CN114063281A - Design method for lens optical system by artificial intelligence - Google Patents
Design method for lens optical system by artificial intelligence Download PDFInfo
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- CN114063281A CN114063281A CN202111395392.2A CN202111395392A CN114063281A CN 114063281 A CN114063281 A CN 114063281A CN 202111395392 A CN202111395392 A CN 202111395392A CN 114063281 A CN114063281 A CN 114063281A
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Abstract
The invention relates to the technical field of optical lens design, in particular to a design method for an artificial intelligence lens optical system. The method comprises the following steps: s1, acquiring market demands; s2, calling a screening module according to market demands to obtain lens parameters; s3, calling an algorithm optimizing module according to the lens parameters to obtain an initial structure of the lens; s4, calling an interface interaction module according to the initial structure to obtain optimization parameters of the lens; s5, calling a design optimization module according to the optimization parameters to obtain optical design parameters of the lens; s6, calling an artificial intelligence evaluation module to evaluate whether the optical design parameters in the step S5 meet the requirements of the lens parameters in the step S2; and if the requirements are met, obtaining the final design of the lens. According to the invention, the optical system can be intelligently optimized through the artificial intelligence system, the complexity of the optical design is simplified, the optimization efficiency of the optical design is effectively improved, and the efficiency is higher.
Description
Technical Field
The invention relates to the technical field of optical lens design, in particular to a design method for an artificial intelligence lens optical system.
Background
With the rapid development of mobile phone lenses, smart homes and vehicle-mounted lenses, products are continuously updated and iterated. The method has the advantages that great pressure is exerted on working quality and innovation for optical design engineers, lens design is a complex engineering problem, in the traditional optical design process, the optical design engineers are required to master actual experience in the design process, the workload is huge, the optimization efficiency is slow, and a great amount of experience and basic knowledge are required.
Disclosure of Invention
In view of the above disadvantages and shortcomings of the prior art, the present invention provides a method for designing an artificial intelligence based lens optical system, which solves the technical problems of huge workload, slow optimization efficiency, etc. in the prior art.
In order to achieve the purpose, the invention adopts the main technical scheme that:
the invention provides a design method of an artificial intelligence lens optical system, which comprises the following steps: s1, acquiring market demands; s2, calling a screening module according to market demands to obtain lens parameters; s3, calling an algorithm optimizing module according to the lens parameters to obtain an initial structure of the lens; s4, calling an interface interaction module according to the initial structure to obtain optimization parameters of the lens; s5, calling a design optimization module according to the optimization parameters to obtain optical design parameters of the lens; s6, calling an artificial intelligence evaluation module to evaluate whether the optical design parameters in the step S5 meet the requirements of the lens parameters in the step S2; and if the requirements are met, obtaining the final design of the lens.
Further, if the request is not satisfied in step S6, the process returns to step S4 to reconfirm the optimization parameters.
Further, in step S6, if there is a defect in the design, the process returns to step S3 to reconfirm the original structure.
Further, in step S2, the screening module analyzes the demand information according to the market demand to obtain a lens optical performance index, a lens structure index, and a yield index; and each index obtained by analysis is used as a judgment basis for the algorithm optimizing module and the artificial intelligence evaluation module.
Further, in step S3, the algorithm optimizing module screens out an initial structure that meets the shot parameters from a database through an artificial intelligence system; if the artificial intelligence system does not find the initial structure which accords with the lens parameters from the database, the artificial intelligence system supplements the initial structure data to the database, and then re-screens the initial structure which accords with the lens parameters from the database.
Further, in step S3, the algorithm optimizing module preliminarily selects an initial structure meeting the shot parameters from the database by manual work, and then selects an initial structure meeting the shot parameters from the manually selected initial structure by a manual intelligent system; if the artificial intelligence system does not find the initial structure which accords with the shot parameters from the database, the initial structure is supplemented into the database, and then the initial structure which accords with the shot parameters is screened again.
Further, in step S3, the algorithm optimizing module primarily selects an initial structure meeting the lens parameters from the database through an artificial intelligence algorithm, and then selects an initial structure meeting the lens parameters from the initial structures selected through the artificial intelligence algorithm through an artificial intelligence system; if the artificial intelligence system does not find the initial structure which accords with the shot parameters from the database, the initial structure is supplemented into the database, and then the initial structure which accords with the shot parameters is screened again. Preferably, the artificial intelligence algorithm is a neural network algorithm.
