Spherical optical lens three-dimensional contour detection method and system

Abstract

The invention discloses a spherical optical lens three-dimensional contour detection method and system, and relates to the technical field of optical precision detection, and the method comprises the steps: transmitting a detection laser beam to a spherical optical lens, and collecting a non-linear optical characteristic signal penetrating through a coating layer and a polarized optical characteristic signal of a reflective coating layer through dynamically adjusting the incident angle of the detection laser beam; based on the nonlinear optical characteristic signals, generating substrate curvature space distribution data through a curvature inversion algorithm, and extracting thickness distribution characteristics of a coating layer and substrate surface optical response characteristics through a polarization characteristic analysis technology; correcting substrate curvature space distribution data through a refractive index compensation algorithm, and performing weighted fusion on thickness distribution characteristics of a coating layer and substrate surface optical response characteristics to generate a three-dimensional point cloud coordinate set; according to the method, the reconstruction precision of substrate curvature distribution is effectively improved; and analysis of real optical characteristics of the surface of the substrate is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of optical precision detection, and in particular to a method and system for detecting the three-dimensional profile of a spherical optical lens. Background Art

[0002] The widespread application of optical imaging systems in industrial inspection, aerospace, biomedicine, and other fields has placed increasingly stringent demands on the geometric accuracy and surface quality of optical components. As one of the core components of optical systems, the three-dimensional profile accuracy of spherical optical lenses directly affects the optical path transmission characteristics and imaging quality. In recent years, non-contact measurement technologies based on laser interferometry, confocal scanning, and structured light projection have gradually become mainstream and are widely used in the topography inspection of optical components. In particular, high-precision instruments such as laser scanning confocal microscopes (LSCMs) and white light interferometers (WLIs) have demonstrated excellent performance in submicron surface topography characterization.

[0003] There are two major problems in the existing technology: first, the presence of the coating layer affects the penetration and reflection characteristics of the optical signal, resulting in the inability of traditional detection methods to effectively separate the optical response of the coating layer and the substrate, thereby causing errors in the calculation of the curvature radius; second, the thermal deformation caused by changes in ambient temperature is not fully compensated. Especially in high-precision detection scenarios, tiny temperature fluctuations can cause significant measurement deviations. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a method for detecting the three-dimensional profile of a spherical optical lens to solve the problem of reduced measurement accuracy caused by signal interference and thermal deformation of the coating layer in the prior art.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, the present invention provides a three-dimensional contour detection method for a spherical optical lens, comprising: emitting a detection laser beam to the spherical optical lens, and collecting a nonlinear optical characteristic signal penetrating the coating layer and a polarization optical characteristic signal reflecting the coating layer by dynamically adjusting the incident angle of the detection laser beam; generating substrate curvature spatial distribution data through a curvature inversion algorithm based on the nonlinear optical characteristic signal, and extracting the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface through a polarization characteristic analysis technology; correcting the substrate curvature spatial distribution data through a refractive index compensation algorithm, and weightedly fusing the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface to generate a three-dimensional point cloud coordinate set; real-time monitoring of the temperature field distribution on the surface of the spherical optical lens, performing thermal deformation compensation on the three-dimensional point cloud coordinate set, and generating a three-dimensional contour detection report after surface fitting and topological defect analysis.

[0007] As a preferred embodiment of the spherical optical lens three-dimensional profile detection method of the present invention, the specific steps of emitting a detection laser beam toward the spherical optical lens and collecting the nonlinear optical characteristic signal of the penetrating coating layer and the polarized optical characteristic signal of the reflecting coating layer by dynamically adjusting the incident angle of the detection laser beam are as follows: emitting a detection laser beam of a first wavelength toward the surface area of the spherical optical lens, and collecting a nonlinear optical characteristic signal generated by penetrating the coating layer by dynamically adjusting the incident angle of the detection laser beam to a first optimized angle; A detection laser beam of a second wavelength is emitted to the same surface area of the spherical optical lens. By dynamically adjusting the incident angle of the detection laser beam to a second optimized angle, the polarized optical characteristic signal reflected by the coating layer is collected.

[0008] As a preferred solution of the spherical optical lens three-dimensional profile detection method of the present invention, wherein: the base curvature spatial distribution data is generated by the curvature inversion algorithm based on the nonlinear optical characteristic signal, and the specific steps are as follows: Perform signal band separation processing on the nonlinear optical characteristic signal to extract the substrate characteristic response component that penetrates the coating layer, and use a window function to suppress the noise reflected by the coating layer to generate the nonlinear optical response component; Based on the nonlinear optical response component, the local curvature radius of the substrate is calculated using the curvature inversion algorithm to construct the initial spatial distribution model of the substrate curvature. According to the initial spatial distribution model, the gradient-signal-to-noise ratio joint optimization algorithm is used to correct the base curvature distribution deviation value of the annular area at the edge of the spherical optical lens, and generate the base curvature spatial distribution data.

[0009] As a preferred solution of the spherical optical lens three-dimensional profile detection method of the present invention, wherein: the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface are extracted by polarization feature analysis technology, the specific steps are as follows: Perform polarization state separation on the nonlinear optical response components and extract the full polarization response data of the coupling between the coating layer and the substrate; Based on the full polarization response data, the thickness distribution characteristics of the coating layer are extracted through polarization harmonic coherence analysis, and the transmission matrix of the coating layer is constructed; According to the transmission matrix of the coating layer, the optical response component of the coating layer is stripped from the full polarization response data to obtain the optical response characteristics of the substrate surface.

