A light path optimization system and method based on data simulation

Abstract

The present invention discloses a light path optimization system and method based on data simulation, and relates to the field of data simulation technology. The light path optimization method specifically includes the following steps: obtaining light path data in actual operation to provide input for the simulation process; establishing an optical analysis model; using optical simulation software and a light path composite algorithm to simulate the light path in a computer, and adjusting the parameters of the optical system according to the comparison between the simulation results and the actual data, repeatedly iterating, and gradually optimizing the light path; setting optimization goals according to the design requirements of the system, and combining a multi-objective optimization algorithm to achieve multi-dimensional light path optimization; applying the simulated data to the actual optical system, and backing up the simulated and optimized analysis data, and optimizing and adjusting the model. The present invention improves design efficiency, and the method based on data simulation can quickly simulate the light path on a computer, greatly shortening the design cycle and improving design efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of data simulation, and in particular to an optical path optimization system and method based on data simulation. Background Art

[0002] Data simulation is a process that uses computer technology and mathematical models to simulate the generation, change and flow of data in actual systems. By building a model similar to the actual system, inputting various parameters and conditions, and then running the model to generate data similar to that which may appear in the actual system.

[0003] In the field of modern optics, with the continuous development of science and technology, the performance requirements for optical systems are getting higher and higher. The optimization of optical paths is crucial to improving the efficiency, accuracy and stability of optical systems. Traditional optical path design methods often rely on human experience and trial and error, and it is difficult to accurately predict and optimize optical path performance, including light loss, focusing accuracy and transmission efficiency; it is impossible to automatically simulate application scenarios to find the optimal optical path design solution; and there is a lack of consideration and response to external interference factors. Summary of the invention

[0004] The purpose of the present invention is to provide a light path optimization system and method based on data simulation to solve the problems raised in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solution: a light path optimization method based on data simulation, the light path optimization method specifically comprising the following steps:

[0006] Step S1, obtaining optical path data in actual operation through sensors and experimental equipment, including data such as light intensity, phase change, beam deflection and loss, and establishing an optical path analysis database to provide input for the simulation process; the optical path analysis database includes historical optical path data and simulation data;

[0007] Step S2: according to the actual needs of the optical system, an optical analysis model is established by using the historical optical path data in the optical path analysis database, wherein the optical design parameters of the optical analysis model include light source characteristics, reflection and refraction surfaces, parameters of lenses and optical elements, and external interference factors;

[0008] Step S3, using optical simulation software and optical path composite algorithm, simulating the optical path in a computer, analyzing the path, interaction and interference phenomenon of light propagation, adjusting the parameters of the optical system, including component position, angle and material properties, etc., according to the comparison between the simulation results and the actual data, inputting the adjusted parameters into the simulation program for re-simulation, iterating repeatedly, and gradually optimizing the optical path;

[0009] Step S4: according to the design requirements of the system, set the optimization goals, including reducing optical path loss, improving focusing accuracy and improving system transmission efficiency, etc.; combine the multi-objective optimization algorithm to achieve multi-dimensional optical path optimization;

[0010] Step S5, applying the simulation data to the actual optical system, backing up the simulation and optimized analysis data, inputting the simulation and optimized analysis data as simulation data into the optical path analysis database, and optimizing and adjusting the model.

[0011] In step S1, the specific steps of obtaining the optical path data in actual operation, including data such as light intensity, phase change, beam deflection and loss, through sensors and experimental equipment, and establishing an optical path analysis database to provide input for the simulation process are as follows:

[0012] Step S1-1, during the operation of the optical path, use sensors and experimental equipment to obtain the parameters of the optical path, use a photodetector to measure the light intensity, and record the power value of the light beam at different positions and time points; use an interferometer and a phase detector to capture the phase information of the light wave; use an angle sensor, a position detector and a beam tracking system to record the deflection angle of the light beam; use an optical loss meter, a power meter and a wavelength meter to measure the transmission loss of light;

[0013] Step S1-2, record the different parameters in the optical path uniformly according to the experimental time and spatial position, and express the data in matrix form. The specific time series matrix is: , where t is the timestamp, t1, t2, t3, …, t n represent the recording time respectively; I1, Φ1, θ1 and L1 represent the light intensity, phase change, beam deflection angle and light transmission loss corresponding to time t1 respectively; I n , Φ n ,θ n and L n Respectively represent the corresponding time t n The light intensity, phase change, beam deflection angle and light transmission loss of the optical system are: , where (x,y) is the coordinates of different node positions in the light path, (x,y)1, (x,y)2, (x,y)3, ..., (x,y) m Respectively represent the spatial coordinates of the data collection location; I 1 , Φ 1 ,θ 1 and L 1 I represent the light intensity, phase change, beam deflection angle and light transmission loss corresponding to time (x, y)1 respectively; m , Φ m ,θ m and L mRespectively represent the corresponding time (x, y) m light intensity, phase change, beam deflection angle and light transmission loss;

[0014] Step S1-3: Establishing a light path analysis database, and entering the light path data in actual operation as historical light path data into the light path analysis database.

