Intelligent generation of optical lens milling machining path and error compensation method

Abstract

The application discloses an optical lens milling and grinding processing path intelligent generation and error compensation method and relates to the technical field of program control. The method comprises the following steps: planning a primary milling and grinding processing path based on the mechanical structure characteristics of the optical lens under a preset assembly condition, wherein the preset assembly condition defines the specific application scene of the optical lens, the specific application scene comprises an optical detection instrument and an optical wearing device, and the mechanical structure characteristics are carriers for assembling the optical lens in the specific application scene, including an optical lens seat or an optical lens frame. The method utilizes a central stress uniformity model of the detection instrument scene and an edge thinning weight control model of the wearing device scene, realizes dynamic matching of the optical lens thickness distribution and the terminal function, and ensures the imaging stability of the high-precision optical lens by optimizing the milling and grinding depth parameters, while eliminating the central area micro-crack risk and reducing the edge redundant weight.

Description

Technical Field

[0001] This invention relates to the field of program control technology, specifically to a method for intelligent generation and error compensation of milling paths for optical lenses. Background Technology

[0002] As precision optical components, optical lenses are prone to random errors during processing due to factors such as tool wear, material elastic deformation, and machine tool vibration. Since these errors are random and real-time, they affect the processing accuracy of optical lenses. Therefore, an intelligent generation and error compensation method for optical lens milling processing paths is needed.

[0003] A search revealed that Chinese invention patent application with publication number "CN109725595A" proposes a "compensation method for machining path of workpiece, machining method and workpiece". By compensating the machining path based on the result of machining the first machining path, the error can be corrected regardless of the factor that causes the final error. For example, deformation caused by servo control, CAM function, machine tool accuracy, material deformation and algorithm smoothing can be compensated, thereby improving machining accuracy.

[0004] However, in actual use, the aforementioned disclosed devices and similar existing technologies fail to meet the dual requirements of central stress uniformity and edge weight control due to the lack of differentiated processing path planning strategies for different application scenarios of optical lenses. This results in lenses that are difficult to adapt to the functional requirements of end-user scenarios. Secondly, the lack of a real-time stress monitoring and dynamic path correction mechanism based on spectral data makes it difficult to accurately identify and eliminate the risk of micro-cracks during processing. Furthermore, compensation for residual error sources is mostly static or single-factor compensation, failing to achieve real-time integration and dynamic calibration of multi-source errors, ultimately affecting the processing accuracy and imaging stability of optical lenses. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent generation and error compensation method for the milling process path of optical lenses, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for intelligent generation and error compensation of milling paths for optical lenses, comprising:

[0007] Based on the mechanical structural characteristics of optical lenses under preset assembly conditions, a primary milling processing path is planned. The preset assembly conditions define the specific application scenarios of the optical lenses, including optical testing instruments and optical wearable devices. The mechanical structural characteristics are the carriers for assembling optical lenses in specific application scenarios, including optical lens mounts or optical lens frames.

[0008] According to the processing requirements, the thickness of the optical lens in the primary milling process is calibrated, and a three-dimensional calibration milling process is generated. The processing requirements are the application scenarios of the optical lens. Different scenarios correspond to differences in the degree of stress concentration at the center of the optical lens or the edge comfort and weight control.

[0009] Under the three-dimensional calibration milling process, the spectral data of the optical lens is collected, and the stress range of the optical lens under the three-dimensional calibration milling process is adjusted and corrected based on the spectral data.

[0010] The residual error sources are calibrated on the corrected 3D calibrated milling path, and the final milling path is generated. The residual error sources include tool wear, thermal deformation, and material removal deviation.

[0011] As a further preferred embodiment of this technical solution, the method for generating the primary milling machining path includes:

[0012] Based on the mechanical structural features, the milling processing range is mapped within the optical lens. A two-dimensional coordinate system is created at the contact surface position between the carrier and the optical lens corresponding to the mechanical structural features. The two-dimensional coordinate system takes the center point of the carrier as the origin, the horizontal axis represents the radial offset distance of the optical lens on the contact surface of the carrier, and the vertical axis corresponds to the position parameters of the axial height or curvature direction. According to the contour dimensions of the carrier and the assembly tolerance requirements of the optical lens, the milling processing range of the optical lens is defined in the two-dimensional coordinate system.

[0013] The geometric shape of the mechanical structure is obtained, and the preliminary milling path is determined within the milling processing range, wherein the geometric shape is the two-dimensional contour shape of the contact area between the carrier and the optical lens.

[0014] As a further preferred embodiment of this technical solution, when the carrier is an optical lens mount or an optical lens frame, the radial machining range P of the milling processing range is [0, D / 2], and the axial machining range Z is calculated based on the radius of curvature R of the optical lens, where D is the inner diameter of the carrier, and the effective range of the axial height is set to [H-Δh, H+Δh], where H is the axial height of the edge support surface, and Δh is the assembly tolerance.