[0010] As a preferred solution of the spherical optical lens three-dimensional contour detection method of the present invention, wherein: the generating of the three-dimensional point cloud coordinate set is carried out in the following specific steps: Applying a refractive index compensation algorithm to the base curvature spatial distribution data to generate corrected base curvature data; Based on the corrected substrate curvature data, the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface are spatially fused using a weighted fusion algorithm to generate a comprehensive feature dataset of the substrate morphology. Perform three-dimensional point cloud mapping on the comprehensive feature data set of the base morphology to generate a three-dimensional point cloud coordinate set.

[0011] As a preferred solution of the spherical optical lens three-dimensional profile detection method of the present invention, wherein: the temperature field distribution of the spherical optical lens surface is monitored in real time, and thermal deformation compensation is performed on the three-dimensional point cloud coordinate set. The specific steps are as follows: The temperature field distribution data of the spherical optical lens surface is collected in real time by an infrared thermal imager, and the temperature field distribution data is spatially differentiated by a two-dimensional discrete gradient operator to generate a temperature gradient matrix. Based on the temperature gradient matrix, the thermal deformation compensation coefficient is calculated through the thermal-optical coupling model, and the three-dimensional point cloud coordinate set is corrected for thermal expansion pixel by pixel to generate the thermally compensated three-dimensional point cloud coordinates.

[0012] As a preferred solution of the spherical optical lens three-dimensional profile detection method of the present invention, wherein: after the surface fitting and topological defect analysis, a three-dimensional profile detection report is generated, the specific steps are as follows: Perform Zernike polynomial surface fitting on the three-dimensional point cloud coordinate set after thermal compensation to generate an ideal reference surface and calculate the surface deviation; Based on the surface deviation, the geometric features of surface defects are identified through morphological image processing algorithms, and compared with the preset defect judgment threshold to generate defect classification statistics; The ideal reference surface, surface deviation and defect classification statistics are integrated to generate a 3D contour inspection report.

[0013] In a second aspect, the present invention provides a three-dimensional contour detection system for a spherical optical lens, comprising a laser acquisition module, a signal decoupling module, a point cloud generation module and a thermal compensation analysis module, wherein the laser acquisition module is used to emit a detection laser beam to the spherical optical lens, and collect the nonlinear optical characteristic signal of the penetrating coating layer and the polarization optical characteristic signal of the reflecting coating layer by dynamically adjusting the incident angle of the detection laser beam; the signal decoupling module is used to generate substrate curvature spatial distribution data based on the nonlinear optical characteristic signal through a curvature inversion algorithm, and extract the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface through polarization characteristic analysis technology; the point cloud generation module is used to correct the substrate curvature spatial distribution data through a refractive index compensation algorithm, and weightedly fuse the thickness distribution characteristics of the penetrating coating layer and the optical response characteristics of the substrate surface to generate a three-dimensional point cloud coordinate set; the thermal compensation analysis module is used to monitor the temperature field distribution on the surface of the spherical optical lens in real time, compensate for thermally induced deformation of the three-dimensional point cloud coordinate set, and generate a three-dimensional contour detection report after surface fitting and topological defect analysis.

[0014] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the spherical optical lens three-dimensional profile detection method as described in the first aspect of the present invention is implemented.

[0015] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the method for detecting the three-dimensional profile of a spherical optical lens as described in the first aspect of the present invention is implemented.

[0016] The beneficial effects of the present invention are as follows: by implementing frequency band separation and window function noise reduction processing on the nonlinear optical response components, combined with the curvature inversion algorithm and the gradient-signal-to-noise ratio joint optimization strategy, the reconstruction accuracy of the substrate curvature distribution is effectively improved; further, the polarization harmonic coherence analysis method is used to extract the thickness distribution of the coating layer, and the influence of the coating layer on the optical response of the substrate is stripped based on the transmission matrix, thereby realizing the analysis of the true optical properties of the substrate surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 The flowchart of the 3D profile detection method for a spherical optical lens is shown in FIG.

[0019] Figure 2 The flowchart of the detection laser beam collection and signal acquisition for the 3D contour detection method of spherical optical lenses.

[0020] Figure 3 Flowchart of optical signal decoupling and feature extraction for 3D contour detection method of spherical optical lens.

[0021] Figure 4 Flowchart of 3D point cloud generation and thermal compensation analysis for 3D profile detection method of spherical optical lens. DETAILED DESCRIPTION

[0022] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0023] 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. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0024] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0025] Reference Figures 1 to 4 , is an embodiment of the present invention, which provides a method for detecting the three-dimensional profile of a spherical optical lens, comprising the following steps: S1: Launch a detection laser beam to the spherical optical lens, and collect the nonlinear optical characteristic signals penetrating the coating layer and the polarization optical characteristic signals reflecting the coating layer by dynamically adjusting the incident angle of the detection laser beam.

[0026] S1.1: Emit a probe laser beam of a first wavelength toward the surface area of the spherical optical lens, dynamically adjust the incident angle of the probe laser beam to a first optimized angle, and collect nonlinear optical characteristic signals generated by penetrating the coating layer.