[0015] In step S2, the specific steps of establishing an optical analysis model according to the actual needs of the optical system by using the historical optical path data in the optical path analysis database include:

[0016] Step S2-1: According to the actual needs of the optical system, the optical loss model is modeled based on the historical optical path data in the optical path analysis database. The expression is: ; Wherein, f1(a) represents the optical loss; a represents the optical design parameters of the system; including the geometric dimensions of the optical system (such as the width, length, bending radius, etc. of the waveguide), the optical properties of the material (such as the refractive index, absorption coefficient, etc.) and other factors that affect the propagation of light (such as temperature, electric field, magnetic field, etc., if the relevant physical effects are used to modulate the propagation of light); the smaller f1(a), the lower the optical loss and the higher the energy utilization of the system; T(a) represents the transmittance matrix in the optical system, which depends on the optical design parameter a of the system;

[0017] Step S2-2, modeling the beam focusing accuracy, the specific expression is:

[0018] ; Where f2(a) represents the beam focusing accuracy, which is determined by the size of the focal plane spot; r f (a) represents the radius of the focused spot; λ represents the wavelength of the incident light beam; w0 represents the minimum radius of the light beam; z R represents the Rayleigh length; z represents the distance from the lens to the focus; we need r f (a) As small as possible, indicating that the focusing accuracy of the beam is higher;

[0019] Step S2-3: Modeling the transmission efficiency. The specific expression is: ; Where f3(a) is the energy transfer efficiency, which represents the ratio of the optical system output light power to the incident light power; P out (a) represents the optical system output light power; P in represents the incident light power. It is hoped that the energy transfer efficiency f3(a) is as close to 1 as possible, that is, the output energy of the system is almost the same as the input energy;

[0020] In step S3, the specific steps of simulating the optical path in a computer using optical simulation software are as follows:

[0021] Step S3-1-1, define the optical system structure, input the light source model, and input the light path data into the optical simulation software through the optical analysis model established in step S2. The light path data includes the wavelength distribution, light intensity distribution, coherence and polarization state of the light source; establish an optical element geometric model, import the geometric structure and material parameters of optical elements such as lenses, reflective surfaces and refractive interfaces, and define the curvature radius, refractive index and transmittance of the lens based on the established optical analysis model; set external environmental conditions, including external interference conditions such as temperature and vibration. The simulation environment can dynamically adjust the influence of these external factors on the light path;

[0022] Step S3-1-2, define the initial conditions of the light path, the incident angle and position of the light, set the incident angle and initial position of the light according to the design requirements, and simulate multiple different incident conditions; define different light beam paths through simulation software to simulate the propagation and interaction of multiple beams of light emitted by the light source.

[0023] In step S3, the specific steps of obtaining preliminary light path optimization results by using the light path compounding algorithm and analyzing the light propagation path, interaction and interference phenomena according to the optical simulation results are as follows:

[0024] Step S3-2-1, define the light propagation path, use the ray tracing algorithm to simulate the light propagation process, after the light is emitted from the light source, it will be reflected, refracted and scattered when it encounters the reflective surface, refractive interface and lens optical element; according to the Fresnel equation, calculate the reflection and refraction of the light at the medium interface, and record the propagation path and direction change of each light;

[0025] Step S3-2-2, calculating the phase relationship and superposition effect of multiple light beams through an optical path compounding algorithm, and analyzing the bending and expansion of the light beams at the boundary; the optical path compounding algorithm includes a coherent light superposition formula and a diffraction equation formula;

[0026] The coherent light superposition formula is: ; Wherein, I_total represents the total light intensity; I_1 and I_2 represent the light intensity of the two beams respectively; ΔΦ' represents the phase difference between the two beams; the diffraction equation formula is:

[0027] ; Where I(x,y) represents the light intensity at the observation point; λ represents the wavelength of the incident light beam; z represents the distance from the lens to the focus; U(x0,y0) represents the incident light wave field passing through the aperture, (x0,y0) represents the position coordinates of the diffraction aperture; exp represents the exponential operation method with the natural constant e as the base; I0 represents the light intensity of the incident light when no diffraction occurs, which is an initial parameter related to the energy of the incident light; i represents the imaginary unit;

[0028] Step S3-2-3, combining the propagation information of light on different paths through the optical path compound algorithm, analyzing the coupling phenomenon when the light passes through different optical elements, recording the complete path of each light, and performing preliminary optical path optimization;

[0029] Step S3-2-4, establish a closed-loop feedback mechanism, and finally achieve efficient optical path design by continuously adjusting and optimizing the optical path parameters. The feedback mechanism can propose new optical path optimization suggestions based on the preliminary results and update the simulation model.

[0030] In step S3-2-3, the optical path composite algorithm combines the propagation information of light on different paths, analyzes the coupling phenomenon when the light passes through different optical elements, records the complete path of each light, and performs preliminary optical path optimization. The specific process is as follows: based on the optical path coupling analysis, find the key optical paths and areas that affect the optical path efficiency, analyze the contribution of each light to the optical path optimization, and give recommended adjustment directions; evaluate the light loss caused by reflection, scattering and absorption in the optical path through ray tracing and coupling analysis, and the software automatically calculates the total transmission efficiency of the light; for the imaging optical system, evaluate the imaging quality, analyze the aberration, optimize the lens design, and reduce the optical path distortion; adjust the lens curvature and focal length, and adjust the curvature radius and focal length of the lens according to the preliminary optical path optimization results to improve the focusing ability of the light; adjust the refractive index and surface structure of the interface material according to the reflection and refraction efficiency to reduce the optical path loss and improve the transmission efficiency; adjust the material and structure of the optical element through real-time monitoring and simulation of the impact of temperature changes on the optical path to reduce the refractive index fluctuation caused by temperature changes.