Further, in step S4, the interface interaction module is configured to transmit the initial structure of the shot to an artificial intelligence system, and screen out the optimization parameters that conform to the initial structure through a mechanical learning algorithm.
Further, in step S5, the optimization parameters are transmitted to the optical design software through the interface interaction module, and then the design optimization module is called to perform optical optimization on the constraint conditions in the optical design software, so as to obtain the optical design parameters.
Further, in step S6, the artificial intelligence evaluation module is an intelligent evaluation module based on deep learning, and is configured to perform data analysis and judgment on the optical design parameters fed back by the interface interaction module.
The invention has the beneficial effects that: compared with the existing optical engineer for optical design, the artificial intelligence algorithm can rely on the server to perform 24-hour uninterrupted operation, so that the optical design software can effectively improve the experience accumulation of the optical engineer on the optical design, improve the quality of optical system optimization and reduce the design time. Compared with the prior artificial intelligence in the aspect of optimizing the optical design, the method simplifies the calculation force requirement of the artificial intelligence system under the action of the algorithm optimizing module and the artificial intelligence evaluating module, can effectively reduce the running time and increase the optical design efficiency.
Drawings
FIG. 1 is a block diagram of a design method for an artificial intelligence based lens optical system according to the present invention;
FIG. 2 is a flow chart of the present invention for determining an initial face shape;
fig. 3 is a flow chart of the optimization of the optical system of the present invention.
Detailed Description
For the purpose of better explaining the present invention and to facilitate understanding, the present invention will be described in detail by way of specific embodiments with reference to the accompanying drawings.
Example 1:
referring to fig. 1 to 3, an embodiment of the present invention provides a method for designing a lens optical system through artificial intelligence. The method comprises the following steps: s1, acquiring market demands; s2, calling a screening module according to market demands to obtain lens parameters; s3, calling an algorithm optimizing module according to the lens parameters to obtain an initial structure of the lens; s4, calling an interface interaction module according to the initial structure to obtain optimization parameters of the lens; s5, calling a design optimization module according to the optimization parameters to obtain optical design parameters of the lens; s6, calling an artificial intelligence evaluation module to evaluate whether the optical design parameters in the step S5 meet the requirements of the lens parameters in the step S2; if the requirements are met, the final design of the lens is obtained; if not, returning to step S4 to re-confirm the optimized parameters; if the design is defective, the process returns to step S3 to reconfirm the original structure.
According to the invention, through the artificial intelligence system, the intelligent optimization of the optical system can be realized, the complexity of the optical design is simplified, the optimization efficiency of the optical design is effectively improved, and the efficiency is higher.
The screening module is used for analyzing the demand information to obtain a lens optical performance index, a lens structure index and a yield index. The indexes obtained by analysis become judgment bases of the algorithm optimizing module and the artificial intelligence evaluation module. When the screening module is used for screening data, the data can be analyzed and screened through a neural network algorithm, and the data can also be analyzed and screened manually by a designer. The screening module is used for collecting requirement data of market customers for shots, because the showing forms of the shots by the customers tend to be non-professional and fuzzy requirements. The specific customer requirements are as follows: clear shooting, low price, small and exquisite lens appearance and the like. The screening module analyzes the description through a neural network algorithm, generally, the neural network algorithm determines and selects a corresponding optical system index by learning a relation between the corresponding description and the optical system index, or an optical engineer performs leading distinction, and finally specific optical system indexes are determined.
The algorithm optimizing module firstly receives the judgment basis of the lens parameters (namely the optical system indexes) obtained by the screening module, and searches the initial optical design of the closest design index from the database through a mechanical learning algorithm. The algorithm optimizing module carries out the next operation through the optical system indexes output by the screening module, namely, an appropriate initial structure of the optical system is searched in the database. The database is an initial database which is formed by taking the existing optical lens as the database, the artificial intelligence system continuously learns and judges the finally determined system parameters of the optical system and the relation between the indexes of the optical system by mechanical learning by using a damped least square method, finally the most appropriate initial structure of the optical system is found by the algorithm optimizing module, and then the initial structure is output to the design optimizing module. The artificial intelligence system can supplement the database through a neural network algorithm.