[0027] The specific process includes: when emitting a detection laser beam of a first wavelength to the surface area of the spherical optical lens, a tunable laser is used to output a detection laser beam of a specific wavelength, and the incident angle of the detection laser beam is dynamically adjusted to a first optimized angle through a precision rotating platform, so that the detection laser beam passes through the coating layer of the spherical optical lens under optimal penetration conditions; during the penetration process, the detection laser beam undergoes nonlinear optical interaction with the substrate material of the spherical optical lens, generating characteristic signals including nonlinear optical effects such as second harmonics and sum frequency; a high-sensitivity photodetector array is used to receive the nonlinear optical characteristic signals after penetrating the coating layer, and the detector array synchronously collects signal intensity and phase information according to the spatial coordinate distribution; during the acquisition process, bandpass filtering technology is used to separate the target nonlinear optical characteristic signals, and phase-locked amplification technology is used to improve the signal-to-noise ratio; finally, the nonlinear optical characteristic signals are obtained.

[0028] The first optimization angle is to conduct spectral response tests and transmittance experiments on the coating layer material of the spherical optical lens, combine the functional relationship curve between the nonlinear optical signal intensity and the incident angle, and select the incident angle that maximizes the signal-to-noise ratio of the nonlinear optical characteristic signal as the first optimization angle.

[0029] The optimal penetration condition is the combination of incident angle and wavelength that maximizes the signal-to-noise ratio of the nonlinear optical characteristic signal, based on the material properties of the spherical optical lens coating layer and the nonlinear optical response characteristics of the substrate material, through experimental calibration.

[0030] S1.2: Emit a second wavelength of a probe laser beam to the same surface area of the spherical optical lens, and dynamically adjust the incident angle of the probe laser beam to a second optimized angle to collect the polarized optical characteristic signal reflected by the coating layer.

[0031] The specific process includes: when emitting a second wavelength of a detection laser beam to the same surface area of the spherical optical lens, a polarization-tunable laser source is used to output a linearly polarized detection laser beam of a specific wavelength, and the incident angle of the detection laser beam is dynamically adjusted to a second optimized angle through a precise rotating platform, so that the detection laser beam acts on the coating layer of the spherical optical lens under optimal reflection conditions; during the reflection process, the interaction between the detection laser beam and the coating layer causes the polarization state to change, generating a polarization optical characteristic signal containing ellipticity angle and azimuth angle information; using a polarization-sensitive detector array to receive the polarization optical characteristic signal reflected by the coating layer, and the detector array synchronously collects Stokes parameters according to the spatial coordinate distribution; during the collection process, a rotation compensator technology is used to eliminate the polarization effect of the instrument, and synchronous detection technology is used to improve the measurement accuracy; finally, a polarization optical characteristic signal containing thickness distribution and interface characteristic information of the coating layer of the spherical optical lens is generated.

[0032] The second optimization angle is to select the incident angle that maximizes the intensity of the polarization optical characteristic signal and optimizes the signal-to-noise ratio by measuring the reflectivity curve and polarization state change curve of the coating layer to linearly polarized light of different wavelengths.

[0033] The optimal reflection condition is based on the polarization reflection characteristic curve of the coating material and the Stokes parameter sensitivity analysis. Through experimental calibration, the signal-to-noise ratio and measurement sensitivity of the polarization optical characteristic signal can simultaneously achieve the optimal combination of incident angle and polarization state.

[0034] S2: Based on the nonlinear optical characteristic signal, the spatial distribution data of the substrate curvature is generated through the curvature inversion algorithm, and the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface are extracted through the polarization feature analysis technology.

[0035] S2.1: Perform signal band separation processing on the nonlinear optical characteristic signal to extract the substrate characteristic response component that penetrates the coating layer, and use a window function to suppress the noise reflected by the coating layer to generate the nonlinear optical response component.

[0036] The specific process includes using a digital filter group to decompose the collected nonlinear optical characteristic signal into multiple sub-bands according to the frequency components; analyzing the spectral characteristics of each sub-band to identify the characteristic frequency band corresponding to the substrate characteristic response component penetrating the coating layer; extracting the signal components in the characteristic frequency band through a bandpass filter while retaining the phase information of the nonlinear optical effect; applying a Hanning window function to the extracted signal components to suppress the boundary effect and spectral leakage caused by the reflection penetrating the coating layer; coherently superimposing the sub-band signals after window function processing to reconstruct the complete nonlinear optical response component; the nonlinear optical response component finally generated effectively highlights the characteristic response of the substrate material while minimizing the interference of the reflection noise of the coating layer.

[0037] S2.2: Based on the nonlinear optical response component, the local curvature radius of the substrate is calculated using the curvature inversion algorithm to construct the initial spatial distribution model of the substrate curvature. The expression is: ; in, Indicates the spatial coordinates of the spherical optical lens The base curvature radius value at , Represents the spatial coordinates of the spherical optical lens, represents the second-order nonlinear susceptibility of the substrate material, represents the wavelength of the nonlinear optical signal, Indicates the spatial coordinates of the spherical optical lens The intensity of the nonlinear optical signal after purification is represents the spherical solid angle, Represents the refractive index of the base material and the coating layer, Indicates the spatial coordinates of the spherical optical lens The dynamic scattering angle deviation between the incident laser and the local substrate normal at represents the nonlinear signal gradient correction coefficient, Indicates the spatial coordinates of the spherical optical lens The square of the spatial gradient of the purified nonlinear optical signal intensity.