[0031] In step S4, the specific process of setting the optimization target according to the design requirements of the system and combining the multi-objective optimization algorithm to achieve multi-dimensional optical path optimization is as follows:

[0032] Step S4-1, particle initialization. In the light path optimization problem, each particle represents an optical system configuration, including light source, optical element parameters, light incident angle and position, etc. The vector representation of a particle is: ; Among them, a k is the vector representation of the particle; a kl represents the lth optical system parameter of the kth particle; the initial position of the particle is randomly generated within the definition range of different parameters, and the initial velocity is also randomly generated. A reasonable range is selected based on experience so that the initial particles can be distributed throughout the entire design space;

[0033] Step S4-2: construct a multi-objective function, and determine the particle position by calculating the multi-objective function value. The multi-objective function is specifically: ; Wherein, f1(a) represents the optical loss; a represents the optical design parameter of the system; f2(a) represents the beam focusing accuracy, which is determined by the size of the focal plane spot; f3(a) is the energy transfer efficiency, which represents the ratio of the output optical power of the optical system to the incident optical power; D(a) represents the robustness of the system;

[0034] Step S4-3: The speed and position of the particle are updated. The speed update rule is:

[0035] ;in, represents the inertia weight; c1 and c2 represent acceleration constants; r1 and r2 represent random numbers, with a value range of [0,1], to increase pseudo-randomness; P j represents the optimal position of the particle itself; the optimal position of the particle itself is the position where the minimum value is calculated in the multi-objective function of the particle; P g represents the global optimal position of the group; the global optimal position of the group is the position of the group minimum value calculated in the multi-objective function; V j (t) represents the velocity of particle j in the tth generation; V j (t+1) represents the velocity of particle j in the t+1 generation; G j (t) represents the position of particle j in the tth generation; the position update rule is:

[0036] Among them, G j (t) represents the position of particle j in the tth generation; G j (t+1) represents the position of particle j in the t+1 generation; V j (t+1) represents the velocity of particle j in the t+1th generation;

[0037] Step S4-4, through step S4-2 and step S4-3, iterate to find the Pareto frontier. If all the objective function values ​​of a particle are better than another particle, it is said to dominate the other particle; if a particle is not dominated by other particles, it will be added to the Pareto frontier; in each iteration, the Pareto frontier is updated, and the particle group is continuously pushed to move to the non-dominable area;

[0038] Step S4-5: according to the light path simulation experience, set the number of iterations and calculate the historical average convergence range, and stop the iteration when the maximum number of iterations is reached and the value of the objective function converges to a certain range; the final solution set is a set of equilibrium solutions.

[0039] In step S5, the simulation data is applied to the actual optical system, and the simulation and optimized analysis data are backed up, and the simulation and optimized analysis data are input into the optical path analysis database as simulation data. The specific steps of optimizing and adjusting the model are as follows:

[0040] Step S5-1, applying the simulation data to the actual optical system, and backing up the simulation and optimized analysis data;

[0041] Step S5-2: input the simulation and optimized analysis data into the optical path analysis database as simulation data to optimize the model.

[0042] A light path optimization system based on data simulation, the light path optimization system comprising a data acquisition module, an optical analysis model module, an optical simulation and composite algorithm module, a multi-objective optimization module and a feedback optimization and practical application module;

[0043] The data acquisition module is used to acquire optical path data in real time through sensors and experimental equipment, including light intensity, phase change, beam deflection, etc., to establish an optical path analysis database;

[0044] The optical analysis model module is used to construct an analysis model of the optical system using historical light path data and current needs, including light source characteristics, reflection, refraction and other physical phenomena;

[0045] The optical simulation and composite algorithm module is used to simulate the optical path using simulation software, optimize the optical path design in combination with the optical path composite algorithm, and analyze the light propagation path and coherence effect;

[0046] The multi-objective optimization module is used to set optimization goals according to system requirements through a multi-objective optimization algorithm, such as reducing light loss and improving focusing accuracy, and optimizing optical system parameters;

[0047] The feedback optimization and practical application module is used to apply the optimized simulation data to the actual optical system, and at the same time to feed back and update the optical path analysis database to continuously optimize the model.

[0048] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention improves design efficiency, and the method based on data simulation can quickly simulate the optical path on the computer, which greatly shortens the design cycle and improves design efficiency; optimizes the optical path performance, and through a multi-objective optimization algorithm, multiple indicators such as optical loss, focusing accuracy and transmission efficiency can be considered at the same time to achieve comprehensive optimization of the optical path performance; reduces costs, and reduces the large amount of experimental and debugging costs required by traditional trial and error methods; improves system stability, and considers external interference factors such as temperature and vibration. By adjusting the material and structure of optical components, the influence of these factors on the optical path is reduced, thereby improving the stability of the system; and continuously optimizes, and feeds back the simulation data to the optical path analysis database, continuously optimizes the model, and achieves continuous improvement of the optical path design. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A schematic diagram of the steps of a light path optimization system and method based on data simulation according to the present invention;

[0050] Figure 2 The present invention is a schematic structural diagram of an optical path optimization system based on data simulation. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] Example: Figure 1-Figure 2 As shown, the present invention provides a technical solution, a light path optimization method based on data simulation, such as Figure 1 As shown, the optical path optimization method specifically includes the following steps:

[0053] Step S1, obtaining optical path data in actual operation through sensors and experimental equipment, including data such as light intensity, phase change, beam deflection and loss, and establishing an optical path analysis database to provide input for the simulation process; the optical path analysis database includes historical optical path data and simulation data;

[0054] In step S1, the specific steps of obtaining the optical path data in actual operation, including data such as light intensity, phase change, beam deflection and loss, through sensors and experimental equipment, and establishing an optical path analysis database to provide input for the simulation process are as follows:

[0055] Step S1-1, during the operation of the optical path, use sensors and experimental equipment to obtain the parameters of the optical path, use a photodetector to measure the light intensity, and record the power value of the light beam at different positions and time points; use an interferometer and a phase detector to capture the phase information of the light wave; use an angle sensor, a position detector and a beam tracking system to record the deflection angle of the light beam; use an optical loss meter, a power meter and a wavelength meter to measure the transmission loss of light;

[0056] Step S1-2, record the different parameters in the optical path uniformly according to the experimental time and spatial position, and express the data in matrix form. The specific time series matrix is: , where t is the timestamp, t1, t2, t3, …, t n represent the recording time respectively; I1, Φ1, θ1 and L1 represent the light intensity, phase change, beam deflection angle and light transmission loss corresponding to time t1 respectively; I n , Φ n ,θ n and L n Respectively represent the corresponding time t n The light intensity, phase change, beam deflection angle and light transmission loss of the optical system are: , where (x,y) is the coordinates of different node positions in the light path, (x,y)1, (x,y)2, (x,y)3, ..., (x,y) m Respectively represent the spatial coordinates of the data collection location; I 1 , Φ 1 ,θ 1 and L 1 I represent the light intensity, phase change, beam deflection angle and light transmission loss corresponding to time (x, y)1 respectively; m , Φ m ,θ m and L m Respectively represent the corresponding time (x, y) m light intensity, phase change, beam deflection angle and light transmission loss;

[0057] Step S1-3: Establishing a light path analysis database, and entering the light path data in actual operation as historical light path data into the light path analysis database.

[0058] Data collection:

[0059] Time series: from left to right: timestamp (t), light intensity (I), phase change (Φ), deflection angle (θ), and light loss (L);

[0060] t1=0.1s, I1=5W / m², Φ1=0.01rad, θ1=0.2°, L1=0.01dB;

[0061] t2=0.2s, I2=4.8W / m², Φ2=0.015rad, θ2=0.18°, L2=0.015dB;

[0062] t3=0.3s, I3=4.5W / m², Φ3=0.02rad, θ3=0.25°, L3=0.02dB;

[0063] Spatial sequence: from left to right: position coordinates (x, y), light intensity (I), phase change (Φ), deflection angle (θ) and light loss (L);

[0064] (x,y)1=(0,0),I 1 =5W / m²,Φ 1 =0.01rad,θ 1 =0.2°, L 1 =0.01dB;

[0065] (x,y)2=(1,0),I 2 =4.8W / m², Φ 2 =0.015rad,θ 2 =0.18°, L 2 =0.015dB;

[0066] (x,y)3=(2,0),I 3 =4.5W / m², Φ 3 =0.02rad,θ 3 =0.25°, L 3 =0.02dB;

[0067] Step S2: according to the actual needs of the optical system, an optical analysis model is established by using the historical optical path data in the optical path analysis database, wherein the optical design parameters of the optical analysis model include light source characteristics, reflection and refraction surfaces, parameters of lenses and optical elements, and external interference factors;

[0068] In step S2, the specific steps of establishing an optical analysis model according to the actual needs of the optical system by using the historical optical path data in the optical path analysis database include:

[0069] Step S2-1: According to the actual needs of the optical system, the optical loss model is modeled based on the historical optical path data in the optical path analysis database. The expression is: ; Wherein, f1(a) represents the optical loss; a represents the optical design parameters of the system; including the geometric dimensions of the optical system (such as the width, length, bending radius, etc. of the waveguide), the optical properties of the material (such as the refractive index, absorption coefficient, etc.) and other factors that affect the propagation of light (such as temperature, electric field, magnetic field, etc., if the relevant physical effects are used to modulate the propagation of light); the smaller f1(a), the lower the optical loss and the higher the energy utilization of the system; T(a) represents the transmittance matrix in the optical system, which depends on the optical design parameter a of the system;

[0070] Step S2-2, modeling the beam focusing accuracy, the specific expression is:

[0071] ; Where f2(a) represents the beam focusing accuracy, which is determined by the size of the focal plane spot; r f (a) represents the radius of the focused spot; λ represents the wavelength of the incident light beam; w0 represents the minimum radius of the light beam; z R represents the Rayleigh length; z represents the distance from the lens to the focus; we need r f (a) As small as possible, indicating that the focusing accuracy of the beam is higher;

[0072] Step S2-3: Modeling the transmission efficiency. The specific expression is: ; Where f3(a) is the energy transfer efficiency, which represents the ratio of the optical system output light power to the incident light power; P out (a) represents the optical system output light power; P in represents the incident light power. It is hoped that the energy transfer efficiency f3(a) is as close to 1 as possible, that is, the output energy of the system is almost the same as the input energy;