[0015] As a further preferred embodiment of this technical solution, the formula for calculating the axial machining range Z is as follows: Using the axial height H of the lens mount / frame edge support surface as a reference, the reference axial coordinates required for spherical machining at the radial position P are obtained. For a point on the sphere with a radial position PP (radial distance P from the center of the sphere), the axial coordinates of this point (calculated based on the geometry of the sphere itself) and the axial coordinates of the edge are... The axial coordinate of the sphere itself is located at the inner diameter edge of the optical lens (radial position P=D / 2).

[0016] As a further preferred embodiment of this technical solution, the method for generating the three-dimensional calibration milling path includes:

[0017] The processing requirements are analyzed and thickness calibration parameters are constructed. These requirements are quantified using application scenario identifiers: optical inspection instruments are coded as 01, and optical wearable devices are coded as 02. For scenario 01, the calibration model is as follows: ;

[0018] in Let be the initial thickness distribution function of the optical lens under the primary milling process. This is the stress calibration coefficient, whose value is determined by both the material's elastic modulus E and yield strength σᵧ. It is a specific numerical value, and the specific calculation formula is as follows: ,in This represents the maximum stress value in the central region of the lens under the primary path. Let x be the radius of the central stress control region, and y be the radial coordinates in a two-dimensional coordinate system.

[0019] Based on the thickness calibration parameters output by the calibration model, a three-dimensional thickness mapping is performed on the two-dimensional contour of the primary milling machining path to generate a three-dimensional coordinate point cloud.

[0020] The 3D point cloud is smoothed to generate the final 3D calibration milling path.

[0021] As a further preferred embodiment of this technical solution, for the optical wearable device scenario (02), the calibration model focuses on edge comfort and weight control, and the expression is:

[0022] ;

[0023] in The maximum radial boundary of the carrier. The edge thinning factor is determined by the lens material density ρ and the wearing weight threshold W, and is calculated using the following formula: , This represents the total weight of the lens along the primary path.

[0024] As a further preferred embodiment of this technical solution, spectral data acquisition employs a micro Raman spectrometer, with sampling points including a central region and an edge region, and no fewer than n sampling points in each region. The stress range adjustment and correction includes:

[0025] Characteristic peak values ​​are obtained based on the acquisition and preprocessing of spectral data;

[0026] Based on the preprocessed characteristic peak wave values ​​and the target characteristic peak wave values, and combined with the elastic modulus and Poisson's ratio of the optical lens material, a quantitative relationship between stress and wavenumber shift is constructed.

[0027] The real-time machining stress value corresponding to each sampling point is calculated based on the quantitative relationship, and the stress data of all sampling points are statistically analyzed to determine the stress distribution range under the current three-dimensional calibration milling path;

[0028] The three-dimensional calibration milling path is dynamically corrected based on the stress distribution range.

[0029] As a further preferred embodiment of this technical solution, the method for generating the final milling path through error compensation includes:

[0030] Collect real-time error data of residual error sources, including: using an inductive displacement sensor to monitor the radial wear of the tool, using an infrared thermometer to scan thermal deformation, and using a laser interferometer to detect material removal deviations;

[0031] Dynamic compensation rules are constructed based on real-time error data, and the compensation amount is calculated.

[0032] The compensation amount is integrated into the 3D calibration milling path to generate the final milling machining path.

[0033] As a further preferred embodiment of this technical solution, the wear compensation coefficient is set manually according to the hardness of the processed material. The final milling path is generated by superimposing all compensation amounts onto the corresponding tool position coordinates of the three-dimensional calibrated milling path to form a corrected coordinate sequence, and the final milling path is constructed by associating the corrected coordinate sequence.

[0034] Compared with the prior art, the beneficial effects of the present invention are:

[0035] This intelligent generation and error compensation method for milling processing paths of optical lenses transforms the mechanical structural features of the assembly scene into a processing range mapping in a two-dimensional coordinate system, achieving precise geometric adaptation of the primary milling path. It replaces traditional manual trial and error with quantitative calculation of carrier contour dimensions and assembly tolerances, simplifying the process design process while ensuring the assembly tightness of the optical lens and the carrier, and avoiding stress concentration or optical distortion caused by contour deviation.

[0036] Furthermore, by using a scene-driven three-dimensional thickness calibration mechanism, the central stress uniformity model of the detection instrument scene and the edge thinning weight control model of the wearable device scene are used to achieve dynamic matching between the optical lens thickness distribution and terminal functions. By optimizing the milling depth parameters, the imaging stability of high-precision optical lenses is ensured while eliminating the risk of microcracks in the central area and reducing redundant weight at the edges.

[0037] Furthermore, by using in-situ Raman spectroscopy for real-time stress field analysis and closed-loop correction, and by using a micro Raman spectrometer to monitor the stress wavenumber shift at the sampling points along the processing path, early warning and dynamic suppression of latent damage are achieved. The distribution of milling load is actively optimized by combining thermal mapping with a graded adjustment strategy. This not only blocks the propagation path of microcracks and balances the surface stress field, but also reduces the reliance of subsequent polishing processes on defect compensation.

