Sunlight spectrum real-time reproduction system and cabin sunlight simulation lighting source

Abstract

The invention relates to a sunlight spectrum real-time reproduction system and a cabin sunlight simulation lighting source. The system comprises an acquisition module, a processing module and an output module which are cascaded in sequence, the acquisition module is used for acquiring real-time sunlight spectrum information of an external environment of a cabin, and the real-time sunlight spectrum information comprises sunlight spectrum power distribution data; the processing module is used for generating test spectrum information, calculating the optimal luminous flux ratio of the plurality of illuminating lamps by taking the minimum difference value between the test spectrum information and the real-time sunlight spectrum information as a target, and performing spectrum allocation calculation based on the optimal luminous flux ratio; and the output module is used for outputting each allocation result. The light source comprises a plurality of illuminating lamps and a sunlight spectrum real-time reproduction system. According to the invention, the sunlight atlas can be reproduced in real time, so that the illumination effect of the illumination lamp is close to that of real-time sunlight, the illumination lamp is more suitable for a ship navigation illumination environment, and the daily life light environment of sailors can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of ship lighting, and in particular to a daylight spectrum real-time reproduction system and a cabin daylight simulation lighting source. Background Art

[0002] During the voyage of a ship, the crew members are mostly in the enclosed environment of the cabin, and the cabin lighting source provides illumination for the cabin environment. The current cabin lighting source design mostly considers energy saving, brightness, life span and other aspects. However, in the special scenario of ship navigation, the crew members may not be exposed to sunlight for a long time, which is not conducive to the physical and mental health of the crew members.

[0003] In the prior art, there are lighting sources that can simply simulate sunlight. For example, CN219198931U discloses a solar simulation lighting system. First, the first light source module in the central area of ​​the lighting system emits a first white light with a high color temperature, and the outer area emits a second white light with a low color temperature to simulate the two luminous surfaces of the center and edge of the sun with different color temperatures. The first light source module and the second light source module can switch between different brightnesses respectively, and the brightness of the first white light and the second white light are controlled to present two different brightness changes of light and dark to simulate the dynamic flickering effect when the sun is shining. The lighting system simulates the color temperature distribution and flickering effect of sunlight through light source simulation modules with different color temperatures. However, in actual use, the lighting system fails to simulate the lighting effect of the sun at different time periods. The simulation effect is fixed and single, and it is impossible to truly simulate sunlight, which needs to be improved. Summary of the invention

[0004] In order to solve the problems existing in the above-mentioned prior art, the purpose of this application is to provide a daylight spectrum real-time reproduction system and a cabin daylight simulation lighting source. This application can perform spectrum adjustment calculation based on real-time daylight spectrum information with the goal of approaching real-time daylight spectrum information, and can achieve real-time reproduction of daylight spectrum, so that the lighting effect of the lighting lamp is close to real-time sunlight, which is more suitable for ship navigation lighting environment and helps to improve the daily life light environment of the crew.

[0005] The daylight spectrum real-time reproduction system described in the present application is applied to a cabin daylight simulation lighting source having a plurality of lighting lamps. The daylight spectrum real-time reproduction system comprises a collection module, a processing module and an output module cascaded in sequence;

[0006] The acquisition module is used to collect real-time sunlight spectrum information of the environment outside the cabin, and the real-time sunlight spectrum information includes sunlight spectrum power distribution data;

[0007] The processing module is used to generate test spectral information, calculate the optimal luminous flux ratio of the several lighting lamps with the goal of minimizing the difference between the test spectral information and the real-time sunlight spectral information, and perform spectral blending calculation based on the optimal luminous flux ratio;

[0008] An output module, which is used to output each blending result.

[0009] Preferably, the processing module includes a ratio calculation unit, a blending calculation unit and an amplification unit connected in series in sequence;

[0010] The ratio calculation unit calculates the optimal luminous flux ratio of the several lighting lamps through an optimization algorithm;

[0011] The blending calculation unit is used to perform spectral blending calculation based on the optimal luminous flux ratio to obtain a blending result;

[0012] The amplification unit is used to proportionally amplify the obtained blending result.

