A fast tool servo machining method for microlens array, medium and device

Abstract

The present application relates to the technical field of ultra-precision optical manufacturing, and particularly relates to a fast tool planing machining method for a microlens array, a medium and equipment. The method comprises the following steps: determining a feasible planing tool without interference according to surface shape data of a microlens array to be machined; constructing a parameter physical model of a planing base frequency, surface roughness and a machining time length of a single unit based on microlens unit parameters, tool parameters and machining parameters; taking parameter limit conditions as nonlinear constraints and total machining time length as an objective function to optimize and solve fs, Rt and D L , fx to obtain the shortest machining time length; and completing machining by using the optimized parameters. The present application innovatively constructs a multi-physical parameter model, realizes collaborative optimization of optical performance (surface shape), process capability (roughness, dynamic characteristics) and manufacturing efficiency (machining time), ensures nanoscale roughness and dynamic stability, significantly shortens the machining cycle of a large-scale array, and provides an efficient path for batch manufacturing of ultra-precision optical elements.

Description

Technical Field

[0001] This invention relates to the field of ultra-precision optical manufacturing technology, and in particular to a fast-tool planing method, medium, and equipment for microlens arrays. Background Technology

[0002] Optical microstructures with complex micro / nano topologies are widely used in aerospace, optoelectronic communications, and weaponry due to their unique optical properties. However, these surfaces require sub-micron level surface accuracy and nano-level surface roughness, making them difficult to fabricate effectively using traditional manufacturing systems. Therefore, novel manufacturing equipment and processing technologies for optical microstructures have become a research hotspot in both academia and industry. Among various methods for manufacturing optical microstructures, processing technology based on Fast Tool Servo (FTS) systems is considered a promising technology for achieving efficient and ultra-precision fabrication of these surfaces.

[0003] When machining large-scale microlens arrays, to shorten machining time while ensuring machining quality, a single-point diamond planing method based on fast tool servo can be used. First, a suitable tool needs to be selected according to the specific parameters of the aspherical lens to avoid interference during machining. Current technologies use empirical methods to select parameters, which cannot achieve ideal machining results. Especially when machining large-scale, complex micro / nano topological optical microstructure surfaces, there is still no systematic and accurate method for optimizing process parameters.

[0004] Therefore, there is an urgent need for a method to optimize the processing parameters of microlens arrays in order to improve the efficiency of planing while ensuring processing accuracy. Summary of the Invention

[0005] To address one of the aforementioned technical problems, the present invention adopts the following technical solution: According to one aspect of the present invention, a fast-tool planing method for machining microlens arrays is provided, the method comprising the following steps: Based on the surface shape data of the microlens array to be processed, at least one feasible planing tool is determined; the feasible planing tool does not interfere with the surface shape of the microlens unit to be processed; Based on the unit parameters of the microlens units in the microlens array to be processed, the planing tool parameters, and the planing parameters, parametric physical models corresponding to the planing fundamental frequency f, surface roughness Ra, and processing time T1 of a single unit are generated. The unit parameters include: the unit side length D of the microlens unit. L The microlens array side length L; planing tool parameters include: tool tip radius Rt; planing machining parameters include: feed rate fx after each planing operation, planing speed fs; and return speed fb. The constraints corresponding to each parameter are the nonlinear constraints output by the physical model for that parameter. The total processing time T is the objective function, where fs, Rt, and D are the parameters. L And fx is the optimization variable. The physical model of each parameter is optimized by nonlinear constraints to obtain fs, Rt, and D corresponding to the shortest total processing time. L and fx; The optimized solution yields fs, Rt, and D. L And fx performs planing processing on the microlens array to be processed.

[0006] According to a second aspect of the present invention, a non-transitory computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the above-described method for planing microlens arrays.

[0007] According to a third aspect of the present invention, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for planing microlens arrays.