[0038] Finally, through a multi-source collaborative mechanism of tool wear pre-compensation, thermal deformation offset correction, and material removal deviation mapping, the residual error is synchronously eliminated and the path coordinate is self-healed by using an inductive displacement sensor to predict the trend of milling cutter wear, an infrared thermometer to track local temperature differences in real time, and a laser interferometer to provide deviation feedback on the theoretical machining depth. This replaces manual intervention with closed-loop control, which suppresses contour distortion caused by tool dulling, offsets surface warping caused by thermal deformation, and corrects depth deviations induced by material inhomogeneity, while ensuring the consistency of mass production of complex curved surfaces such as aspherical lenses. Attached Figure Description

[0039] Figure 1 This is a flowchart of the method steps of the present invention;

[0040] Figure 2 This is a flowchart illustrating the thought process for generating the primary milling machining path in this invention.

[0041] Figure 3 This is a diagram illustrating the stress range analysis of the present invention;

[0042] Figure 4 This is a thermal diagram of stress distribution in the optical lens of the present invention.

[0043] Figure 5 This is a flowchart illustrating the thought process for generating the final milling machining path in this invention. Detailed Implementation

[0044] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0045] Before understanding the technical solution proposed in this application, it should be clear that the specific application scenario of this technical solution is the CNC milling and grinding process of high-precision optical lenses (such as aspherical lenses, freeform surface lenses, microscope lens lenses, and laser resonant cavity lenses). In this scenario, this technical solution proposes an intelligent generation and error compensation method for the milling and grinding process of optical lenses.

[0046] Specifically, such as Figure 1 As shown, this technical solution includes steps S100 to S400.

[0047] Step S100: Based on the mechanical structural characteristics of the optical lens under preset assembly conditions, plan the primary milling process path.

[0048] It is worth noting that in step S100, the content defined by the preset assembly conditions is the specific application scenario of the optical lens, including: optical testing instruments and optical wearing devices. The content described in step S100 is specifically the carrier for assembling the optical lens in the specific application scenario. For example, the carrier corresponding to the optical testing instrument is the optical lens mount, and the carrier corresponding to the optical wearing device is the optical lens frame. The primary milling processing path is the path limitation of the optical lens in terms of specifications.

[0049] As a supplement to step S100, refer to Figure 2 It can be seen that the planning method for the primary milling machining path includes: step S101-step S102.

[0050] Step S101: Map the milling processing range within the optical lens based on the mechanical structural characteristics.

[0051] It should be noted that during the operation of step S101, a two-dimensional coordinate system is first created at the contact surface position of the carrier and the optical lens corresponding to the mechanical structural features. The two-dimensional coordinate system is mapped onto the contact surface position of the optical lens in the form of optical projection. The two-dimensional coordinate system takes the center point of the carrier as the origin, the horizontal axis is used to represent the radial offset distance of the optical lens on the contact surface of the carrier, and the vertical axis corresponds to the position parameters in the axial height or curvature direction. Then, according to the contour dimensions of the carrier and the assembly tolerance requirements of the optical lens, the milling processing range of the optical lens is defined in the two-dimensional coordinate system.

[0052] Specifically, when the mechanical structural feature is either an optical lens mount or an optical lens frame, firstly, obtain the inner diameter D of the optical lens mount or optical lens frame, the axial height H of the edge support surface, and the assembly tolerance ±Δh. Then, in the created two-dimensional coordinate system, set the effective range of the radial offset distance to [0, D / 2] (corresponding to the inner radial boundary of the mechanical structural feature), and the effective range of the axial height to [H-Δh, H+Δh] (matching the height tolerance requirements between the lens and the mechanical structural feature during assembly). If the optical lens is spherical, the radius of curvature R of the optical lens also needs to be considered. In this case, the radial machining range P of the milling machining range is [0, D / 2], and the axial machining range Z is... Using the axial height H of the lens mount / frame edge support surface as a reference, the reference axial coordinates required for spherical machining at the radial position P are obtained. For a point on the sphere with a radial position PP (radial distance P from the center of the sphere), the axial coordinates of this point (calculated based on the geometry of the sphere itself) and the axial coordinates of the edge are... The axial coordinate of the sphere itself is located at the inner diameter edge of the optical lens (radial position P=D / 2).

[0053] Step S102: Obtain the geometry of the mechanical structural features and determine the preliminary milling path within the milling range.

[0054] It should be noted that the geometric shape of the mechanical structural features in step S102 specifically refers to the two-dimensional contour of the contact area between the carrier (optical lens mount or optical lens frame) and the optical lens. Furthermore, by recording the coordinate values ​​of different nodes within the two-dimensional contour in a two-dimensional coordinate system, the mathematical function expression formula for the preliminary milling path is determined. For example, when the carrier is a circular optical lens mount, the two-dimensional contour of the contact area between the circular optical lens mount and the optical lens is circular. N nodes (N≥8, to ensure contour fitting accuracy) are selected evenly distributed on the contour, and the polar coordinates of each node can be expressed as (r... i ,θ i ) where r i =D / 2 (D is the inner diameter of the lens mount), θ i =2π(i-1) / N (i=1,2,...,N), converting polar coordinates to rectangular coordinates in a two-dimensional coordinate system (x i , y i ), that is, x i =r i cosθ i y i =r i sinθ i Then, the rectangular coordinates of these nodes are fitted using the least squares method in the existing technology, and the circular contour function of the preliminary milling path is obtained as x² + y² = (D / 2)².