[0013] Preferably, the optimization algorithm is a particle swarm algorithm. The ratio calculation unit calculates the optimal luminous flux ratio of the several lighting lamps through the particle swarm algorithm, including the following steps:

[0014] S01. Establish the objective function Dis_sum(w) of the particle swarm algorithm:

[0015]

[0016] Among them, λ represents the peak wavelength of the lighting lamp; np represents the number of points that can be obtained by continuously sampling at a fixed interval within the wavelength range of the lighting lamp; Test(λ)_n represents the test spectral power value of the nth point, Sun(λ)_n represents the sunlight spectral power value of the nth point, n ∈ [1, np]; w represents the luminous flux ratio vector, w = [w1, w2... wq] T , q represents the number of lighting lamps;

[0017] S02. Initialize the parameters of the particle swarm algorithm: Initialize the population size Size_pop, the space dimension Dim, the maximum number of iterations Ger, the position parameter range [P min , P max , the speed parameter range [V min , V max , the inertia weight C 1 , the self-learning factor C 2 and the group learning factor C 3 ;

[0018] S03. Set the color temperature CCT and the color rendering index CRI as the constraint conditions of the particle swarm algorithm;

[0019] S04. When the function value that satisfies the objective function Dis_sum(w) is calculated to be the smallest by the particle swarm algorithm, the luminous flux ratio vector of each lighting lamp is the optimal luminous flux ratio.

[0020] Preferably, in step S01, the peak wavelength λ of the lighting lamp ∈ [380nm, 780nm], the fixed interval is 1nm, and np = 401;

[0021] In step S02, the initialized population size Size_pop = 500, the space dimension Dim is equal to the number of lighting lamps, the maximum number of iterations Ger = 500, the position parameter range [P min , P max = [0, 1], the speed parameter range [V min , V max = [-1, 1], the inertia weight C 1 = 0.8, the self-learning factor C 2 = 0.5, the swarm learning factor C 3 = 0.5.

[0022] Preferably, the calculation formula of the color temperature CCT is:

[0023] CCT = 669(M) 4 - 779(M) 3 + 3360(M) 2 - 7047M + 5652;

[0024]

[0025] Among them, x and y are the color coordinates corresponding to the test spectral information, and the constraint condition of the color temperature CCT is:

[0026] |CCT_Sun - CCT| < 1k;

[0027] Among them, CCT_Sun represents the daylight color temperature;

[0028] The constraint condition of the color rendering index CRI is:

[0029] CRI > 80.

[0030] Preferably, the spectral blending calculation unit performs spectral blending calculation according to the following steps:

[0031] Use the Gaussian model to calculate the spectral power T of a single lighting lamp m :

[0032]

[0033] Among them, Tm (λ) represents the spectral power of the m-th lighting lamp, where m represents the number of the lighting lamp, and λ m represents the peak wavelength of the m-th lighting lamp, and σ represents the standard deviation related to the full width at half maximum;

[0034] The spectral power of the lighting lamp group T(λ) = [T1(λ), T2(λ)... Tq(λ)];

[0035] The blending result is expressed as:

[0036] Test‘(λ) = T(λ) * w,

[0037] where Test‘(λ) represents the optimized test spectral information.

[0038] Preferably, the optimization algorithm is the gradient descent method or the genetic algorithm.

[0039] A daylight simulation lighting source for a ship's cabin according to the present application includes a plurality of lighting lamps and the daylight spectrum real-time reproduction system as described above. The daylight spectrum real-time reproduction system is signal-connected to the lighting lamps and is used to control the lighting lamps to perform lighting actions according to the blending result.

[0040] Preferably, the number of the lighting lamps is nine.

[0041] Preferably, the peak wavelengths of the nine lighting lamps are 420 nm, 450 nm, 480 nm, 520 nm, 560 nm, 600 nm, 640 nm, 680 nm, and 750 nm in sequence, and the full widths at half maximum are 40 nm, 45 nm, 50 nm, 100 nm, 105 nm, 110 nm, 80 nm, 75 nm, and 90 nm in sequence.