[0008] This invention has at least one of the following beneficial effects: In existing fast tool servo (FTS) machining technology for microlens arrays, tool selection generally relies on operator experience or simple geometric matching, lacking a systematic analysis of the interference relationship between the special geometry of diamond tools (such as curved tips in the planing direction and sharp angles in the vertical direction) and the local geometric features of the aspherical surface of the microlens. This coarse selection is prone to causing tool rake-off angle interference or arc mismatch in high curvature or steep slope regions, resulting in surface distortion and making it difficult to meet sub-micron level surface accuracy requirements. In contrast, this invention explicitly proposes: determining at least one feasible planing tool based on the surface shape data of the microlens array to be processed. Based on the aspherical analytical expression of the target microlens unit, the local slope and radius of curvature at each point on its surface are quantitatively calculated, and the minimum required tool rake angle, minimum tool clearance angle, and maximum allowable tool arc radius are deduced accordingly, forming a clear interference avoidance criterion. This transforms tool selection from experience-based judgment to a geometrically calculable and verifiable scientific process, fundamentally avoiding machining errors caused by tool geometric mismatch and significantly improving surface shape reproduction accuracy and process reliability.

[0009] Existing FTS machining parameter settings mostly employ trial-and-error or table lookup methods, failing to establish a coupling relationship model between surface roughness, dynamic stability (such as planing fundamental frequency), and machining efficiency. This often results in sacrificing surface quality for high efficiency or excessively sacrificing machining time to maintain accuracy, making it difficult to achieve synergistic optimization of "high efficiency + high precision." This invention innovatively constructs a multi-physical parameter model including surface roughness Ra, planing fundamental frequency f, and single-piece machining time T1. Using the total machining time T as the objective function, it incorporates feed rate fs, feed amount fx, tool radius Rt, and unit side length D. L As optimization variables, the optimal parameter combination is solved through nonlinear constraint optimization. This technical solution achieves unified modeling and collaborative optimization of optical performance (microlens surface shape), process capability (roughness, dynamic characteristics), and manufacturing efficiency (processing time). Compared with existing technologies, this invention not only ensures nanoscale surface roughness and structural dynamic stability, but also significantly shortens the processing cycle of large-scale arrays, providing an efficient and engineerable path for the mass production of ultra-precision optical components. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 A flowchart of a fast-tool planing method for microlens arrays provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of a planing tool provided in an embodiment of the present invention, wherein the upper part is a three-dimensional view of the planing tool, and the lower left part is a view along the feed direction (x). t The tool cross-section, with the lower right side showing the section along the planing direction (y). t The cross section of the tool; Figure 3 This is a schematic diagram of the tool path for planing provided in an embodiment of the present invention; Figure 4 This is a schematic diagram showing the difference in elevation between the blade tip arc and a point on the aspherical cross section, provided in an embodiment of the present invention. Figure 5 This is a schematic diagram of the tool mark height corresponding to each point in the feed direction, provided by an embodiment of the present invention. Figure 6 This is a schematic diagram of the interference of the tool's front and rear angles in the feed direction, provided for an embodiment of the present invention. Detailed Implementation

[0012] 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.

[0013] As one possible embodiment of the present invention, such as Figure 1 As shown, a fast-tool planing method for machining microlens arrays is provided, which includes the following steps: S100: Based on the surface shape data of the microlens array to be processed, determine at least one feasible planing tool. The feasible planing tool does not interfere with the surface shape of the microlens unit to be processed.

[0014] like Figure 2 As shown, due to the special structural form of the tool cross-section along the feed direction and the tool cross-section along the planing direction, specifically, S100 includes: S101: Along the planing direction (e.g.) Figure 3 The aspherical surface of the microlens unit is discretized into N1 points (in the Y direction), and the slope corresponding to each discrete point is calculated.

[0015] S102: Based on the maximum slope k corresponding to all discrete points max The minimum tool limit rake angle α for generating the planing tool. min and minimum tool limit back angle β min Considering the symmetry of aspherical surfaces, the rake angle of the cutting tool is therefore limited to the same value. α min and β min The following conditions must be met: .