[0038] The specific process includes establishing a three-dimensional sampling grid of the spherical optical lens based on the spatial coordinate information in the nonlinear optical response component; utilizing the physical relationship between the nonlinear optical signal intensity and curvature, establishing a local curvature calculation equation at each spatial coordinate point, which includes the second-order nonlinear polarization rate, the nonlinear optical signal wavelength and the purified nonlinear optical signal intensity; correcting the angular influence between the incident laser and the local substrate normal by solving the geometric relationship between the spherical solid angle and the dynamic scattering angle deviation; performing refraction compensation on the nonlinear optical signal propagation path based on the equivalent refractive index difference between the substrate material and the coating layer; introducing a nonlinear signal gradient correction coefficient to weight the square of the modulus of the spatial gradient of the purified nonlinear optical signal intensity to eliminate the calculation error caused by signal fluctuations; calculating the local curvature radius value of the substrate point by point through the mathematical expression of the curvature inversion algorithm; the curvature calculation results of all spatial coordinate points are arranged according to the sampling grid to construct an initial spatial distribution model of the substrate curvature; the initial spatial distribution model completely characterizes the three-dimensional morphological characteristics of the spherical optical lens substrate.

[0039] S2.3: Based on the initial spatial distribution model, calculate the base curvature distribution deviation value of the annular area around the edge of the spherical optical lens using the gradient-signal-to-noise ratio joint optimization algorithm, and generate the base curvature spatial distribution data. The expression is: ; in, Indicates the spatial coordinates of the spherical optical lens The base curvature distribution deviation value at represents the theoretical curvature value based on the substrate material properties and geometric constraints, Represented in spatial coordinates The weighting factor is dynamically adjusted according to the signal quality. Indicates the difference in refractive index between the base material and the coating layer.

[0040] The specific process includes: according to the substrate curvature radius value calculated in the initial spatial distribution model, a point-by-point comparison is performed with the theoretical curvature value based on the substrate material properties and geometric constraints to obtain the initial deviation; then the weighting factor dynamically adjusted according to the signal quality at the spatial coordinate is applied to the initial deviation to compensate for the measurement error caused by signal attenuation in the edge ring area; at the same time, the influence of the equivalent refractive index difference between the substrate material and the coating layer on the optical path propagation is considered, and the calculation result is corrected for the refraction effect; the deviation after weighted processing and refraction correction is used as the substrate curvature distribution deviation value; finally, the substrate curvature distribution deviation value is iteratively optimized through the gradient-signal-to-noise ratio joint optimization algorithm to eliminate local distortion and achieve a smooth transition of the curvature distribution, and finally output accurate substrate curvature spatial distribution data.

[0041] The theoretical curvature value of the substrate material properties and geometric constraints is the ideal curvature distribution obtained by combining the intrinsic parameters of the material with the design geometric equation of the optical lens.

[0042] S2.4: Perform polarization state separation on the nonlinear optical response components and extract the full polarization response data of the coupling between the coating layer and the substrate.

[0043] The specific process includes using a polarization beam splitter to decompose the nonlinear optical response component into multiple sub-components according to the polarization direction; obtaining the polarization state information of each sub-component, including linear polarization and circular polarization components, through a Stokes parameter meter; using Jones matrix operations to process the polarization transmission process at the interface between the coating layer and the substrate, and distinguishing the reflection response of the coating layer from the interaction response of the substrate after penetrating the coating layer; using a polarization phase-sensitive detection device to extract the elliptical polarization characteristics generated by the coupling between the coating layer and the substrate, and separating the full polarization response data that simultaneously reflects the interface characteristics of the coating layer and the nonlinear optical effects of the substrate; the full polarization response data finally obtained completely retains the polarization characteristic information of the coupling between the coating layer and the substrate.

[0044] S2.5: Based on the full polarization response data, the thickness distribution characteristics of the coating layer are extracted through polarization harmonic coherence analysis, and the transmission matrix of the coating layer is constructed.

[0045] The specific process includes using Fourier transform to decompose the full polarization response data into different harmonic components; using coherent demodulation technology to separate the characteristic harmonic components directly related to the thickness of the coating layer; establishing a mapping relationship between the characteristic harmonic phase and the coating layer thickness through the least squares fitting algorithm to obtain the thickness value of each spatial coordinate point; combining Jones matrix operations to derive the optical transmission characteristics of the coating layer, and convert the thickness distribution characteristics into an equivalent optical transmission matrix; the final constructed coating layer transmission matrix fully characterizes the optical transmission behavior of the coating layer at different spatial positions.

[0046] S2.6: Based on the transmission matrix of the coating layer, the optical response component of the coating layer is stripped from the full polarization response data to obtain the optical response characteristics of the substrate surface.

[0047] The specific process includes performing matrix analysis on the transmission matrix of the coating layer and the full polarization response data to inversely derive the polarization state before the incident light enters the coating layer; eliminating the modulation effect of the coating layer on the polarization state through polarization state deconvolution processing, and restoring the original polarization response at the substrate interface; using a differential algorithm to subtract the optical response component contributed by the coating layer from the full polarization response data, retaining the optical response characteristics generated only by the substrate surface; the optical response characteristics of the substrate surface finally obtained completely eliminate the interference of the coating layer and accurately reflect the intrinsic optical properties of the substrate surface.