[0042] The advantages of the daylight spectrum real-time reproduction system and the daylight simulation lighting source for a ship's cabin according to the present application are that by obtaining real-time daylight spectrum information and generating test spectral information, the optimal luminous flux ratio of the lighting lamps is calculated with the goal of minimizing the difference between the two, and spectral blending calculation is performed. Thus, spectral blending calculation based on real-time daylight spectrum information can be realized, and applying the blending result to the control of the lighting lamps can make the lighting light of the lighting lamps close to sunlight, so as to achieve the daylight simulation lighting effect, which is more suitable for the ship navigation lighting environment and helps to improve the daily light environment of the crew. Description of the Drawings

[0043] Figure 1 is a structural block diagram of a daylight spectrum real-time reproduction system according to the present application;

[0044] Figure 2 is a flowchart of the execution steps of a daylight spectrum real-time reproduction system according to the present application;

[0045] Figure 3 is the flowchart of the processing steps of the processing module described in this application;

[0046] Figure 4 is the comparison chart between the optimized test spectral information and the solar spectrum.

[0047] Explanation of reference numerals: 1 - acquisition module, 2 - processing module, 21 - ratio calculation unit, 22 - formulation calculation unit, 23 - amplification unit, 3 - output module. Detailed implementation manners

[0048] As Figures 1-3 shown, a real-time daylight spectrum reproduction system described in this application is applied to a daylight simulation lighting source in a cabin with several lighting lamps. The real-time daylight spectrum reproduction system includes an acquisition module 1, a processing module 2, and an output module 3 that are cascaded in sequence.

[0049] The acquisition module 1 is used to acquire the real-time daylight spectrum information of the external environment of the cabin. The real-time daylight spectrum information includes daylight spectrum power distribution data. Specifically, the acquisition module 1 is a spectrometer set in the open-air environment outside the cabin. The spectrometer receives sunlight and performs spectral analysis on the sunlight to obtain the real-time daylight spectrum information.

[0050] The processing module 2 is used to generate test spectral information. With the goal of minimizing the difference between the test spectral information and the real-time daylight spectrum information, calculate the optimal luminous flux ratio of the several lighting lamps, and perform spectral formulation calculation based on the optimal luminous flux ratio. Specifically, the processing module 2 is an MCU with computing power. The test spectral information collected by the acquisition module 1 is input into the processing module 2. The processing module 2 generates test spectral information. With the goal of minimizing the difference between the test spectral information and the real-time daylight spectrum information, that is, the test spectral information is closest to the real-time daylight spectrum information, calculate the optimal luminous flux ratio of the several lighting lamps, and perform spectral formulation calculation based on the optimal luminous flux ratio.

[0051] In this embodiment, by obtaining the real-time daylight spectrum information and generating the test spectral information, calculating the optimal luminous flux ratio of the lighting lamps and performing spectral formulation calculation with the goal of minimizing the difference between the two, it is possible to realize spectral formulation calculation based on the real-time daylight spectrum information. Applying the formulation result to the control of the lighting lamps can make the lighting light of the lighting lamps close to sunlight, so as to achieve the daylight simulation lighting effect, which is more suitable for the ship navigation lighting environment and helps to improve the daily lighting environment of the crew.

[0052] Furthermore, in this embodiment, the processing module 2 includes a ratio calculation unit 21, a formulation calculation unit 22, and an amplification unit 23 that are cascaded in sequence;

[0053] The ratio calculation unit 21 calculates the optimal luminous flux ratio of the several lighting lamps through an optimization algorithm;

[0054] Specifically, the optimization algorithm can be a particle swarm algorithm, a gradient descent method, or a genetic algorithm.

[0055] Taking the particle swarm algorithm as an example, the optimization algorithm includes the following steps:

[0056] S01. Establish the objective function Dis_sum(w) of the particle swarm algorithm:

[0057]

[0058] Among them, λ represents the peak wavelength of the lighting lamp; np represents the number of points that can be obtained by continuously taking points at a fixed interval within the wavelength range of the lighting lamp; Test(λ)_n represents the test spectral power value of the nth point, Sun(λ)_n represents the daylight spectral power value of the nth point, n ∈ [1, np]; w represents the luminous flux ratio vector, w = [w1, w2... wq] T , and q represents the number of lighting lamps.