The interface interaction module is used for connecting the artificial intelligence system with an interface of the optical design software, then the artificial intelligence system calls the interface interaction module, the initial structure searched in the algorithm optimizing module is transmitted to the design optimizing module, and data in the artificial intelligence evaluation module is transmitted back to the artificial intelligence system or the algorithm optimizing module, so that closed-loop optimization is realized. Specifically, the interface interaction module inputs a program instruction through MatLab, and transmits required optical system data to the optical design software codev software, and likewise, both the system data and the optical performance data of the optical system in the codev can be transmitted back to the MatLab software through the interface interaction module. The present invention may be used in, but is not limited to, artificial intelligence software or languages, MatLab, VB, etc.; optical design software: codev, zemax, etc. The artificial intelligence system adopts an instruction for controlling optical design software in artificial intelligence software through a neural network algorithm, and input data is of a numerical type. The optical design software feeds back the digitized data of the optical performance of the artificial intelligence software through the interface interaction module.
The design optimization module is used for constraining the optical design software by converting the optical system evaluation conditions into system constraints. The design optimization module only performs optical calculation and does not perform data analysis. In the design optimization module, the artificial intelligence system needs to program the optical design software according to the indexes determined in the screening module, and a mechanical learning algorithm or an optical engineer in the artificial intelligence system can select the limiting conditions in the optical software to perform optical optimization.
The artificial intelligence evaluation module is an intelligent evaluation module based on deep learning, can perform data analysis and judgment on optical performance data fed back by the interface interaction module, feeds an improvement scheme back to the design optimization module, and outputs the final design of the optical system to a user through the interface interaction module if various indexes are met. The artificial intelligence system calls the interface interaction module, extracts the performance parameters, structural parameters and sensitivity of the optical system from the design optimization module, is realized by the analysis and judgment of a neural network algorithm, and intervenes in the optical system through artificial intelligence or engineers. And finally, outputting the optical design parameters meeting the design indexes by the artificial intelligence system.
The artificial intelligence evaluation module and the design optimization module realize closed-loop connection through the interface interaction module; the design optimization module can program the optical design software according to the performance indexes obtained from the screening module. The optical design software can be programmed by an optical engineer, or optical parameters needing to be controlled are selected by artificial intelligence software, then optical programming is carried out, then the optical design software is started to calculate the optical system, and optical simulation is carried out.
The artificial intelligence system can judge the data of the optical performance provided by the interface interaction module through a neural network algorithm, judge the artificial intelligence system through comparing system indexes, output the optical system if the system indexes meet the design requirements, and re-screen the optical parameter adjusting optical design software if the optical parameters cannot be realized. And if the design limit of the current optical system appears, the design limit is fed back to the algorithm optimizing module, and the initial structure of the optical system is searched again.
The working principle of the invention is as follows: the method comprises the steps of determining initial conditions after analyzing and screening demand data, transmitting the initial conditions to an algorithm optimizing module, and then screening the demand data from a shot database by the algorithm optimizing module. And outputting the shot face meeting the specification requirement to form an initial shot face type, outputting the shot face if the shot face does not meet the requirement, further supplementing data, and then screening the shot face type again in the database by the artificial intelligence system until the initial shot face type meeting the specification requirement is found. And in the other situation, after the initial conditions are transmitted into the database, the database is subjected to partial screening, the other part is manually screened, similarly, the initial lens surface type is output according with the specification requirement, the initial lens surface type cannot be output if the requirements are not met, then data supplement is carried out, and after the supplement, the artificial intelligence system is subjected to screening again in the database until the initial lens surface type meeting the specification requirement is found. And after the initial lens surface type is determined, carrying out optimization design, carrying out parameter setting by an artificial intelligence system or a manual work, and sending an instruction to optical design software to further carry out optimization design. After the optimization is completed, the artificial intelligence system evaluates the optimization result, outputs the result if the optimization result meets the requirement, returns to the parameter setting program if the optimization result does not meet the requirement, resets the parameters for optimization until the optimization result meets the requirement and outputs the result. And if the system optimization limit is exceeded, stopping optimization, returning to the algorithm optimizing module, and re-screening the lens surface type to optimize the design until the optical system meeting the requirements is output.
Although embodiments of the present invention have been shown and described above, it should be understood that the above embodiments are illustrative and not restrictive, and that those skilled in the art may make changes, modifications, substitutions and alterations to the above embodiments without departing from the scope of the present invention.
Claims (10)
1. A design method for carrying out lens optical system by artificial intelligence is characterized by comprising the following steps: the method comprises the following steps:
s1, acquiring market demands;
s2, calling a screening module according to market demands to obtain lens parameters;
s3, calling an algorithm optimizing module according to the lens parameters to obtain an initial structure of the lens;
s4, calling an interface interaction module according to the initial structure to obtain optimization parameters of the lens;
s5, calling a design optimization module according to the optimization parameters to obtain optical design parameters of the lens;
s6, calling an artificial intelligence evaluation module to evaluate whether the optical design parameters in the step S5 meet the requirements of the lens parameters in the step S2; and if the requirements are met, obtaining the final design of the lens.