[0048] The optical response component refers to the optical characteristic response part contained in the polarized light signal generated by the interaction between the coating layer and the substrate.

[0049] S3: The spatial distribution data of the substrate curvature is corrected through the refractive index compensation algorithm, and the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface are weighted and integrated to generate a three-dimensional point cloud coordinate set.

[0050] S3.1: Apply a refractive index compensation algorithm to the base curvature spatial distribution data to generate corrected base curvature data.

[0051] The specific process includes obtaining the refractive index distribution parameters of the coating layer of the spherical optical lens, establishing a correction relationship between the refractive index of the coating layer and the substrate curvature; performing a convolution operation on the curvature value of each spatial coordinate point in the substrate curvature spatial distribution data with the refractive index of the coating layer at the corresponding position, and analyzing the curvature measurement deviation caused by the refractive index difference; quantifying the influence of the sudden change in the refractive index of the coating layer interface on the substrate curvature measurement through Fresnel transmission theory; using the iterative least squares method to correct the curvature deviation component in the substrate curvature spatial distribution data point by point; performing a weighted fusion of the corrected curvature value and the original substrate curvature spatial distribution data to eliminate the systematic error caused by the refractive index disturbance of the coating layer; the corrected substrate curvature data finally generated accurately reflects the true geometric characteristics of the spherical optical lens substrate.

[0052] S3.2: Based on the corrected substrate curvature data, the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface are spatially fused through a weighted fusion algorithm to generate a comprehensive feature dataset of the substrate morphology.

[0053] The specific process includes establishing a spatial correspondence between the thickness change of the coating layer and the optical response characteristics of the substrate surface; using an adaptive weight allocation method to dynamically adjust the fusion weight coefficient according to the signal-to-noise ratio of the coating layer thickness distribution characteristics, giving the coating layer characteristics a higher weight in areas with high thickness measurement accuracy, and increasing the fusion ratio of the optical response characteristics in areas with an advantageous signal-to-noise ratio of the substrate surface optical response characteristics; through spatial convolution operations, multi-scale feature matching of the thickness distribution characteristics and the optical response characteristics is achieved to eliminate local measurement inconsistencies; the final generated substrate morphology comprehensive feature data set contains both high-precision geometric curvature information and surface optical characteristic parameters, which fully characterizes the three-dimensional morphology and surface optical properties of the substrate.

[0054] S3.3: Perform three-dimensional point cloud mapping on the base morphology comprehensive feature dataset to generate a three-dimensional point cloud coordinate set.

[0055] The specific process includes: when performing three-dimensional point cloud mapping on the substrate morphology comprehensive feature data set, extracting the spatial coordinate information and geometric feature parameters in the substrate morphology comprehensive feature data set; converting the substrate curvature spatial distribution data into the curvature field distribution in three-dimensional space; deriving the height compensation amount of each spatial position based on the coating layer thickness distribution characteristics; converting the two-dimensional plane coordinates into point cloud coordinates in a three-dimensional rectangular coordinate system through a coordinate transformation algorithm; using a bilinear interpolation method to process the transition area between discrete sampling points; adaptively adjusting the point cloud density in combination with the optical response characteristics of the substrate surface; arranging the processed three-dimensional spatial coordinates in an orderly manner according to the spatial topological relationship; and finally generating a three-dimensional point cloud coordinate set that accurately represents the three-dimensional geometric morphology of the surface of the spherical optical lens.

[0056] S4: Real-time monitoring of the temperature field distribution on the surface of the spherical optical lens, compensation for thermal deformation of the three-dimensional point cloud coordinate set, and generation of a three-dimensional contour detection report after surface fitting and topological defect analysis.

[0057] S4.1: The temperature field distribution data of the spherical optical lens surface is collected in real time by an infrared thermal imager, and the temperature field distribution data is spatially differentiated by a two-dimensional discrete gradient operator to generate a temperature gradient matrix.

[0058] The specific process includes: when using an infrared thermal imager to collect temperature field distribution data on the surface of a spherical optical lens in real time, a high-resolution infrared detector is used to obtain the temperature value of each pixel point on the lens surface at a fixed sampling interval; the collected temperature field distribution data is converted into a two-dimensional digital matrix form, and the matrix elements correspond to the temperature measurement values of the spatial coordinate points; a two-dimensional discrete gradient operator is applied to perform spatial differential operations on the temperature field distribution data matrix to obtain the temperature change rate of each pixel point in the horizontal and vertical coordinate directions; the matrix edge data points are processed by the central difference method to ensure the boundary accuracy of the differential operation; the temperature change rate components in the horizontal and vertical coordinate directions are combined to form a temperature gradient matrix, and the matrix elements contain the temperature gradient amplitude and direction information corresponding to the spatial coordinate points; the temperature gradient matrix finally generated completely characterizes the spatial variation characteristics of the temperature field on the surface of the spherical optical lens.