[0059] In a specific embodiment, when the peak wavelength λ of the lighting lamp ∈ [380nm, 780nm], points are taken at a fixed interval of 1nm, and 401 points can be obtained, that is, np = 401, n ∈ [1, 401].

[0060] S02. Initialize the parameters of the particle swarm algorithm: Initialize the population size Size_pop, the space dimension Dim, the maximum number of iterations Ger, the position parameter range [P min , P max , V min , V max , the inertia weight C 1 , the self-learning factor C 2 and the group learning factor C 3 ;

[0061] In a specific embodiment, the initialized population size Size_pop = 500, the space dimension Dim is equal to the number of lighting lamps. For example, when the number of lighting lamps is nine, the space dimension Dim = 9.

[0062] The maximum number of iterations Ger = 500, the position parameter range [P min , P max , V min , V max = [-1, 1], the inertia weight C 1 = 0.8, the self-learning factor C 2 = 0.5, the group learning factor C3 = 0.5.

[0063] S03. Set the color temperature CCT and the color rendering index CRI as the constraint conditions of the particle swarm algorithm;

[0064] The calculation formula of the color temperature CCT is:

[0065] CCT = 669(M) 4 - 779(M) 3 + 3360(M) 2 - 7047M + 5652;

[0066]

[0067] where x, y are the color coordinates corresponding to the test spectral information, and the constraint condition of the color temperature CCT is:

[0068] |CCT_Sun - CCT| < 1k;

[0069] where CCT_Sun represents the sunlight color temperature. The sunlight color temperature can obtain the color coordinates of sunlight through the previously collected sunlight spectral information, and calculate the sunlight color temperature through the color coordinates of sunlight.

[0070] The constraint condition of the color rendering index CRI is:

[0071] CRI > 80.

[0072] S04. When the function value of the objective function Dis_sum(w) is calculated to be the smallest through the particle swarm algorithm, the luminous flux ratio vector of each lighting lamp is the optimal luminous flux ratio.

[0073] The deployment calculation unit 22 is used to perform spectral deployment calculation based on the optimal luminous flux ratio to obtain a deployment result;

[0074] Specifically, the deployment calculation unit 22 performs spectral deployment calculation according to the following steps:

[0075] Use the Gaussian model to calculate the spectral power T of a single lighting lamp m :

[0076]

[0077] where T m (λ) represents the spectral power of the m-th lighting lamp, m represents the number of the lighting lamp, m ∈ [1, Dim], λ m represents the peak wavelength of the m-th lighting lamp, σ represents the standard deviation related to the full width at half maximum, and the full width at half maximum is expressed as Δλ, then there is

[0078] The spectral power T(λ) of the lighting lamp group = [T1(λ), T2(λ)... Tq(λ)];

[0079] The blending result is expressed as:

[0080] Test‘(λ) = T(λ) * w,

[0081] where Test‘(λ) represents the optimized test spectral information, and the blending result Test‘(λ) is the product of the spectral power T(λ) of the lighting lamp and the luminous flux ratio vector w = [w1, w2... wq] T Specifically, the multiplication is Test‘(λ) = T1(λ) * w1 + T2(λ) * w2 +... Tq(λ) * wq. Thus, the optimized test spectral information can be calculated, and this optimized test spectral information is the blending result used to control the lighting lamp to perform corresponding lighting actions.

[0082] The amplification unit 23 is used to amplify the obtained blending result in equal proportion to form an output that can control the spectral information of the lighting lamp.

[0083] The output module 3 is used to output the amplified blending result to the lighting lamp, and control the lighting lamp to perform lighting actions according to the blending result.