[0073] Step S3, using optical simulation software and optical path composite algorithm, simulating the optical path in a computer, analyzing the path, interaction and interference phenomenon of light propagation, adjusting the parameters of the optical system, including component position, angle and material properties, etc., according to the comparison between the simulation results and the actual data, inputting the adjusted parameters into the simulation program for re-simulation, iterating repeatedly, and gradually optimizing the optical path;

[0074] In step S3, the specific steps of simulating the optical path in a computer using optical simulation software are as follows:

[0075] Step S3-1-1, define the optical system structure, input the light source model, and input the light path data into the optical simulation software through the optical analysis model established in step S2. The light path data includes the wavelength distribution, light intensity distribution, coherence and polarization state of the light source; establish an optical element geometric model, import the geometric structure and material parameters of optical elements such as lenses, reflective surfaces and refractive interfaces, and define the curvature radius, refractive index and transmittance of the lens based on the established optical analysis model; set external environmental conditions, including external interference conditions such as temperature and vibration. The simulation environment can dynamically adjust the influence of these external factors on the light path;

[0076] Step S3-1-2, define the initial conditions of the light path, the incident angle and position of the light, set the incident angle and initial position of the light according to the design requirements, and simulate multiple different incident conditions; define different light beam paths through simulation software to simulate the propagation and interaction of multiple beams of light emitted by the light source.

[0077] In step S3, the specific steps of obtaining preliminary light path optimization results by using the light path compounding algorithm and analyzing the light propagation path, interaction and interference phenomena according to the optical simulation results are as follows:

[0078] Step S3-2-1, define the light propagation path, use the ray tracing algorithm to simulate the light propagation process, after the light is emitted from the light source, it will be reflected, refracted and scattered when it encounters the reflective surface, refractive interface and lens optical element; according to the Fresnel equation, calculate the reflection and refraction of the light at the medium interface, and record the propagation path and direction change of each light;

[0079] Step S3-2-2, calculating the phase relationship and superposition effect of multiple light beams through an optical path compounding algorithm, and analyzing the bending and expansion of the light beams at the boundary; the optical path compounding algorithm includes a coherent light superposition formula and a diffraction equation formula;

[0080] The coherent light superposition formula is: ; Wherein, I_total represents the total light intensity; I_1 and I_2 represent the light intensity of the two beams respectively; ΔΦ' represents the phase difference between the two beams; the diffraction equation formula is:

[0081] ; Where I(x,y) represents the light intensity at the observation point; λ represents the wavelength of the incident light beam; z represents the distance from the lens to the focus; U(x0,y0) represents the incident light wave field passing through the aperture, (x0,y0) represents the position coordinates of the diffraction aperture; exp represents the exponential operation method with the natural constant e as the base; I0 represents the light intensity of the incident light when no diffraction occurs, which is an initial parameter related to the energy of the incident light; i represents the imaginary unit;

[0082] Step S3-2-3, combining the propagation information of light on different paths through the optical path compound algorithm, analyzing the coupling phenomenon when the light passes through different optical elements, recording the complete path of each light, and performing preliminary optical path optimization;

[0083] In step S3-2-3, the optical path composite algorithm combines the propagation information of light on different paths, analyzes the coupling phenomenon when the light passes through different optical elements, records the complete path of each light, and performs preliminary optical path optimization. The specific process is as follows: based on the optical path coupling analysis, find the key optical paths and areas that affect the optical path efficiency, analyze the contribution of each light to the optical path optimization, and give recommended adjustment directions; evaluate the light loss caused by reflection, scattering and absorption in the optical path through ray tracing and coupling analysis, and the software automatically calculates the total transmission efficiency of the light; for the imaging optical system, evaluate the imaging quality, analyze the aberration, optimize the lens design, and reduce the optical path distortion; adjust the lens curvature and focal length, and adjust the curvature radius and focal length of the lens according to the preliminary optical path optimization results to improve the focusing ability of the light; adjust the refractive index and surface structure of the interface material according to the reflection and refraction efficiency to reduce the optical path loss and improve the transmission efficiency; adjust the material and structure of the optical element through real-time monitoring and simulation of the impact of temperature changes on the optical path to reduce the refractive index fluctuation caused by temperature changes.

[0084] Step S3-2-4, establish a closed-loop feedback mechanism, and finally achieve efficient optical path design by continuously adjusting and optimizing the optical path parameters. The feedback mechanism can propose new optical path optimization suggestions based on the preliminary results and update the simulation model.

[0085] We use the optical simulation software Zemax to simulate the optical path and set the initial conditions:

[0086] Light incident angle: 0.2°;

[0087] Light source wavelength: 1550nm;

[0088] External disturbance conditions: set temperature fluctuation ±5°C;

[0089] The simulation results show that the loss and deflection of the optical path can be further optimized. We adjusted the radius of curvature of the lens, reduced the deflection angle, and increased the optical path transmission efficiency to 98%.