[0016] Among them, Z i and Z i+1 Let represent the vector height of the i-th and (i+1)-th discrete points among the N1 points along the planing direction, and Δ represent the step size between the two discrete points.

[0017] S103: If the rake angle α of the planing tool t >90°-α min And the tool clearance angle r of the planing tool t >β min If so, the planing tool is determined as the initially feasible planing tool.

[0018] like Figure 6 As shown, to avoid interference between the tool's rake angle and the aspherical surface shape in the planing direction during machining, the tool rake angle α of the planing tool needs to be... t>90°-α min And the tool clearance angle r of the planing tool t >β min This generates the initial selection conditions for the planing tool.

[0019] S104: Along the feed direction (e.g.) Figure 3 The aspherical surface of the microlens unit (in the X direction) is discretized into N² points, and the sag corresponding to each discrete point is calculated. The feed direction is perpendicular to the planing direction.

[0020] S105: Use the difference method to solve for the first derivative Z' and second derivative Z' of each discrete point in the curve corresponding to the vector height of N2 discrete points.

[0021] Specifically, the first derivative Zi' and the second derivative Zi” of the i-th discrete point among the N2 points along the feed direction satisfy the following conditions: ; ; Among them, Z 1 i and Z 1 i+1 This represents the vector height of the i-th and (i+1)-th discrete points among the N2 points along the feed direction.

[0022] S106: Determine the maximum tip limiting radius Rt of the planing tool based on Z' and Z”. max Rt max The following conditions must be met: .

[0023] S107: If the initial feasible maximum tip radius of the planing tool is Rt1 <Rt max If so, the initially feasible planing tool is determined as the target planing tool.

[0024] Since the edge of the rake face of the planing tool is an arc, it may interfere with the surface shape of the microlens unit in the feed direction during planing, thus affecting the surface accuracy. Therefore, in this embodiment, differential processing is used to calculate the radius of curvature of the microlens unit's surface shape at each point in the feed direction, and then the minimum radius of curvature is taken as Rt. max When selecting cutting tools, only the maximum tip radius Rt1 of the planing tool is considered. <Rt max This indicates that the planing tool will not interfere with the surface shape of the microlens unit in the feed direction, thus ensuring machining accuracy.

[0025] In this embodiment, based on the aspherical analytical expression of the target microlens unit, the local slope and radius of curvature at each point on its surface are quantitatively calculated. Based on this, the minimum rake angle, minimum clearance angle, and maximum allowable radius of curvature required by the tool are deduced, forming a clear interference avoidance criterion. This transforms tool selection from an experience-based judgment to a geometrically calculable and verifiable scientific process, fundamentally avoiding machining errors caused by tool geometric mismatch and significantly improving surface shape reproduction accuracy and process reliability.

[0026] Prior to S100, the method also includes: S110: Determine the surface shape of each microlens unit in the microlens array to be processed, based on the optical requirements. All microlens units in the array have the same surface shape. The surface shape of each microlens unit is aspherical.

[0027] First, considering that the three-dimensional surface shape of a microlens directly determines its optical performance, it is necessary to first establish a general equation for aspherical surfaces based on the optical performance requirements of the microlens unit. Then, a mathematical model of the microlens surface is constructed to accurately describe its three-dimensional aspherical profile. ; in, This represents the normalized radial distance from any point to the optical axis; c = 1 / R is the curvature. is the radius of curvature at the lens vertex; k is the conic coefficient; A, B, C, and D are the fourth, sixth, eighth, and tenth order aspherical coefficients, respectively, used to correct higher-order aberrations. The origin of the coordinate system is at the bottom of the aspherical surface, with the positive z-axis pointing inwards from the concave surface.

[0028] S120: Determine the equivalent aperture of the microlens unit to be processed based on its surface shape.

[0029] S130: Determine D based on the equivalent caliber. L And the range of values ​​corresponding to L.