[0084] In other alternative embodiments, the optimization algorithm can also adopt the gradient descent method or the genetic algorithm. In the algorithm, the goal is to minimize the difference between the test spectral information and the real-time sunlight spectral information, and add the color temperature CCT satisfying |CCT_Sun - CCT| < 1k and the color rendering index CRI > 80 as constraint conditions to optimize and obtain the optimal luminous flux ratio, and use the Gaussian model to calculate the spectral power T of a single lighting lamp m to obtain the spectral power T(λ) of the lighting lamp group, and combine the obtained optimal luminous flux ratio and the spectral power T(λ) to obtain the blending result. The particle swarm algorithm, the gradient descent method, and the genetic algorithm are common optimization algorithms. After the specific calculation process of the particle swarm algorithm is disclosed above, those skilled in the art can refer to the above description for understanding when calculating the blending result using the gradient descent method and the genetic algorithm, and details will not be repeated here.

[0085] This embodiment also provides a cabin daylight simulation lighting source, including several lighting lamps and the daylight spectrum real-time reproduction system as described above. The daylight spectrum real-time reproduction system is signal-connected to the lighting lamps and is used to control each lighting lamp to perform lighting actions according to the aforementioned blending result.

[0086] Further, in this embodiment, the number of the lighting lamps is nine, and the peak wavelengths of the nine lighting lamps are 420 nm, 450 nm, 480 nm, 520 nm, 560 nm, 600 nm, 640 nm, 680 nm and 750 nm in sequence, and the full width at half maximum are 40 nm, 45 nm, 50 nm, 100 nm, 105 nm, 110 nm, 80 nm, 75 nm and 90 nm in sequence.

[0087] The cabin daylight simulation lighting source of this embodiment applies the above daylight spectrum real-time reproduction system and has the effect of being able to simulate daylight in real time.

[0088] Combined with the above content, the reproduction situations of the solar spectra at different time periods are respectively illustrated by examples as follows:

[0089] The peak wavelengths of the nine lighting lamps of the cabin lighting source are 420 nm, 450 nm, 480 nm, 520 nm, 560 nm, 600 nm, 640 nm, 680 nm and 750 nm in sequence, and the full width at half maximum are 40 nm, 45 nm, 50 nm, 100 nm, 105 nm, 110 nm, 80 nm, 75 nm and 90 nm in sequence.

[0090] Scenario 1:

[0091] Weather: Sunny.

[0092] Time period: 6:26 at sunrise.

[0093] Use a spectral color illuminometer to measure the daylight spectrum information at different incident angles, such as 0°, 30°, 60° and 90°, and take the average value as the real-time daylight spectrum information, and obtain the daylight color temperature and color coordinates.

[0094] Through the above algorithm for optimization calculation, the obtained test spectral luminous flux ratio vector w = [0.470, 0.288, 0.494, 0.711, 0.365, 0.362, 0.281, 0.427, 0.719] T , and the objective function value Dis_sum(w) is 31.8, the color temperature CCT is 8899 K, and the color rendering index CRI is 93.

[0095] The comparison diagram of the spectral power distribution between the optimized test spectrum and the solar spectrum is as shown in Figure 4 part a in.

[0096] Scenario 2:

[0097] Weather: Sunny.

[0098] Time period: 9:24 in the morning.

[0099] Measure the daylight spectral information at different incident angles, such as 0°, 30°, 60° and 90°, using a spectral color illuminometer, take the average value as the real-time daylight spectral information, and calculate the daylight color temperature and color coordinates.

[0100] Through the above algorithm for optimization calculation, obtain the test spectral luminous flux ratio vector w = [0.415, 0.317, 0.331, 0.852, 0.561, 0.764, 0.399, 0.541, 0.972] T , the objective function value Dis_sum(w) is 25.6, the color temperature CCT is 5414K, and the color rendering index CRI is 98.

[0101] The comparison diagram of the spectral power distribution between the optimized test spectrum and the solar spectrum is as Figure 4 shown in part b of

[0102] Scenario three:

[0103] Weather: Sunny.

[0104] Time period: 12:16 noon.

[0105] Measure the daylight spectral information at different incident angles, such as 0°, 30°, 60° and 90°, using a spectral color illuminometer, take the average value as the real-time daylight spectral information, and calculate the daylight color temperature and color coordinates.

[0106] Through the above algorithm for optimization calculation, obtain the test spectral luminous flux ratio vector w = [0.342, 0.368, 0.374, 0.558, 0.831, 0.564, 0.401, 0.576, 1] T , the objective function value Dis_sum(w) is 26.9, the color temperature CCT is 5410K, and the color rendering index CRI is 98.