[0090] Step S4: according to the design requirements of the system, set the optimization goals, including reducing optical path loss, improving focusing accuracy and improving system transmission efficiency, etc.; combine the multi-objective optimization algorithm to achieve multi-dimensional optical path optimization;

[0091] In step S4, the specific process of setting the optimization target according to the design requirements of the system and combining the multi-objective optimization algorithm to achieve multi-dimensional optical path optimization is as follows:

[0092] Step S4-1, particle initialization. In the light path optimization problem, each particle represents an optical system configuration, including light source, optical element parameters, light incident angle and position, etc. The vector representation of a particle is: ; Among them, a k is the vector representation of the particle; a kl represents the lth optical system parameter of the kth particle; the initial position of the particle is randomly generated within the definition range of different parameters, and the initial velocity is also randomly generated. A reasonable range is selected based on experience so that the initial particles can be distributed throughout the entire design space;

[0093] Step S4-2: construct a multi-objective function, and determine the particle position by calculating the multi-objective function value. The multi-objective function is specifically: ; Wherein, f1(a) represents the optical loss; a represents the optical design parameter of the system; f2(a) represents the beam focusing accuracy, which is determined by the size of the focal plane spot; f3(a) is the energy transfer efficiency, which represents the ratio of the output optical power of the optical system to the incident optical power; D(a) represents the robustness of the system;

[0094] Step S4-3: The speed and position of the particle are updated. The speed update rule is:

[0095] ;in, represents the inertia weight; c1 and c2 represent acceleration constants; r1 and r2 represent random numbers, with a value range of [0,1], to increase pseudo-randomness; P j represents the optimal position of the particle itself; the optimal position of the particle itself is the position where the minimum value is calculated in the multi-objective function of the particle; P g represents the global optimal position of the group; the global optimal position of the group is the position of the group minimum value calculated in the multi-objective function; V j (t) represents the velocity of particle j in the tth generation; V j (t+1) represents the velocity of particle j in the t+1 generation; G j (t) represents the position of particle j in the tth generation; the position update rule is:

[0096] Among them, G j (t) represents the position of particle j in the tth generation; G j (t+1) represents the position of particle j in the t+1 generation; V j (t+1) represents the velocity of particle j in the t+1th generation;

[0097] Step S4-4, through step S4-2 and step S4-3, iterate to find the Pareto frontier. If all the objective function values ​​of a particle are better than another particle, it is said to dominate the other particle; if a particle is not dominated by other particles, it will be added to the Pareto frontier; in each iteration, the Pareto frontier is updated, and the particle group is continuously pushed to move to the non-dominable area;

[0098] Step S4-5: according to the light path simulation experience, set the number of iterations and calculate the historical average convergence range, and stop the iteration when the maximum number of iterations is reached and the value of the objective function converges to a certain range; the final solution set is a set of equilibrium solutions.

[0099] Step S5, applying the simulation data to the actual optical system, backing up the simulation and optimized analysis data, inputting the simulation and optimized analysis data as simulation data into the optical path analysis database, and optimizing and adjusting the model.

[0100] In step S5, the simulation data is applied to the actual optical system, and the simulation and optimized analysis data are backed up, and the simulation and optimized analysis data are input into the optical path analysis database as simulation data. The specific steps of optimizing and adjusting the model are as follows:

[0101] Step S5-1, applying the simulation data to the actual optical system, and backing up the simulation and optimized analysis data;

[0102] Step S5-2: input the simulation and optimized analysis data into the optical path analysis database as simulation data to optimize the model.

[0103] like Figure 2 As shown, a light path optimization system based on data simulation, the light path optimization system includes a data acquisition module, an optical analysis model module, an optical simulation and composite algorithm module, a multi-objective optimization module and a feedback optimization and practical application module;

[0104] The data acquisition module is used to acquire optical path data in real time through sensors and experimental equipment, including light intensity, phase change, light beam deflection, etc., and establish an optical path analysis database; the optical analysis model module is used to use historical optical path data and current needs to build an analysis model of the optical system, including light source characteristics, reflection and refraction and other physical phenomena; the optical simulation and composite algorithm module is used to simulate the optical path using simulation software, optimize the optical path design in combination with the optical path composite algorithm, and analyze the light propagation path and coherence effect; the multi-objective optimization module is used to set optimization goals according to system requirements through a multi-objective optimization algorithm, such as reducing light loss and improving focusing accuracy, and optimizing optical system parameters; the feedback optimization and practical application module is used to apply the optimized simulation data to the actual optical system, while feeding back and updating the optical path analysis database to continuously optimize the model.