[0030] After solving the aspherical equation of the microlens unit, the equivalent aperture corresponding to a given sag can be calculated. In microlens design, the sag is typically used to define the effective optical area. Microlenses do not extend infinitely; their effective imaging area is usually limited by a maximum sag value. Edge areas exceeding this sag may be clipped or ignored due to excessive aberrations and low light energy utilization. Therefore, given a sag d, the equivalent aperture L1 of the corresponding microlens unit can be derived, which is the diameter of the circular area covered by that sag. In this embodiment, the given sag is the distance from the lowest point to the highest point of the aspherical surface, i.e., the maximum sag.

[0031] Correspondingly, the relationship between L1 and d is as follows: .

[0032] To ensure a certain spacing between the microlens units, the unit side length D will be... L The diameter is set to be slightly larger than the equivalent aperture L1 of the aspherical surface. After obtaining L1, the side length L of the large-scale microlens array can be calculated based on the microlens array size N. L satisfies the following condition: If the calculated value is not an integer, it needs to be removed and processed to ensure that the parameter is an integer.

[0033] Following S100, the method further includes: S210: Obtain the set of sags Z1 of multiple discrete points in the surface shape of the aspherical lens by using the aspherical analytical equation corresponding to the microlens unit.

[0034] Specifically, including: S210.1. Take the theoretical aspherical surface and the tool arc section perpendicular to the planing direction.

[0035] S210.2 Calculate the sag Z1 of each discrete point on each cross section perpendicular to the planing direction of the aspherical lens.

[0036] ; ; Where r1 i N is the radial distance of the i-th discrete point, and N4 is the total number of discrete points on each cross section.

[0037] S220: Based on any feasible planing tool and the corresponding tool planning path, obtain the set of sags Z2 of multiple discrete points in the surface shape of the aspherical lens after theoretical machining.

[0038] Specifically, including: S220.1. Based on the tool selected to meet the requirements of the rake angle and tool tip radius, tool machining modeling can be performed, and the sag Z2 of each discrete point on each cross section after theoretical machining can be calculated: ; S230: Generate the maximum sag difference ΔZ based on Z1 and Z2. max .

[0039] Specifically, including: S230.1. Translate both Z1 and Z2 to the origin (aligning discrete points), and calculate the difference in elevation ΔZ between the two at each discrete point on each cross section: like Figure 4 As shown, ; Then, take the largest ΔZ as ΔZ. max If the error meets the machining accuracy requirements, the machining plan is deemed feasible.

[0040] S240: If △Z max If the value is less than △Zy, then execute steps S200 to S400. △Zy is the preset theoretical shape error threshold.

[0041] S250: If △Z max If the value is greater than or equal to △Zy, then stop the subsequent operations and generate an alarm message indicating that the current tool cannot meet the machining accuracy requirements.

[0042] S210 to S250 is the process of theoretical shape error assessment. By calculating the difference between the theoretical aspherical surface shape and the theoretical tool-machined surface shape in advance, the theoretical machining accuracy can be evaluated in advance, and the machining plan can be judged in advance.

[0043] S200: Based on the element parameters of the microlens units in the microlens array to be processed, the planing tool parameters, and the planing parameters, generate parametric physical models corresponding to the planing fundamental frequency f, surface roughness Ra, and processing time T1 for a single unit. Element parameters include: the element side length D of the microlens unit. L The microlens array side length L. Planing tool parameters include: tool tip radius Rt. Planing machining parameters include: feed rate fx after each planing pass, planing speed fs, and return speed fb.

[0044] Specifically, the physical models corresponding to the planing fundamental frequency f, surface roughness Ra, and machining time T1 of a single unit respectively satisfy the following conditions: .

[0045] .

[0046] like Figure 5 As shown, h i and h j Let h be the tool mark heights corresponding to the i-th and j-th discrete points, respectively, where i = 1, 2, ..., N3, j = 1, 2, ..., N3. i Ra is the height of the tool marks at each discrete point, and its arithmetic mean deviation is taken as the estimated value of Ra.

