; it only performs linear transformations on node identifiers, relationships, and parameter information to ensure that the encoded feature vectors accurately correspond to the original node information. The role of this layer is to transform the node and hyperedge information of the hypergraph into digital signals that the model can process, avoiding the loss or distortion of node information. The cascaded hypergraph convolution module consists of at least three hypergraph convolutional layers with a hyperedge attention mechanism. Each convolutional layer corresponds to different types of coupling and association extraction. The hyperedge attention mechanism can automatically identify the association strength between nodes, distinguish the association weights of spatial coupling, dimensional coupling, signal coupling, and cross-domain coupling, and prioritize the extraction of node features with high association and weaken the interference of unrelated nodes. The construction of this module is based on the coupling characteristics of a dual-effect lens. Different coupling types have different association strengths. The feature extraction is deepened step by step through multiple convolutions to ensure the integrity of high-order association features. The interference correction branch is used to fit and eliminate nonlinear coupling interference of multi-dimensional optical parameters. It adopts a hierarchical correction method and establishes correction models for four different types of interference: spatial coupling, dimensional coupling, signal coupling, and cross-domain coupling. The correction process is based on the coupling correlation information in the hypergraph, and the parameters of each signal feature node are corrected to eliminate parameter deviations caused by coupling interference. This ensures that the corrected feature parameters can truly reflect the actual optical performance of the lens and avoids detection errors caused by unresolved interference. Based on the multi-zone and multi-dimensional characteristics of dual-effect lenses, this branch achieves precise elimination of coupling interference through a dedicated correction branch. The comprehensive evaluation branch is used to convert the corrected target feature parameters into optical performance test results that can be directly output. Its output content corresponds to the test requirements of dual-effect lenses, including the individual performance test values ​​of each sampling point, the parameter deviation values ​​of each functional zone, the pass / fail judgment results of the entire lens, the comprehensive performance score and performance level. Each output content corresponds to a clear node feature and the corrected parameters. During model training, the extracted original feature parameters and hypergraph association information are used as the training basis to adjust the model's hyperparameters, complete the model adaptation and training, enable the model to accurately identify different types of coupling interference, adapt to the optical characteristics of the dual-effect lens, and adjust the parameters in a repeatable and verifiable manner during the training process to ensure the stability of the model output. Step S420: Input the optical performance detection hypergraph into the hypergraph neural network model. During the input process, verify the node and hyperedge information of the hypergraph, remove invalid association information, and ensure that the hypergraph structure of the input model is complete and the association is accurate, so as to avoid model processing deviation due to incorrect input information. Step S430: Extract high-order correlation features between nodes to eliminate nonlinear coupling interference of multi-dimensional optical parameters; through the cascaded hypergraph convolution module, deeply mine the node and hyperedge correlation information in the hypergraph to extract high-order correlation patterns between different nodes, including the correlation of spatial nodes within the same functional zone, the correlation of nodes in different performance dimensions, and the cross-domain correlation of nodes in different functional zones, forming a complete high-order correlation feature set; for the extracted high-order correlation features, combined with the interference correction branch, correct the original feature parameters of each performance dimension, specifically as follows: To address spatial coupling interference, the parameter deviation of the sampling point is corrected by combining the correlation information of spatial location nodes; To address dimensional coupling interference, the parameter interference between different dimensions is corrected by considering the correlation between performance dimension nodes. To address signal coupling interference, the mutual interference between parameters is corrected by combining the properties of signal characteristic nodes; To address cross-domain coupling interference, cross-partition correlation information is combined to correct parameter deviations between different functional partitions, ultimately obtaining corrected target feature parameters to ensure that the parameters can truly reflect the actual optical characteristics of the dual-effect lens. Step S440: Based on the corrected target feature parameters, output the comprehensive optical performance test results of the dual-effect lens to be tested, clarifying the corresponding basis of each test result; the individual performance test value of each sampling point corresponds to the original feature parameters of each performance dimension, reflecting the specific optical performance of that point; the design deviation value is derived based on the comparison results between the corrected parameters and the preset design parameters, reflecting the difference between the actual performance of the lens and the design requirements; the qualification judgment result is derived based on the individual performance test values ​​and the design deviation value, combined with the performance standards of the dual-effect lens, clarifying whether the lens meets the usage requirements; the overall lens performance score is calculated by combining the individual performance of each sampling point and the design deviation value, intuitively reflecting the overall optical performance of the lens; the performance level is divided according to the overall performance score, used to quickly judge the performance level of the lens.