2. The design method of an artificial intelligence lens optical system according to claim 1, characterized in that: if the request is not satisfied in step S6, the process returns to step S4 to reconfirm the optimization parameters.
3. The design method of an artificial intelligence lens optical system according to claim 1, characterized in that: in step S6, if there is a defect in the design, the process returns to step S3 to reconfirm the initial structure.
4. The design method of an artificial intelligence lens optical system according to claim 1, characterized in that: in step S2, the screening module analyzes the demand information according to the market demand to obtain a lens optical performance index, a lens structure index, and a yield index; and each index obtained by analysis is used as a judgment basis for the algorithm optimizing module and the artificial intelligence evaluation module.
5. The design method of an artificial intelligence lens optical system according to claim 1, characterized in that: in step S3, the algorithm optimizing module screens out an initial structure that meets the shot parameters from a database through an artificial intelligence system; if the artificial intelligence system does not find the initial structure which accords with the lens parameters from the database, the artificial intelligence system supplements the initial structure data to the database, and then re-screens the initial structure which accords with the lens parameters from the database.
6. The design method of an artificial intelligence lens optical system according to claim 1, characterized in that: in the step S3, the algorithm optimizing module preliminarily selects an initial structure meeting the lens parameters from the database by manual work, and then selects an initial structure meeting the lens parameters from the manually selected initial structure by a manual intelligent system; if the artificial intelligence system does not find the initial structure which accords with the shot parameters from the database, the initial structure is supplemented into the database, and then the initial structure which accords with the shot parameters is screened again.
7. The design method of an artificial intelligence lens optical system according to claim 1, characterized in that: in the step S3, the algorithm optimizing module primarily selects an initial structure meeting the lens parameters from the database through an artificial intelligence algorithm, and then selects an initial structure meeting the lens parameters from the initial structures selected by the artificial intelligence algorithm through an artificial intelligence system; if the artificial intelligence system does not find the initial structure which accords with the shot parameters from the database, the initial structure is supplemented into the database, and then the initial structure which accords with the shot parameters is screened again.
8. The design method of an artificial intelligence lens optical system according to claim 1, characterized in that: in the step S4, the interface interaction module is configured to transmit the initial structure of the lens to an artificial intelligence system, and screen out an optimization parameter that conforms to the initial structure through a mechanical learning algorithm.
9. The design method of an artificial intelligence lens optical system according to claim 1, characterized in that: in step S5, the optimization parameters are transmitted to the optical design software through the interface interaction module, and then the design optimization module is called to perform optical optimization on the constraint conditions in the optical design software, so as to obtain the optical design parameters.
10. The design method of an artificial intelligence lens optical system according to claim 1, characterized in that: in step S6, the artificial intelligence evaluation module is an intelligent evaluation module based on deep learning, and is configured to perform data analysis and judgment on the optical design parameters fed back by the interface interaction module.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118151373A (en) * | 2024-03-13 | 2024-06-07 | 广州安特激光技术有限公司 | An ultra-wide-angle large working surface F-theta lens and its design method |
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| CN112285924A (en) * | 2020-11-10 | 2021-01-29 | 上海大学 | Optimal design method of fisheye lens optical system based on wave aberration theory |
| CN113163075A (en) * | 2020-01-22 | 2021-07-23 | 华为技术有限公司 | Lens, camera module and terminal equipment |
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- 2021-11-23 CN CN202111395392.2A patent/CN114063281A/en active Pending
Patent Citations (5)
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| WO2004097489A1 (en) * | 2003-04-25 | 2004-11-11 | Olympus Corporation | Method of designing optical system |
| CN107976804A (en) * | 2018-01-24 | 2018-05-01 | 郑州云海信息技术有限公司 | A kind of design method of lens optical system, device, equipment and storage medium |
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| CN113163075A (en) * | 2020-01-22 | 2021-07-23 | 华为技术有限公司 | Lens, camera module and terminal equipment |
| CN112285924A (en) * | 2020-11-10 | 2021-01-29 | 上海大学 | Optimal design method of fisheye lens optical system based on wave aberration theory |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN118151373A (en) * | 2024-03-13 | 2024-06-07 | 广州安特激光技术有限公司 | An ultra-wide-angle large working surface F-theta lens and its design method |
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