[0047] N3 represents the total number of discrete sampling points in the horizontal direction between the top of the tool mark arc center and the edge of the tool mark arc after each planing feed. xi represents the horizontal distance from the i-th discrete point to the center of the tool mark arc.

[0048] .

[0049] The objective function corresponding to T satisfies the following condition: .

[0050] in, The total number of planing operations for the lens array to be processed.

[0051] S300: The constraints corresponding to each parameter are the nonlinear constraints output by the physical model of the corresponding parameter. The total processing time T is the objective function, where fs, Rt, and D are the parameters. L And fx is the optimization variable. The physical model for each parameter is optimized using nonlinear constraints to obtain fs, Rt, and D corresponding to the shortest total processing time. L and fx.

[0052] The S300 includes: S300.1, Set the optimization variable vector x = [fs, Rt, D] L [f(x)]; and the upper and lower boundaries of all optimized parameters in x. For example, Ra(x) < 2nm, f(x) < 300Hz, T1(x) ≤ 0.5s and the equality constraint Rt = 100μm. Since each selected tool has known and definite parameters, Rt is an equality constraint.

[0053] S300.2, Establish nonlinear constraints: ; S300.3, Establish the objective function: minT(x): ; S300.4. Iterative optimization is performed by calling the fmincon function in MATLAB. Within a search space bounded by upper and lower bounds, starting from the initial value x0, the optimal solution to the objective function T(x) is sought, and the optimal solution x and the corresponding objective value minT(x) are returned.

[0054] S400: fs, Rt, D obtained from the optimized solution L And fx performs planing processing on the microlens array to be processed.

[0055] This embodiment innovatively constructs a multi-physical parameter model that includes surface roughness Ra, planing fundamental frequency f, and single-piece machining time T1. The model uses the total machining time T as the objective function, and incorporates feed rate fs, feed amount fx, tool radius Rt, and unit side length D. LAs optimization variables, the optimal parameter combination is solved through nonlinear constraint optimization. This technical solution achieves unified modeling and collaborative optimization of optical performance (microlens surface shape), process capability (roughness, dynamic characteristics), and manufacturing efficiency (processing time). Compared with existing technologies, this invention not only ensures nanoscale surface roughness and structural dynamic stability, but also significantly shortens the processing cycle of large-scale arrays, providing an efficient and engineerable path for the mass production of ultra-precision optical components.

[0056] Furthermore, the present invention provides the following embodiments to illustrate the effectiveness of the method of the present invention. An aspherical surface shape equation for the microlens unit is established, and finally, according to the corresponding optical performance requirements, the parameters of the aspherical equation are set as follows: k=6.6930, A=-0.0069, B=-0.0007, C=0, D=0.

[0057] Correspondingly, given a height d = 0.25 μm, the effective aperture (i.e., equivalent aperture) L1 of the microlens at that height can be calculated: ; To ensure a certain spacing between lenses, the side length of the unit is set slightly larger than the equivalent diameter of the aspherical surface, that is, D... L Set to 20 μm, then calculate the side length of the large-scale microlens array based on the microlens array size N=200000: .

[0058] To avoid interference between the tool tip arc and the lens surface, the local maximum slope and minimum radius of curvature need to be calculated to determine the limiting geometric parameters of the tool. The maximum slope value is calculated to be: k max =0.0744; Therefore, the minimum tool limit rake angle α can be derived. min and minimum tool limit back angle β min : .

[0059] Maximum blade tip radius: .

[0060] Therefore, an existing single-crystal diamond circular arc cutter with a tip radius Rt=100μm, a rake angle of 0° and a clearance angle of 7° was selected to complete the machining of the microlens array on a five-axis fast tool servo (FTS) planer.

[0061] Before machining, to verify whether the tool tip arc can reproduce the designed surface shape, it is necessary to calculate the height difference between the theoretical surface shape and the actual tool tip trajectory, and then obtain the maximum height difference ΔZ. max .