[0059] S4.2: Based on the temperature gradient matrix, the thermal-optical coupling model is used to calculate the thermal deformation compensation coefficient. The thermal expansion correction is performed pixel by pixel on the 3D point cloud coordinate set to generate the thermally compensated 3D point cloud coordinates. The expression is: ; in, Indicates the spatial coordinates of the spherical optical lens Thermal deformation compensation coefficient at (0.8≤ ≤1.2), Represents the base of the spherical optical lens, Indicates the coating layer of the spherical optical lens. Indicates the thermal expansion coefficient of the spherical optical lens substrate, Indicates the spatial coordinates of the spherical optical lens base The local temperature change at Indicates the refractive index of the coating layer of the spherical optical lens, Indicates the thermal expansion coefficient of the coating layer of the spherical optical lens, Indicates the spatial coordinates of the spherical optical lens base The temperature gradient vector at Indicates the physical thickness of the coating layer on the spherical optical lens. represents the nonlinear thermal coupling coefficient, Indicates the local temperature change of the spherical optical lens coating layer and the spherical optical lens substrate The nonlinear thermal stress accumulation term under represents the thermal relaxation time constant.

[0060] The specific process includes performing a dot product operation on the temperature gradient vector at the spatial coordinate in the temperature gradient matrix and the thermal expansion coefficient of the spherical optical lens substrate to obtain a linear thermal expansion component; combining the refractive index and physical thickness of the spherical optical lens coating layer to calculate the modulation effect of the coating layer on heat conduction; describing the thermal impedance effect between the spherical optical lens substrate and the spherical optical lens coating layer by a nonlinear thermal coupling coefficient; introducing a thermal relaxation time constant to perform weighted processing on the local temperature change in the time dimension to reflect the relaxation characteristics of the heat accumulation effect; superimposing the nonlinear thermal stress accumulation term and the linear component of the spherical optical lens coating layer and the spherical optical lens substrate under local temperature changes to generate a thermally induced deformation compensation coefficient at the spatial coordinate; using the thermally induced deformation compensation coefficient to perform pixel-by-pixel coordinate correction on the three-dimensional point cloud coordinate set to offset the deformation error caused by thermal expansion; the thermally compensated point cloud data finally generated eliminates the measurement deviation caused by temperature field changes and accurately reflects the true geometric morphology of the spherical optical lens.

[0061] Furthermore, the temperature gradient matrix and the corresponding three-dimensional point cloud coordinate set of the spherical optical lens under different temperature conditions are collected as training samples; the theoretical thermal deformation field of the spherical optical lens substrate and the spherical optical lens coating layer under each temperature condition is obtained through finite element analysis software; a mapping relationship network architecture between the temperature gradient matrix and the thermal deformation field is established, the input layer receives parameters such as the temperature gradient vector, the thermal expansion coefficient of the spherical optical lens substrate, and the refractive index of the spherical optical lens coating layer, and the output layer predicts the thermally induced deformation compensation coefficient; the L-BFGS (limited memory quasi-Newton optimization algorithm) optimization algorithm is used to minimize the mean square error between the predicted thermally induced deformation compensation coefficient and the theoretical thermal deformation field; parameters such as the nonlinear thermal coupling coefficient and the thermal relaxation time constant are adjusted through cross-validation; the training is completed when the average relative error between the predicted thermally induced deformation compensation coefficient and the finite element analysis result is less than 5%; the thermal-optical coupling model finally obtained can accurately reflect the nonlinear relationship between the temperature gradient matrix and the thermally induced deformation.

[0062] S4.3: Perform Zernike polynomial surface fitting on the thermally compensated 3D point cloud coordinate set to generate an ideal reference surface and calculate the surface deviation. The expression is: ; ; in, Indicates the ideal reference surface generated by Zernike polynomial surface fitting in space coordinates The height value at represents the order index of the Zernike polynomial ( ≥0), Indicates the highest order Zernike polynomial used for surface fitting, Indicates the The fitting coefficients corresponding to the Zernike polynomial of order, Indicates the order Zernike polynomials, represents the normalized polar diameter, represents the polar angle, Indicates the index number of the point cloud data, Indicates the The surface deviation of the coordinate points, Indicates the The measured height value of the coordinate point, Indicates the ideal reference surface generated by Zernike polynomial surface fitting in space coordinates The height value at Indicates the The plane coordinates of the coordinate points.

[0063] The specific process includes: when performing Zernike polynomial surface fitting on the three-dimensional point cloud coordinate set after thermal compensation, the spatial coordinates in the three-dimensional point cloud coordinate set are converted into normalized polar coordinate form; the fitting coefficients corresponding to the Zernike polynomials of each order are solved by the least squares method, so that the Zernike polynomial combination and the measured point cloud data are optimally matched; the ideal reference surface is reconstructed using the fitting coefficients obtained by the solution, and the height value generated by the Zernike polynomial surface fitting at each spatial coordinate point is calculated; the measured height value of each coordinate point is compared with the ideal reference surface height value at the corresponding position point by point to obtain the surface deviation; the surface deviation matrix finally obtained completely characterizes the morphological difference between the three-dimensional point cloud coordinate set after thermal compensation and the ideal reference surface.

[0064] The ideal reference surface is the optimal fitting mathematical surface obtained by fitting the three-dimensional point cloud coordinate set after thermal compensation through Zernike polynomials, which serves as a reference for evaluating the actual surface deviation.

[0065] S4.4: Based on the surface deviation, the geometric features of surface defects are identified through morphological image processing algorithms, and compared with the preset defect judgment thresholds to generate defect classification statistics.