[0055] If the carrier is a square optical lens frame, and the outline of the contact area between the square optical lens frame and the optical lens is square, select 8 nodes, including the four vertices and the midpoints of each side of the square, and record the rectangular coordinates of each node (e.g., the vertex coordinates are (±L / 2, ±L / 2), where L is the side length inside the square frame). The piecewise function expression of the path is obtained through piecewise linear fitting, that is, the function on the positive x-axis side is y=±(L / 2) (x∈[0, L / 2]), and the function on the positive y-axis side is x=±(L / 2) (y∈[0, L / 2]). This process is repeated to form a complete square outline processing path.

[0056] Step S200: According to the processing requirements, the thickness of the optical lens in the primary milling path is calibrated, and a three-dimensional calibration milling path is generated.

[0057] It should be noted that the processing requirements in step S200 refer to the application scenario of the optical lens. Different application scenarios correspond to different central stress concentrations of the optical lens. For example, optical testing instruments have higher requirements for the uniformity of central stress of the lens, while optical wearable devices pay more attention to edge comfort and weight control. The three-dimensional calibration milling processing path in step S200 is mainly used to dynamically adjust the thickness distribution of the optical lens in three dimensions to match the performance requirements of different application scenarios.

[0058] Specifically, refer to Figure 3 It can be seen that the method for generating the three-dimensional calibration milling machining path includes: steps S201 to S203.

[0059] Step S201: Analyze the processing requirements and construct thickness calibration parameters.

[0060] It should be noted that step S201 is used to convert the process requirements of different application scenarios into quantifiable calibration parameters. This is based on the plane stress theory of elasticity in existing technology to establish a mechanical-material coupling model. Specifically, it first receives the application scenario identifier. In this technical solution, the optical detection instrument is coded as 01 and the optical wearable device is coded as 02. Then, the thickness distribution data of the primary milling path and the material property library (including elastic modulus E and yield strength) are received. y Then, the calibration model is selected based on the scene identifier; for the optical inspection instrument scene (01), the expression formula of the calibration model is as follows: ;

[0061] in Let be the initial thickness distribution function of the optical lens under the primary milling process. This is the stress calibration coefficient, whose value is determined by both the material's elastic modulus E and yield strength σᵧ. It is a specific numerical value, and the specific calculation formula is as follows: ,in (This represents the maximum stress value in the central region of the lens under the primary path). The radius of the central stress control region is taken as 1 / 4 of the inner diameter D of the carrier in this technical solution, which is used to limit the main range of thickness calibration. x and y are radial coordinates in a two-dimensional coordinate system (consistent with the two-dimensional coordinate system in step S101). This model effectively reduces the stress concentration by performing gradient fine adjustment on the thickness of the central region. The calibration model in the optical inspection instrument scenario is used to ensure that the uniformity of the central stress of the lens meets the accuracy detection requirements in the optical inspection instrument scenario.

[0062] For optical wearable device scenarios (02), the calibration model focuses on edge comfort and weight control, and the expression is:

[0063] ;

[0064] in This represents the maximum radial boundary of the carrier (i.e., D / 2). The edge thinning coefficient, in this technical solution, ranges from 0.1 to 0.3, and is determined by the lens material density ρ and the wearing weight threshold W. The calculation formula is: ;

[0065] The total weight of the lens in the primary path is denoted as 1. In the context of optical wearable devices, the calibration model reduces the lens weight and improves wearing comfort by nonlinearly thinning the thickness of the edge region while ensuring structural strength.

[0066] Step S202: Based on the thickness calibration parameters output by the calibration model, perform three-dimensional thickness mapping on the two-dimensional contour of the primary milling path and generate a three-dimensional coordinate point cloud.

[0067] It should be noted that this step generates a machining path point cloud in three-dimensional space by combining the thickness calibration model obtained in step S201 with the two-dimensional contour coordinates of the primary path.

[0068] For example, in a circular carrier scene, the nodes (x, y, z) on the two-dimensional contour are taken. i ,y i ), combined with the calibrated thickness h(x) i ,y i ), to obtain the three-dimensional coordinates (x i ,y i ,h(x i ,y i Connect the three-dimensional coordinates of all nodes in sequence to form the initial point cloud of the three-dimensional calibration milling path.

[0069] Step S203: Smooth the 3D point cloud to generate the final 3D calibration milling path.

[0070] Specifically, a B-spline curve fitting algorithm is used to interpolate and smooth the 3D point cloud to eliminate the discreteness of the point cloud, ensure the continuity and smoothness of the milling path, and finally output the 3D calibration milling path.