[0062] Calculations show that when i = 7171, the corresponding sag in Z1 is 0.1249, and the sag in Z2 is 0.1251. At this time, ΔZ... max =0.0002. This value is much smaller than λ / 10, indicating that the selected tool and machining path meet the sub-micron surface accuracy requirements. λ is the wavelength of the laser interferometer used for surface accuracy measurement, such as 632.8nm.

[0063] Then, with Ra < 2nm, f < 300Hz, T1 ≤ 0.5s and the equality constraint Rt = 100μm as nonlinear constraints, and T as the objective function, optimization was performed. The fmincon function in MATLAB was used for iterative solution, and fs was obtained after iterative convergence. * =6000μm / s; Rt * =100μm (process fixed); fx * =5nm; T1 * =0.0267s; T * =1.5h; By back-substituting the optimal value to verify the satisfaction of all constraints, the shortest processing time for a single microlens was confirmed to be 0.0267s.

[0064] On-site verification: The actual processing of an array of 200,000 microlenses took 1.5 hours. The surface shape error PV ≤ 0.10 μm, the surface roughness Ra ≤ 2 nm, and the fundamental frequency 300 Hz all met the design requirements.

[0065] Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0066] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, mobile terminal, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0067] In an exemplary embodiment of this disclosure, an electronic device capable of implementing the above-described method is also provided.

[0068] Those skilled in the art will understand that various aspects of the present invention can be implemented as systems, methods, or program products. Therefore, various aspects of the present invention can be specifically implemented in the following forms: entirely in hardware, entirely in software (including firmware, microcode, etc.), or in a combination of hardware and software, collectively referred to herein as “circuit,” “module,” or “system.”

[0069] An electronic device according to this embodiment of the invention. The electronic device is merely an example and should not be construed as limiting the functionality or scope of the embodiments of the invention.

[0070] Electronic devices are manifested in the form of general-purpose computing devices. Components of an electronic device may include, but are not limited to: at least one processor, at least one memory, and buses connecting different system components (including memory and processor).

[0071] The memory stores program code that can be executed by a processor, causing the processor to perform the steps described in the "Exemplary Methods" section above, according to various exemplary embodiments of the present invention.

[0072] The storage may include readable media in the form of volatile storage, such as random access memory (RAM) and / or cache memory, and may further include read-only memory (ROM).

[0073] The storage may also include programs / utilities having a set (at least one) of program modules, including but not limited to: an operating system, one or more applications, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0074] A bus can represent one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus that uses any of the various bus architectures.

[0075] The electronic device can also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication can be performed via input / output (I / O) interfaces. Furthermore, the electronic device can communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter. The network adapter communicates with other modules of the electronic device via a bus. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0076] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of the present invention may also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of the present invention described in the "Exemplary Methods" section above.

[0077] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0078] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0079] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0080] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0081] Furthermore, the accompanying drawings are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention and are not intended to be limiting. It is readily understood that the processes shown in the above drawings do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0082] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0083] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A fast-tool planing method for machining microlens arrays, characterized in that, The method includes the following steps: Based on the surface shape data of the microlens array to be processed, at least one feasible planing tool is determined; the feasible planing tool does not interfere with the surface shape of the microlens unit to be processed; Based on the unit parameters of the microlens units in the microlens array to be processed, the planing tool parameters, and the planing processing parameters, parametric physical models corresponding to the planing fundamental frequency f, surface roughness Ra, and processing time T1 of a single unit are generated; the unit parameters include: the unit side length D of the microlens unit. L The microlens array side length L; planing tool parameters include: tool tip radius Rt; planing machining parameters include: feed rate fx after each planing operation, planing speed fs; and return speed fb. The constraints corresponding to each parameter are the nonlinear constraints output by the physical model for that parameter. The total processing time T is the objective function, where fs, Rt, and D are the parameters. L And fx is the optimization variable. The physical model of each parameter is optimized by nonlinear constraints to obtain fs, Rt, and D corresponding to the shortest total processing time. L and fx; The optimized solution yields fs, Rt, and D. L and fx performs planing processing on the microlens array to be processed; The physical models corresponding to the planing fundamental frequency f, surface roughness Ra, and single-unit machining time T1 respectively satisfy the following conditions: ； ， ； h i and h j Let be the tool mark heights corresponding to the i-th and j-th discrete points, respectively, i=1,2…N3, j=1,2…N3; N3 is the total number of discrete sampling points in the horizontal direction between the top of the tool mark arc center and the edge of the tool mark arc after each planing feed; xi is the horizontal distance between the i-th discrete point and the center of the tool mark arc. ； The objective function corresponding to T satisfies the following condition: ； in, The total number of planing operations for the lens array to be processed; L1 is the equivalent aperture of the corresponding microlens unit derived from the given sag, that is, the diameter of the circular area covered by the sag, where the sag is the distance from the lowest point to the highest point of the aspherical surface.