[0105] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A light path optimization method based on data simulation, characterized in that: The optical path optimization method specifically comprises the following steps: Step S1, obtaining optical path data in actual operation through sensors and experimental equipment, including light intensity, phase change, beam deflection and loss data, and establishing an optical path analysis database to provide input for the simulation process; the optical path analysis database includes historical optical path data and simulation data; Step S2: according to the actual needs of the optical system, an optical analysis model is established by using the historical optical path data in the optical path analysis database, wherein the optical design parameters of the optical analysis model include light source characteristics, reflection and refraction surfaces, parameters of lenses and optical elements, and external interference factors; In step S2, the specific steps of establishing an optical analysis model according to the actual needs of the optical system by using the historical optical path data in the optical path analysis database include: Step S2-1: According to the actual needs of the optical system, the optical loss model is modeled based on the historical optical path data in the optical path analysis database. The expression is: ; Wherein, f1(a) represents the optical loss; a represents the optical design parameter of the system; T(a) represents the transmittance matrix in the optical system, which depends on the optical design parameter a of the system; Step S2-2, modeling the beam focusing accuracy, the specific expression is: ; Where f2(a) represents the beam focusing accuracy, which is determined by the size of the focal plane spot; r f (a) represents the radius of the focused spot; λ represents the wavelength of the incident light beam; w0 represents the minimum radius of the light beam; z R represents the Rayleigh length; z represents the distance from the lens to the focus; Step S2-3: Modeling the transmission efficiency. The specific expression is: ; Where f3(a) is the energy transfer efficiency, which represents the ratio of the optical system output light power to the incident light power; P out (a) represents the optical system output light power; P in Represents the incident light power; Step S3, using optical simulation software and optical path composite algorithm, simulating the optical path in a computer, analyzing the path, interaction and interference phenomenon of light propagation, adjusting the parameters of the optical system, including component position, angle and material properties, according to the comparison between the simulation results and the actual data, inputting the adjusted parameters into the simulation program for re-simulation, iterating repeatedly, and gradually optimizing the optical path; In step S3, the specific steps of simulating the optical path in a computer using optical simulation software are as follows: Step S3-1-1, define the optical system structure, input the light source model, and input the optical path data into the optical simulation software through the optical analysis model established in step S2. The optical path data includes the wavelength distribution, light intensity distribution, coherence and polarization state of the light source; establish an optical element geometric model, import the geometric structure and material parameters of the lens, reflective surface and refractive interface optical elements, and define the curvature radius, refractive index and transmittance of the lens based on the established optical analysis model; set external environmental conditions, including temperature and vibration, and simulate the impact of dynamic adjustment of the environment on the optical path; Step S3-1-2, define the initial conditions of the light path, the incident angle and position of the light, set the incident angle and initial position of the light according to the design requirements, and simulate multiple different incident conditions; define different light beam paths through simulation software to simulate the propagation and interaction of multiple light beams emitted by the light source; In step S3, the specific steps of obtaining preliminary light path optimization results by using the light path compounding algorithm and analyzing the light propagation path, interaction and interference phenomena according to the optical simulation results are as follows: Step S3-2-1, define the light propagation path, use the ray tracing algorithm to simulate the light propagation process, after the light is emitted from the light source, it will be reflected, refracted and scattered when it encounters the reflective surface, refractive interface and lens optical element; according to the Fresnel equation, calculate the reflection and refraction of the light at the medium interface, and record the propagation path and direction change of each light; Step S3-2-2, calculating the phase relationship and superposition effect of multiple light beams through an optical path compounding algorithm, and analyzing the bending and expansion of the light beams at the boundary; the optical path compounding algorithm includes a coherent light superposition formula and a diffraction equation formula; The coherent light superposition formula is: ; Wherein, I_total represents the total light intensity; I_1 and I_2 represent the light intensity of the two beams respectively; ΔΦ' represents the phase difference between the two beams; the diffraction equation formula is: ; Where I(x,y) represents the light intensity at the observation point; λ represents the wavelength of the incident light beam; z represents the distance from the lens to the focus; U(x0,y0) represents the incident light wave field passing through the aperture, (x0,y0) represents the position coordinates of the diffraction aperture; exp represents the exponential operation method with the natural constant e as the base; I0 represents the light intensity of the incident light when no diffraction occurs, which is an initial parameter related to the energy of the incident light; i represents the imaginary unit; Step S3-2-3, combining the propagation information of light on different paths through the optical path compound algorithm, analyzing the coupling phenomenon when the light passes through different optical elements, recording the complete path of each light, and performing preliminary optical path optimization; Step S3-2-4, establish a closed-loop feedback mechanism, and finally achieve efficient optical path design by continuously adjusting and optimizing optical path parameters. The feedback mechanism proposes new optical path optimization suggestions based on preliminary results and updates the simulation model; Step S4: according to the design requirements of the system, set the optimization goals, including reducing optical path loss, improving focusing accuracy and improving system transmission efficiency; combine the multi-objective optimization algorithm to achieve multi-dimensional optical path optimization; Step S5, applying the simulation data to the actual optical system, backing up the simulation and optimized analysis data, inputting the simulation and optimized analysis data as simulation data into the optical path analysis database, and optimizing and adjusting the model.

2. The optical path optimization method based on data simulation according to claim 1, characterized in that: In step S1, the specific steps of obtaining the optical path data in actual operation, including light intensity, phase change, beam deflection and loss data, through sensors and experimental equipment, and establishing an optical path analysis database to provide input for the simulation process are as follows: Step S1-1, during the operation of the optical path, use sensors and experimental equipment to obtain the parameters of the optical path, use a photodetector to measure the light intensity, and record the power value of the light beam at different positions and time points; use an interferometer and a phase detector to capture the phase information of the light wave; use an angle sensor, a position detector and a beam tracking system to record the deflection angle of the light beam; use an optical loss meter, a power meter and a wavelength meter to measure the transmission loss of light; Step S1-2, record the different parameters in the optical path uniformly according to the experimental time and spatial position, and express the data in matrix form. The specific time series matrix is: , where t is the timestamp, t1, t2, t3, …, t n represent the recording time respectively; I1, Φ1, θ1 and L1 represent the light intensity, phase change, beam deflection angle and light transmission loss corresponding to time t1 respectively; I n , Φ n ,θ n and L n Respectively represent the corresponding time t n The light intensity, phase change, beam deflection angle and light transmission loss of the optical system are: , where (x,y) is the coordinates of different node positions in the light path, (x,y)1, (x,y)2, (x,y)3, ..., (x,y) m Respectively represent the spatial coordinates of the data collection location; I 1 , Φ 1 ,θ 1 and L 1 I represent the light intensity, phase change, beam deflection angle and light transmission loss corresponding to time (x, y)1 respectively; m , Φ m ,θ m and L m Respectively represent the corresponding time (x, y) m light intensity, phase change, beam deflection angle and light transmission loss; Step S1-3: Establishing a light path analysis database, and entering the light path data in actual operation as historical light path data into the light path analysis database.