[0071] Step S300: Under the three-dimensional calibration milling process path, collect the spectral data of the optical lens, and adjust and correct the stress range of the optical lens under the three-dimensional calibration milling process path based on the spectral data.

[0072] It should be noted that in step S300, during the execution of the three-dimensional calibration milling path, the spectral data of the optical lens is collected in situ, the processing stress field distribution is analyzed in real time, and the three-dimensional calibration milling processing path is dynamically corrected to avoid stress exceeding the limit.

[0073] Specifically, in step S300, spectral data acquisition uses a micro Raman spectrometer, selecting sampling points on the three-dimensional calibration milling path, including the central region and the edge region, with no less than n sampling points in each of the central region and the edge region. In this technical solution, the micro Raman spectrometer is set with a laser wavelength of 532nm, a scanning step size of 0.5mm, and an integration time of 10s to ensure the accuracy and representativeness of the data.

[0074] Specifically, refer to Figure 3 It can be seen that the analysis method for stress range includes steps S301-S304.

[0075] Step S301: Obtain the characteristic peak values ​​based on the acquisition and preprocessing of spectral data.

[0076] It should be noted that step S301 is mainly used to preprocess the acquired raw spectral data to eliminate interference factors and extract effective stress features. The preprocessing specifically includes: smoothing the raw spectral data using a Gaussian filtering algorithm, setting the filtering window size to 5 consecutive data points to suppress random noise while retaining the wavenumber shift information of characteristic peaks; secondly, baseline correction is performed by fitting the background baseline of the spectrum using a cubic polynomial fitting method, and subtracting the fitted baseline from the raw spectral data to eliminate baseline shifts caused by fluorescence background, instrument light source fluctuations, and sample surface unevenness; finally, characteristic peak extraction is performed, i.e., using a local maximum detection algorithm to identify key Raman characteristic peaks in the spectrum (such as the 464 cm⁻¹ peak in quartz glass). -1 (characteristic peaks), it is worth noting that the preprocessing disclosed in step S301 is a mature spectral data processing method in the prior art, and the specific principle details will not be repeated here.

[0077] Step S302: Based on the preprocessed characteristic peak wave values ​​and the target characteristic peak wave values, and combined with the elastic modulus and Poisson's ratio of the optical lens material, construct a quantitative relationship between stress and wavenumber shift.

[0078] It should be noted that step S302 in this technical solution is mainly used to establish a direct correlation between spectral characteristics and processing stress, providing a quantitative basis for subsequent stress range analysis.

[0079] Specifically, the peak wave number shift is first defined as the difference between the peak wave number of the extracted characteristic peak after preprocessing and the peak wave number of the target characteristic peak under stress-free conditions. Then, the elastic modulus and Poisson's ratio of the material corresponding to the optical lens are retrieved from the material property library. Combining this with the classical theory of Raman spectroscopy stress detection in existing technologies, the quantitative relationship between stress and wave number shift is derived: Raman spectral stress = difference between the peak wave number of the target characteristic peak / Raman stress coefficient, where the Raman stress coefficient is a material-related constant used to quantify the conversion ratio between wave number shift and stress. Its calculation formula is Raman stress coefficient = (elastic modulus × Poisson's ratio) / [(1 − Poisson's ratio²) × Raman frequency shift - strain sensitivity coefficient]. In addition, the elastic modulus represents the stiffness of the optical lens material and is a known existing parameter value. Poisson's ratio represents the ratio of the transverse strain to the longitudinal strain of the material under stress, and is also a known existing parameter value in this technology. The Raman shift-strain sensitivity coefficient represents the shift in the characteristic peak wavenumber when the material strain increases by one micro-strain. This Raman shift-strain sensitivity coefficient is established by conducting standard tensile or compressive tests on the same batch of optical lens materials in advance, combined with synchronously acquired Raman spectral data, to establish a linear relationship between strain and characteristic peak wavenumber shift. The slope of this relationship is the Raman shift-strain sensitivity coefficient. In this technical solution, for quartz glass material, this coefficient is calibrated to 3.2 cm. -1 / GPa ensures the accuracy of quantitative relationships.

[0080] Step S303: Calculate the real-time machining stress value corresponding to each sampling point based on the quantitative relationship, and statistically analyze the stress data of all sampling points to determine the stress distribution range under the current three-dimensional calibration milling path.

[0081] It should be noted that step S303 in this technical solution is mainly used to convert spectral data into stress distribution results that can be analyzed intuitively, providing key data support for subsequent error compensation. By calculating the real-time processing stress value of each sampling point, the stress concentration area and stress extreme value can be located, thereby determining whether the stress distribution under the current three-dimensional calibration milling path meets the stress control standard in the process requirements, providing a quantitative basis for subsequent dynamic adjustment of path parameters and realization of error compensation.