2. The method according to claim 1, characterized in that, The constraints corresponding to each parameter are the nonlinear constraints output by the physical model for that parameter. The total processing time T is the objective function, where fs, Rt, and D are the parameters. L And fx is the optimization variable, and the physical model of each parameter is optimized and solved by nonlinear constraints; To obtain the fs, Rt, and D corresponding to the shortest total processing time L and fx, including: Iterative optimization is performed by calling the fmincon function in MATLAB.

3. The method according to claim 1, characterized in that, Before determining at least one feasible planing tool based on the surface shape data of the microlens array to be processed, the method further includes: The surface shape of the microlens unit to be processed is determined according to the optical requirements corresponding to the microlens array to be processed; all the microlens units to be processed in the microlens array to be processed have the same surface shape; The equivalent aperture of the microlens unit to be processed is determined based on the surface shape of the microlens unit to be processed. Based on the equivalent caliber, determine D L And the range of values ​​corresponding to L.

4. The method according to claim 1, characterized in that, Based on the surface shape data of the microlens array to be processed, at least one feasible planing tool is determined, including: The aspherical surface of the microlens unit is discretized into N1 points along the planing direction, and the slope corresponding to each discrete point is calculated. Based on the maximum slope k corresponding to all discrete points max The minimum tool limiting rake angle α of the planing tool is generated. min and minimum tool limit back angle β min ;α min and β min The following conditions must be met: ； ； Among them, Z i and Z i+1 Let represent the vector height of the i-th and (i+1)-th discrete points, and Δ represent the step size between the two discrete points; If the rake angle α of the planing tool t >90°-α min And the tool clearance angle r of the planing tool t >β min If so, the planing tool is determined as an initially feasible planing tool.

5. The method according to claim 1, characterized in that, The surface shape of the microlens unit to be processed is aspherical; After determining at least one feasible planing tool based on the surface shape data of the microlens array to be processed, the method further includes: By using the aspherical analytical equation corresponding to the microlens unit, the set of sags Z1 of multiple discrete points in the aspherical lens surface shape is obtained; Based on any feasible planing tool and the corresponding tool planning path, obtain the set of sags Z2 of multiple discrete points in the surface shape of the aspherical lens after theoretical machining; Based on Z1 and Z2, generate the maximum sag difference ΔZ. max ; If △Z max If △Zy is less than 1, then based on the unit parameters of the microlens unit to be processed in the microlens array to be processed, the planing tool parameters and the planing processing parameters, a parametric physical model corresponding to the planing fundamental frequency f, surface roughness Ra and processing time T1 of a single unit is generated respectively; where △Zy is a preset theoretical shape error threshold.

6. The method according to claim 5, characterized in that, If △Z max If the value is greater than or equal to △Zy, then stop the subsequent operations and generate an alarm message indicating that the current tool cannot meet the machining accuracy requirements.

7. A non-transitory computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements a fast-tool planing method for microlens arrays as described in any one of claims 1 to 6.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements a fast-tool planing method for microlens arrays as described in any one of claims 1 to 6.

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