3. The optical path optimization method based on data simulation according to claim 2, characterized in that: In step S3-2-3, the optical path composite algorithm combines the propagation information of light on different paths, analyzes the coupling phenomenon when the light passes through different optical elements, records the complete path of each light, and performs preliminary optical path optimization. The specific process is as follows: based on the optical path coupling analysis, find the key optical paths and areas that affect the optical path efficiency, analyze the contribution of each light to the optical path optimization, and give recommended adjustment directions; evaluate the light loss caused by reflection, scattering and absorption in the optical path through ray tracing and coupling analysis, and the software automatically calculates the total transmission efficiency of the light; for the imaging optical system, evaluate the imaging quality, analyze the aberration, optimize the lens design, and reduce the optical path distortion; adjust the lens curvature and focal length, and adjust the curvature radius and focal length of the lens according to the preliminary optical path optimization results to improve the focusing ability of the light; adjust the refractive index and surface structure of the interface material according to the reflection and refraction efficiency to reduce the optical path loss and improve the transmission efficiency; adjust the material and structure of the optical element through real-time monitoring and simulation of the impact of temperature changes on the optical path to reduce the refractive index fluctuation caused by temperature changes.

4. The optical path optimization method based on data simulation according to claim 3, characterized in that: In step S4, the specific process of setting the optimization target according to the design requirements of the system and combining the multi-objective optimization algorithm to achieve multi-dimensional optical path optimization is as follows: Step S4-1, particle initialization. In the light path optimization problem, each particle represents an optical system configuration, including light source, optical element parameters, light incident angle and position. The vector representation of a particle is: ; Among them, a k is the vector representation of the particle; a kl represents the lth optical system parameter of the kth particle; the initial position of the particle is randomly generated within the definition range of different parameters, and the initial velocity is also randomly generated. A reasonable range is selected based on experience so that the initial particles are distributed throughout the entire design space; Step S4-2: construct a multi-objective function, and determine the particle position by calculating the multi-objective function value. The multi-objective function is specifically: ; Wherein, f1(a) represents the optical loss; a represents the optical design parameter of the system; f2(a) represents the beam focusing accuracy, which is determined by the size of the focal plane spot; f3(a) is the energy transfer efficiency, which represents the ratio of the output optical power of the optical system to the incident optical power; D(a) represents the robustness of the system; Step S4-3: The speed and position of the particle are updated. The speed update rule is: ;in, represents the inertia weight; c1 and c2 represent acceleration constants; r1 and r2 represent random numbers, with a value range of [0,1], to increase pseudo-randomness; P j represents the optimal position of the particle itself; P g represents the global optimal position of the group; V j (t) represents the velocity of particle j in the tth generation; V j (t+1) represents the velocity of particle j in the t+1 generation; G j (t) represents the position of particle j in the tth generation; the position update rule is: Among them, G j (t) represents the position of particle j in the tth generation; G j (t+1) represents the position of particle j in the t+1 generation; V j (t+1) represents the velocity of particle j in the t+1th generation; Step S4-4, through step S4-2 and step S4-3, iterate to find the Pareto frontier. If all the objective function values ​​of a particle are better than another particle, it is said to dominate the other particle; if a particle is not dominated by other particles, it will be added to the Pareto frontier; in each iteration, the Pareto frontier is updated, and the particle group is continuously pushed to move to the non-dominable area; Step S4-5: according to the light path simulation experience, set the number of iterations and calculate the historical average convergence range, and stop the iteration when the maximum number of iterations is reached and the value of the objective function converges to a certain range; the final solution set is a set of equilibrium solutions.

5. The optical path optimization method based on data simulation according to claim 1, characterized in that: In step S5, the simulation data is applied to the actual optical system, and the simulation and optimized analysis data are backed up, and the simulation and optimized analysis data are input into the optical path analysis database as simulation data. The specific steps of optimizing and adjusting the model are as follows: Step S5-1, applying the simulation data to the actual optical system, and backing up the simulation and optimized analysis data; Step S5-2: input the simulation and optimized analysis data into the optical path analysis database as simulation data to optimize the model.

6. A light path optimization system based on data simulation, using a light path optimization method based on data simulation as claimed in any one of claims 1 to 5, characterized in that: The optical path optimization system includes a data acquisition module, an optical analysis model module, an optical simulation and composite algorithm module, a multi-objective optimization module, and a feedback optimization and practical application module; The data acquisition module is used to obtain light path data in real time through sensors and experimental equipment, including light intensity, phase change, and beam deflection, and to establish a light path analysis database; The optical analysis model module is used to construct an analysis model of the optical system using historical light path data and current requirements, including light source characteristics, reflection and refraction physical phenomena; The optical simulation and composite algorithm module is used to simulate the optical path using simulation software, optimize the optical path design in combination with the optical path composite algorithm, and analyze the light propagation path and coherence effect; The multi-objective optimization module is used to set optimization targets according to system requirements through a multi-objective optimization algorithm, reduce light loss and improve focusing accuracy, and optimize optical system parameters; The feedback optimization and practical application module is used to apply the optimized simulation data to the actual optical system, and at the same time to feed back and update the optical path analysis database to continuously optimize the model.

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