[0082] Specifically, the range of stress distribution is determined by statistically analyzing the real-time stress values ​​of all sampling points to calculate the maximum, minimum, average, and standard deviation of stress. This outlines the stress distribution profile under the current processing path. At the same time, the statistically obtained maximum stress value is compared with the maximum allowable stress threshold preset by the process. If the maximum value exceeds the maximum allowable stress threshold, it is determined that there is a risk of stress exceeding the limit in the current path. If the maximum value does not exceed the limit, but the standard deviation of the stress distribution is greater than the preset dispersion threshold, it indicates that the stress distribution is uneven, which may lead to deformation of the optical lens surface or increased processing error.

[0083] In addition, by drawing a thermal map of stress distribution on the optical lens, and referring to... Figure 4 As can be seen, the stress distribution heatmap of the optical lens shows the location and intensity of stress concentration areas, providing a precise positioning basis for subsequent path correction. It should be added that in this technical solution, the stress distribution heatmap is generated by importing the three-dimensional coordinates of each sampling point and the corresponding real-time stress value into professional data visualization software, using the existing Kriging interpolation algorithm to perform spatial interpolation processing on the discrete sampling points, generating a continuous stress distribution surface, and then drawing it based on a preset stress level color scale (such as blue representing low stress and red representing high stress). It should be added that the stress distribution heatmap can intuitively present the spatial distribution characteristics of stress on the surface of the optical lens, helping technicians to quickly identify areas of stress concentration (such as the edge chamfer or the transition position of the central processing area), providing a visualized decision basis for subsequent path correction.

[0084] It should also be noted that, in actual use, the stress distribution heatmap also supports a dynamic update function, that is, the stress distribution image is automatically refreshed after each round of sampling, ensuring that technicians can grasp the stress change trend in the processing process in real time and adjust the milling parameters in a timely manner to optimize the stress distribution.

[0085] Step S304: Dynamically correct the three-dimensional calibration milling path based on the stress distribution range.

[0086] It should be noted that step S304 is mainly used to reduce the processing stress in the stress concentration area and optimize the overall stress distribution.

[0087] Specifically, the path dynamic correction adopts a graded adjustment strategy: for path segments where the maximum stress exceeds the process threshold, the milling feed rate of the path segment is reduced (e.g., from the original setting of 10mm / s to 6mm / s) and the single milling depth, while the cutting angle of the milling cutter is reduced to reduce local stress concentration by dispersing the machining load.

[0088] For path segments with excessive stress distribution dispersion, optimize the smoothness of the tool path, change the original straight transition path to an arc transition, reduce the spacing between adjacent paths, and balance the material removal rate to improve the uniformity of stress distribution.

[0089] It is worth noting that after each adjustment, step S304 will immediately re-acquire spectral data in the path segment and repeat the stress analysis process from steps S301 to S303. If the stress index still does not meet the standard, the milling parameters and trajectory will continue to be iteratively adjusted until the stress values ​​of all sampling points are within the preset threshold range and the standard deviation of the distribution is less than the dispersion threshold.

[0090] It should be added that the maximum allowable stress threshold in step S300 refers to the maximum stress limit that the optical lens material can withstand during the milling process. The maximum allowable stress threshold is set based on the fracture strength of the lens material, the processing requirements and the optical performance requirements of the final application scenario. In this technical solution, this value is the known attribute data of the optical lens itself.

[0091] The dispersion threshold is an indicator of the uniformity of stress distribution on the surface of an optical lens. Specifically, it is the upper limit of the standard deviation of stress values ​​at all sampling points. When the standard deviation of the stress distribution exceeds this threshold, it indicates that there are significant stress differences in different areas of the lens, which can easily lead to warping or a decrease in surface precision due to uneven stress release during subsequent processing. It should be noted that the dispersion threshold is obtained by conducting multiple sets of three-dimensional milling tests on the same batch of optical lens materials. Each set of tests uses different milling parameters (feed speed, depth of cut). During the processing, stress data (half from the center and half from the edge) at no less than 20 sampling points on the lens surface are collected using a micro Raman spectrometer. The standard deviation of stress distribution for each set of tests is calculated, and the surface defect rate (such as the number of cracks and deformations) of the lens after each set of tests is statistically analyzed. When the stress standard deviation exceeds a certain critical value, the defect rate increases (for example, when the standard deviation is >1.2 GPa, the defect rate is >10%). This critical value is set as the initial threshold, and then the dispersion threshold is reduced by 20% to 30% based on the initial threshold to accommodate fluctuations in the processing environment.

[0092] Step S400: Perform residual error source calibration on the corrected 3D calibrated milling path and generate the final milling path.

[0093] It should be noted that after the stress range is dynamically corrected in step S300, step S400 is used to handle residual error sources (such as tool wear, thermal deformation or material inhomogeneity) and improve machining accuracy through real-time compensation. It is important to emphasize that step S400 adopts a closed-loop control strategy, which combines sensor data and error compensation to generate the final milling machining path.

[0094] Specifically, refer to Figure 5 It can be seen that the method for generating the final milling path through error compensation includes steps S401-S403.