[0066] The specific process includes converting the surface deviation matrix into a grayscale image format; using morphological opening operations to eliminate tiny noise interference and maintain the integrity of the main defect features; extracting the geometric features of the defect area through connected domain analysis, including area, perimeter, major axis length and minor axis length; deriving shape features such as the roundness and convex hull area ratio of each defect area; comparing the extracted geometric features of the surface defects with the preset defect judgment threshold item by item to determine the defect type; counting the number and distribution characteristics of defects of different categories, and generating classified statistical data containing defect type, size and location information; the defect classification statistical data finally obtained completely characterizes the defect distribution on the surface of the spherical optical lens, providing a quantitative basis for quality assessment.

[0067] The preset defect judgment threshold is the critical value of defect size and shape parameters determined through experimental statistics and empirical analysis based on optical component industry standards and quality requirements of specific application scenarios.

[0068] S4.5: Generate a 3D profile inspection report by integrating the ideal reference surface, surface deviation, and defect classification statistics.

[0069] The specific process includes spatially superimposing the mathematical expression of the ideal reference surface with the surface deviation matrix to reconstruct the actual surface three-dimensional morphology; mapping the position information in the defect classification statistical data to the corresponding coordinate area of the three-dimensional morphology through data fusion technology; using a visual rendering algorithm to generate a three-dimensional color contour map containing curvature distribution, surface deviation cloud map and defect marks; recording the maximum surface deviation value, root mean square deviation value and the quantitative statistical results of various defects in the report according to the ISO standard format; the final generated three-dimensional contour detection report contains both quantitative analysis data and intuitive morphology display, which fully reflects the surface quality status of the spherical optical lens.

[0070] This embodiment also provides a spherical optical lens three-dimensional profile detection system, including: a laser acquisition module, a signal decoupling module, a point cloud generation module and a thermal compensation analysis module. The laser acquisition module is used to emit a detection laser beam to the spherical optical lens, and collect nonlinear optical characteristic signals of the penetrating coating layer and polarization optical characteristic signals of the reflecting coating layer by dynamically adjusting the incident angle of the detection laser beam; the signal decoupling module is used to generate substrate curvature spatial distribution data based on the nonlinear optical characteristic signals using a curvature inversion algorithm, and extract the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface using a polarization feature analysis technology; the point cloud generation module is used to correct the substrate curvature spatial distribution data using a refractive index compensation algorithm, and weightedly fuse the thickness distribution characteristics of the penetrating coating layer and the optical response characteristics of the substrate surface to generate a three-dimensional point cloud coordinate set; the thermal compensation analysis module is used to monitor the temperature field distribution on the surface of the spherical optical lens in real time, compensate for thermally induced deformation of the three-dimensional point cloud coordinate set, and generate a three-dimensional profile detection report after surface fitting and topological defect analysis.

[0071] This embodiment further provides a computer device applicable to the 3D profile detection method for a spherical optical lens, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the 3D profile detection method for a spherical optical lens as proposed in the above embodiment.

[0072] The computer device may be a terminal, comprising a processor, memory, a communication interface, a display, and an input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and computer programs. The internal memory provides an environment for the operating system and computer programs stored in the non-volatile storage media. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication. Wireless communication may be achieved via Wi-Fi, a carrier network, NFC (near-field communication), or other technologies. The display of the computer device may be a liquid crystal display or an electronic ink display. The input device may be a touchscreen overlay on the display, buttons, a trackball, or a touchpad on the computer device housing, or an external keyboard, touchpad, or mouse.

[0073] This embodiment further provides a storage medium having a computer program stored thereon. When the program is executed by a processor, the program implements the method for detecting the three-dimensional profile of a spherical optical lens as proposed in the above embodiment. The storage medium can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0074] In summary, the present invention effectively improves the reconstruction accuracy of the substrate curvature distribution by: performing frequency band separation and window function denoising on the nonlinear optical response components, combining the curvature inversion algorithm and the gradient-signal-to-noise ratio joint optimization strategy; further, the polarization harmonic coherence analysis method is used to extract the coating layer thickness distribution, and the influence of the coating layer on the substrate optical response is stripped off based on the transmission matrix, thereby realizing the analysis of the true optical properties of the substrate surface.

[0075] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for detecting the three-dimensional profile of a spherical optical lens, characterized by: include, A detection laser beam is emitted to the spherical optical lens, and the incident angle of the detection laser beam is dynamically adjusted to collect the nonlinear optical characteristic signal of the penetrating coating layer and the polarization optical characteristic signal of the reflecting coating layer; Based on the nonlinear optical characteristic signal, the curvature inversion algorithm is used to generate the spatial distribution data of the substrate curvature, and the polarization characteristic analysis technology is used to extract the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface; The spatial distribution data of the substrate curvature is corrected by the refractive index compensation algorithm, and the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface are weighted and integrated to generate a three-dimensional point cloud coordinate set; Real-time monitoring of the temperature field distribution on the surface of the spherical optical lens, compensation for thermal deformation of the 3D point cloud coordinate set, and generation of a 3D contour detection report after surface fitting and topological defect analysis.