[0030] In this embodiment, a dedicated hypergraph neural network model is constructed, and the optical performance detection hypergraph is input into the model. After model adaptation training, high-order correlation feature extraction, and nonlinear coupling interference correction, the final output is the comprehensive optical performance detection result of the dual-effect lens. The structure of each layer of the model is in line with the multi-zone and multi-dimensional detection requirements of the dual-effect lens, realizing the accurate capture of multi-type coupling correlation and targeted interference elimination, which can comprehensively reflect the comprehensive optical performance of the dual-effect lens.

[0031] Based on the same inventive concept as the optical performance testing method and system for dual-effect lenses described in the foregoing embodiments, this invention also provides an optical performance testing system for dual-effect lenses, such as... Figure 2 As shown, the system includes: The region determination module is used to determine the target detection region that matches at least two sets of optical functional zones of the dual-effect lens under test, based on the preset design parameters of the dual-effect lens under test. The detection and acquisition module is used to simultaneously emit multiple detection beams corresponding to different optical performance detection dimensions into the target detection area, acquire feedback optical signals and extract corresponding original feature parameters, and establish a mapping relationship between the original feature parameters and the corresponding optical performance detection dimensions and the target detection area. The hypergraph construction module is used to construct an optical performance detection hypergraph based on mapping relationships, including spatial location nodes, performance dimension nodes, and signal feature nodes, as well as hyperedges that characterize the coupling relationships between nodes; The result output module is used to input the optical performance detection hypergraph into a preset hypergraph neural network model, extract high-order correlation features between nodes and eliminate nonlinear coupling interference of multi-dimensional optical parameters to obtain the corrected target feature parameters, and output the comprehensive optical performance detection results of the dual-effect lens to be tested.

[0032] The system described above in this invention can effectively realize the optical performance testing method applied to dual-effect lenses, and the technical effects it can achieve are as described in the above embodiments, and will not be repeated here.

[0033] Although this application has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of this application. Accordingly, this specification and drawings are merely exemplary illustrations of the application as defined herein, and are to be considered as covering any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Thus, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A method for testing the optical performance of dual-effect lenses, characterized in that, include: Based on the preset design parameters of the dual-effect lens to be tested, the target detection area that matches at least two sets of optical functional zones of the dual-effect lens to be tested is determined. Multiple detection beams corresponding to different optical performance detection dimensions are simultaneously emitted into the target detection area. Feedback optical signals are collected and corresponding original feature parameters are extracted. A mapping relationship between the original feature parameters and the corresponding optical performance detection dimensions and the target detection area is established. An optical performance detection hypergraph is constructed based on the mapping relationship, including spatial location nodes, performance dimension nodes, and signal feature nodes, as well as hyperedges that characterize the coupling and correlation between nodes. The optical performance detection hypergraph is input into a preset hypergraph neural network model, high-order correlation features between nodes are extracted and nonlinear coupling interference of multi-dimensional optical parameters is eliminated to obtain the corrected target feature parameters, and the comprehensive optical performance detection result of the dual-effect lens to be tested is output.

2. The optical performance testing method for dual-effect lenses according to claim 1, characterized in that, The method for determining the target detection region includes: The refractive correction parameters, defocus control parameters, microlens array parameters, and functional film design parameters of the dual-effect lens to be tested are obtained as preset design parameters. Determine the optical center and effective optical boundary of the lens; Using the optical center as the origin, multiple concentric field-of-view rings are formed by polar coordinate gridding. Multiple sampling points are set at equal intervals within each field-of-view ring, and all sampling points within each field-of-view ring together constitute the target detection area.