[0095] Step S401: Collect real-time error data of residual error sources.

[0096] It should be noted that step S401 in this technical solution is mainly used to synchronously monitor three types of key residual error sources, including: tool wear, thermal deformation and material removal deviation. By collecting these data in real time, error hotspots can be located (such as radial dimension deviation caused by tool wear or axial warping caused by thermal deformation), laying the data foundation for the compensation calculation in step S402 and avoiding the decrease in machining accuracy due to accumulated errors.

[0097] Specifically, for tool wear monitoring, a high-precision inductive displacement sensor scans the milling cutter edge every n minutes, records the radial wear, and predicts the wear trend through linear fitting; for thermal deformation monitoring, an infrared thermometer scans the optical lens processing area at a set frequency and triggers an alarm when the temperature difference exceeds 5°C; for material removal deviation detection, a laser interferometer compares the actual processing depth with the theoretical value in real time (for example, if the theoretical removal is 10 micrometers but the actual removal is 13 micrometers, a deviation of +3 micrometers is marked), and maps the deviation value to a three-dimensional coordinate point cloud.

[0098] Step S402: Construct dynamic compensation rules based on real-time error data and calculate the compensation amount.

[0099] It should be noted that step S402 in this technical solution is mainly used to convert the real-time error data collected in S401 into executable spatial compensation instructions, and to achieve quantitative compensation through a multi-source coupling model. Its core is to eliminate the influence of residual errors on the processing path and improve the surface accuracy of the final lens.

[0100] Specifically, to address tool wear errors, a path radial compensation is constructed based on the radial wear amount collected in real time by an inductive displacement sensor. The path radial compensation amount = radial wear amount × wear compensation coefficient (with a value range of 1.05-1.1, set manually according to the hardness of the processed material, and is a known numerical coefficient). At the same time, combined with the wear trend curve obtained by linear fitting, the wear amount in the next n minutes is predicted, and pre-compensation is added to the corresponding path segment in advance to avoid error accumulation. For cases of uneven wear of the milling cutter edge, local compensation adjustment is made at the tool position point. That is, for the actual tool radius deviation at each cutting point, a slight offset is made in the X / Y axis direction in the three-dimensional path coordinate to ensure that the cutting trajectory is consistent with the theoretical contour.

[0101] Step S403: Integrate the compensation amount into the three-dimensional calibration milling path to generate the final milling machining path.

[0102] It should be noted that step S403 is the final execution stage of the error compensation process. By converting the compensation amount of multi-source errors into precise adjustment of path coordinates, the machining accuracy is improved.

[0103] Specifically, the radial compensation, axial compensation, and depth compensation calculated in step S402 are first mapped to the coordinates of each tool position point in the three-dimensional path. For radial compensation caused by tool wear, a slight offset is applied to the tool position point coordinates in the X / Y axis directions (for example, when the radial wear is 0.02 mm, the X-axis offset is +0.022 mm, the Y-axis offset is -0.022 mm, and the corresponding wear compensation coefficient is 1.1). For axial deviation caused by thermal deformation, the machining depth is adjusted in the Z-axis direction (for example, when the temperature difference causes the lens to warp axially by 0.01 mm, the Z-axis coordinate is increased by 0.01 mm). For material removal deviation, the theoretical machining depth at the corresponding position is corrected based on the point cloud mapping results (for example, when the material removal deviation at a certain point is +3 μm, the machining depth at that point is reduced by 3 μm). It should be noted that the final milling machining path is generated by superimposing all compensation amounts onto the corresponding tool position point coordinates of the three-dimensional calibrated milling path to form a corrected coordinate sequence, and the final milling machining path is constructed based on this corrected coordinate sequence.

[0104] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended embodiments and their equivalents.

Claims

1. A method for intelligent generation and error compensation of milling paths for optical lenses, characterized in that, include: Based on the mechanical structural characteristics of optical lenses under preset assembly conditions, a primary milling processing path is planned. The preset assembly conditions define the specific application scenarios of the optical lenses, including optical testing instruments and optical wearable devices. The mechanical structural characteristics are the carriers for assembling optical lenses in specific application scenarios, including optical lens mounts or optical lens frames. According to the processing requirements, the thickness of the optical lens in the primary milling process is calibrated, and a three-dimensional calibration milling process is generated. The processing requirements are the application scenarios of the optical lens. Different scenarios correspond to differences in the degree of stress concentration at the center of the optical lens or the edge comfort and weight control. Under the three-dimensional calibration milling process, the spectral data of the optical lens is collected, and the stress range of the optical lens under the three-dimensional calibration milling process is adjusted and corrected based on the spectral data. The residual error sources are calibrated on the corrected 3D calibrated milling path, and the final milling path is generated. The residual error sources include tool wear, thermal deformation, and material removal deviation.