2. The method for detecting the three-dimensional profile of a spherical optical lens according to claim 1, wherein: The specific steps of emitting a detection laser beam to the spherical optical lens and collecting the nonlinear optical characteristic signal of the penetrating coating layer and the polarized optical characteristic signal of the reflecting coating layer by dynamically adjusting the incident angle of the detection laser beam are as follows: emitting a detection laser beam of a first wavelength toward the surface area of the spherical optical lens, and collecting a nonlinear optical characteristic signal generated by penetrating the coating layer by dynamically adjusting the incident angle of the detection laser beam to a first optimized angle; A detection laser beam of a second wavelength is emitted to the same surface area of the spherical optical lens, and the polarization optical characteristic signal of the reflective coating layer is collected by dynamically adjusting the incident angle of the detection laser beam to a second optimized angle.

3. The method for detecting the three-dimensional profile of a spherical optical lens according to claim 2, wherein: The base curvature spatial distribution data is generated by the curvature inversion algorithm based on the nonlinear optical characteristic signal. The specific steps are as follows: Perform signal band separation processing on the nonlinear optical characteristic signal to extract the substrate characteristic response component that penetrates the coating layer, and use a window function to suppress the noise reflected by the coating layer to generate the nonlinear optical response component; Based on the nonlinear optical response component, the local curvature radius of the substrate is calculated using the curvature inversion algorithm to construct the initial spatial distribution model of the substrate curvature. According to the initial spatial distribution model, the gradient-signal-to-noise ratio joint optimization algorithm is used to correct the base curvature distribution deviation value of the annular area at the edge of the spherical optical lens, and generate the base curvature spatial distribution data.

4. The method for detecting the three-dimensional profile of a spherical optical lens according to claim 3, wherein: The specific steps of extracting the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface by using the polarization feature analysis technology are as follows: Perform polarization state separation on the nonlinear optical response components and extract the full polarization response data of the coupling between the coating layer and the substrate; Based on the full polarization response data, the thickness distribution characteristics of the coating layer are extracted through polarization harmonic coherence analysis, and the transmission matrix of the coating layer is constructed; According to the transmission matrix of the coating layer, the optical response component of the coating layer is stripped from the full polarization response data to obtain the optical response characteristics of the substrate surface.

5. The method for detecting the three-dimensional profile of a spherical optical lens according to claim 1, wherein: The specific steps of generating a three-dimensional point cloud coordinate set are as follows: Applying a refractive index compensation algorithm to the base curvature spatial distribution data to generate corrected base curvature data; Based on the corrected substrate curvature data, the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface are spatially fused using a weighted fusion algorithm to generate a comprehensive feature dataset of the substrate morphology. Perform three-dimensional point cloud mapping on the comprehensive feature data set of the base morphology to generate a three-dimensional point cloud coordinate set.

6. The method for detecting the three-dimensional profile of a spherical optical lens according to claim 5, wherein: The specific steps of real-time monitoring of the temperature field distribution on the surface of the spherical optical lens and thermal deformation compensation of the three-dimensional point cloud coordinate set are as follows: The temperature field distribution data of the spherical optical lens surface is collected in real time by an infrared thermal imager, and the temperature field distribution data is spatially differentiated by a two-dimensional discrete gradient operator to generate a temperature gradient matrix. Based on the temperature gradient matrix, the thermal deformation compensation coefficient is calculated through the thermal-optical coupling model, and the three-dimensional point cloud coordinate set is corrected for thermal expansion pixel by pixel to generate the thermally compensated three-dimensional point cloud coordinates.

7. The method for detecting the three-dimensional profile of a spherical optical lens according to claim 6, wherein: After surface fitting and topological defect analysis, a three-dimensional contour detection report is generated. The specific steps are as follows: Perform Zernike polynomial surface fitting on the three-dimensional point cloud coordinate set after thermal compensation to generate an ideal reference surface and calculate the surface deviation; Based on the surface deviation, the geometric features of surface defects are identified through morphological image processing algorithms, and compared with the preset defect judgment threshold to generate defect classification statistics; The ideal reference surface, surface deviation and defect classification statistics are integrated to generate a 3D contour inspection report.

8. A spherical optical lens three-dimensional profile detection system, based on the spherical optical lens three-dimensional profile detection method according to any one of claims 1 to 7, characterized in that: Including laser acquisition module, signal decoupling module, point cloud generation module and thermal compensation analysis module, The laser acquisition module is used to emit a detection laser beam to the spherical optical lens, and collect the nonlinear optical characteristic signal of the penetrating coating layer and the polarization optical characteristic signal of the reflecting coating layer by dynamically adjusting the incident angle of the detection laser beam; The signal decoupling module is used to generate the spatial distribution data of the substrate curvature through the curvature inversion algorithm based on the nonlinear optical characteristic signal, and to extract the thickness distribution characteristics of the coating layer and the optical response characteristics of the substrate surface through the polarization characteristic analysis technology; The point cloud generation module is used to correct the spatial distribution data of the substrate curvature through the refractive index compensation algorithm, and to weightedly fuse the thickness distribution characteristics of the penetrating coating layer and the optical response characteristics of the substrate surface to generate a three-dimensional point cloud coordinate set; The thermal compensation analysis module is used to monitor the temperature field distribution on the surface of the spherical optical lens in real time, compensate for thermal deformation of the three-dimensional point cloud coordinate set, and generate a three-dimensional contour detection report after surface fitting and topological defect analysis.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the spherical optical lens three-dimensional profile detection method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the spherical optical lens three-dimensional profile detection method according to any one of claims 1 to 7 are implemented.

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