3. The optical performance testing method for dual-effect lenses according to claim 2, characterized in that, The acquisition of the preset design parameters includes: Extract standard values ​​of refractive correction parameters, defocus control parameters, microlens array parameters, and functional film design parameters from the production design documents; The production batch information is read through the lens traceability system to obtain the actual production parameters and calibrate the standard values. For parameters that cannot be obtained from design documents and traceability systems, non-contact optical measurement equipment is used to scan the lens surface to extract the distribution characteristics of the microlens array and the thickness and distribution range of the functional film as supplementary parameters.

4. The optical performance testing method for dual-effect lenses according to claim 2, characterized in that, The detection beam includes at least a refractive correction detection beam, a defocus performance detection beam, a spectral transmittance detection beam, and a surface reflectance performance detection beam; Multiple probe beams are synchronously incident point-by-point on the same axis through a beam splitter and combiner assembly, and the emission timing is synchronized.

5. The optical performance testing method for dual-effect lenses according to claim 4, characterized in that, The beam splitter and combiner uses an optical fiber coupled structure to integrate the refractive correction detection beam, defocus performance detection beam, spectral transmittance detection beam, and surface reflectance performance detection beam into a single coaxial detection beam.

6. The optical performance testing method for dual-effect lenses according to claim 5, characterized in that, The original feature parameters include: Sphere power, cylinder power, and root mean square error of wavefront in the refractive correction dimension; Defocusing amount and microlens optical efficiency in the defocusing control dimension; Visible light transmittance, blue light blocking rate, and ultraviolet light blocking rate in the spectral protection dimension; The visible light average reflectance and diffuse reflection ratio are dimensions of antireflectivity.

7. The optical performance testing method for dual-effect lenses according to claim 1, characterized in that, The hyperedges include spatially coupled hyperedges, dimensionally coupled hyperedges, signal coupled hyperedges, and cross-domain coupled hyperedges. Each type of hyperedge connects multiple corresponding nodes with coupling relationships.

8. The optical performance testing method for dual-effect lenses according to claim 7, characterized in that, The hypergraph neural network model includes a feature encoding layer, a cascaded hypergraph convolution module, an interference correction branch, and a comprehensive evaluation branch. The feature encoding layer is used to linearly encode the node features of the hypergraph to generate an initial node embedding vector; The cascaded hypergraph convolutional module includes at least three hypergraph convolutional layers with hyperedge attention mechanisms, used to extract high-order association features of nodes; The interference correction branch is used to fit and eliminate nonlinear coupling interference, and outputs the corrected target feature parameters. The comprehensive evaluation branch is used to output the optical performance test results.

9. The optical performance testing method for dual-effect lenses according to claim 8, characterized in that, The optical performance test results include individual performance test values ​​at each sampling point, design deviation values, pass / fail results, overall lens performance score and performance level.

10. An optical performance testing system for dual-effect lenses, characterized in that, include: The region determination module is used to determine the target detection region that matches at least two sets of optical functional zones of the dual-effect lens under test, based on the preset design parameters of the dual-effect lens under test. The detection and acquisition module is used to simultaneously emit multiple detection beams corresponding to different optical performance detection dimensions to the target detection area, acquire feedback optical signals and extract corresponding original feature parameters, and establish a mapping relationship between the original feature parameters and the corresponding optical performance detection dimensions and the target detection area; The hypergraph construction module is used to construct an optical performance detection hypergraph based on the mapping relationship, including spatial location nodes, performance dimension nodes, and signal feature nodes, as well as hyperedges that characterize the coupling relationship between nodes; The result output module is used to input the optical performance detection hypergraph into a preset hypergraph neural network model, extract high-order correlation features between nodes and eliminate nonlinear coupling interference of multi-dimensional optical parameters to obtain the corrected target feature parameters, and output the comprehensive optical performance detection result of the dual-effect lens to be tested.

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