2. The method for intelligent generation and error compensation of milling processing paths for optical lenses according to claim 1, characterized in that: Methods for generating primary milling machining paths include: Based on the mechanical structural features, the milling processing range is mapped within the optical lens. A two-dimensional coordinate system is created at the contact surface position between the carrier and the optical lens corresponding to the mechanical structural features. The two-dimensional coordinate system takes the center point of the carrier as the origin, the horizontal axis represents the radial offset distance of the optical lens on the contact surface of the carrier, and the vertical axis corresponds to the position parameters of the axial height or curvature direction. According to the contour dimensions of the carrier and the assembly tolerance requirements of the optical lens, the milling processing range of the optical lens is defined in the two-dimensional coordinate system. The geometric shape of the mechanical structure is obtained, and the preliminary milling path is determined within the milling processing range, wherein the geometric shape is the two-dimensional contour shape of the contact area between the carrier and the optical lens.

3. The method for intelligent generation and error compensation of milling processing paths for optical lenses according to claim 2, characterized in that: When the carrier is an optical lens mount or an optical lens frame, the radial machining range P of the milling process is [0, D / 2], and the axial machining range Z is calculated based on the radius of curvature R of the optical lens, where D is the inner diameter of the carrier, and the effective range of the axial height is set to [H-Δh, H+Δh], where H is the axial height of the edge support surface, and Δh is the assembly tolerance.

4. The method for intelligent generation and error compensation of milling processing path for optical lenses according to claim 3, characterized in that: The formula for calculating the axial machining range Z is as follows: Using the axial height H of the lens mount / frame edge support surface as a reference, the reference axial coordinates required for spherical machining at the radial position P are obtained. For a point on the sphere with a radial position PP (radial distance P from the center of the sphere), the axial coordinates of this point (calculated based on the geometry of the sphere itself) and the axial coordinates of the edge are... The axial coordinate of the sphere itself is located at the inner diameter edge of the optical lens (radial position P=D / 2).

5. The method for intelligent generation and error compensation of milling processing paths for optical lenses according to claim 1, characterized in that: Methods for generating 3D calibration milling machining paths include: The processing requirements are analyzed and thickness calibration parameters are constructed. These requirements are quantified using application scenario identifiers: optical inspection instruments are coded as 01, and optical wearable devices are coded as 02. For scenario 01, the calibration model is as follows: ; in Let be the initial thickness distribution function of the optical lens under the primary milling process. This is the stress calibration coefficient, whose value is determined by both the material's elastic modulus E and yield strength σᵧ. It is a specific numerical value, and the specific calculation formula is as follows: ,in This represents the maximum stress value in the central region of the lens under the primary path. Let x be the radius of the central stress control region, and y be the radial coordinates in a two-dimensional coordinate system. Based on the thickness calibration parameters output by the calibration model, a three-dimensional thickness mapping is performed on the two-dimensional contour of the primary milling machining path to generate a three-dimensional coordinate point cloud. The 3D point cloud is smoothed to generate the final 3D calibration milling path.

6. The method for intelligent generation and error compensation of milling processing paths for optical lenses according to claim 5, characterized in that: For optical wearable device scenarios (02), the calibration model focuses on edge comfort and weight control, and the expression is: ； in The maximum radial boundary of the carrier. The edge thinning factor is determined by the lens material density ρ and the wearing weight threshold W, and is calculated using the following formula: , This represents the total weight of the lens along the primary path.

7. The method for intelligent generation and error compensation of milling processing paths for optical lenses according to claim 1, characterized in that: Spectral data acquisition was performed using a micro Raman spectrometer. Sampling points included the central and edge regions, with at least n sampling points in each region. The stress range adjustment and correction included: Characteristic peak values ​​are obtained based on the acquisition and preprocessing of spectral data; Based on the preprocessed characteristic peak wave values ​​and the target characteristic peak wave values, and combined with the elastic modulus and Poisson's ratio of the optical lens material, a quantitative relationship between stress and wavenumber shift is constructed. The real-time machining stress value corresponding to each sampling point is calculated based on the quantitative relationship, and the stress data of all sampling points are statistically analyzed to determine the stress distribution range under the current three-dimensional calibration milling path; The three-dimensional calibration milling path is dynamically corrected based on the stress distribution range.

8. The method for intelligent generation and error compensation of milling processing paths for optical lenses according to claim 1, characterized in that: Methods for generating the final milling path through error compensation include: Collect real-time error data of residual error sources, including: using an inductive displacement sensor to monitor the radial wear of the tool, using an infrared thermometer to scan thermal deformation, and using a laser interferometer to detect material removal deviations; Dynamic compensation rules are constructed based on real-time error data, and the compensation amount is calculated. The compensation amount is integrated into the 3D calibration milling path to generate the final milling machining path.

9. The method for intelligent generation and error compensation of milling processing paths for optical lenses according to claim 8, characterized in that: The wear compensation coefficient is set manually based on the hardness of the material being processed. The final milling path is generated by superimposing all compensation values ​​onto the corresponding tool position coordinates of the three-dimensional calibrated milling path to form a corrected coordinate sequence. The final milling path is then constructed by associating this corrected coordinate sequence.

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