[0107] The comparison diagram of the spectral power distribution between the optimized test spectrum and the solar spectrum is as Figure 4 shown in part c of

[0108] Scenario four:

[0109] Weather: Sunny.

[0110] Time period: 15:08 at sunrise.

[0111] Measure the daylight spectral information at different incident angles, such as 0°, 30°, 60° and 90°, using a spectral color illuminometer, take the average value as the real-time daylight spectral information, and calculate the daylight color temperature and color coordinates.

[0112] Through the above algorithm for optimization calculation, the test spectral luminous flux ratio vector w = [0.400, 0.352, 0.342, 0.674, 0.563, 0.519, 0.358, 0.432, 0.777] is obtained. T , the objective function value Dis_sum(w) is 26.6, the color temperature CCT is 6241K, and the color rendering index CRI is 97.

[0113] The comparison diagram of the spectral power distribution between the optimized test spectrum and the solar spectrum is as Figure 4 shown in part d of the figure.

[0114] Scenario Five:

[0115] Weather: Sunny.

[0116] Time period: Sunrise at 18:08.

[0117] Use a spectral color illuminometer to measure the daylight spectral information at different incident angles, such as 0°, 30°, 60°, and 90°, and take the average value as the real-time daylight spectral information, and calculate the daylight color temperature and color coordinates.

[0118] Through the above algorithm for optimization calculation, the test spectral luminous flux ratio vector w = [0.394, 0.382, 0.394, 0.685, 0.346, 0.419, 0.297, 0.654, 0.721] is obtained. T , the objective function value Dis_sum(w) is 39.6, the color temperature CCT is 7811K, and the color rendering index CRI is 87.

[0119] The comparison diagram of the spectral power distribution between the optimized test spectrum and the solar spectrum is as Figure 4 shown in part e of the figure.

[0120] As can be seen from the above, at different time periods, the daylight reproduction achieved by the daylight spectral real-time reproduction system of this embodiment is close to the relative spectral power distribution data of real sunlight, indicating that the daylight spectral real-time reproduction system of this embodiment has a good daylight real-time reproduction effect.

[0121] In the description of this application, it should be understood that the orientation or positional relationship indicated by orientation words such as "front, back, up, down, left, right", "horizontal, vertical, level" and "top, bottom" is usually based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing this application and simplifying the description. Without contrary explanation, these orientation words do not indicate and imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, so it cannot be understood as a limitation on the protection scope of this application.

[0122] For those skilled in the art, various corresponding changes and deformations can be made according to the technical solutions and concepts described above, and all such changes and deformations should fall within the protection scope of the claims of this application.

Claims

1. A daylight spectrum real-time reproduction system, applied to a cabin daylight simulation lighting source having a plurality of lighting lamps, characterized in that: The sunlight spectrum real-time reproduction system comprises a collection module, a processing module and an output module which are cascaded in sequence; The acquisition module is used to collect real-time sunlight spectrum information of the environment outside the cabin, and the real-time sunlight spectrum information includes sunlight spectrum power distribution data; The processing module is used to generate test spectrum information, calculate the optimal luminous flux ratio of the plurality of lighting lamps with the goal of minimizing the difference between the test spectrum information and the real-time daylight spectrum information, and perform spectrum adjustment calculation based on the optimal luminous flux ratio; The output module is used to output various deployment results.

2. The sunlight spectrum real-time reproduction system according to claim 1, characterized in that: The processing module includes a ratio calculation unit, a deployment calculation unit and an amplification unit which are cascaded in sequence; The ratio calculation unit calculates the optimal luminous flux ratio of the plurality of lighting lamps through an optimization algorithm; The adjustment calculation unit is used to perform spectrum adjustment calculation based on the optimal light flux ratio to obtain an adjustment result; The amplification unit is used to amplify the obtained blending result in equal proportion.

3. The sunlight spectrum real-time reproduction system according to claim 2, characterized in that: The optimization algorithm is a particle swarm algorithm, and the ratio calculation unit calculates the optimal luminous flux ratio of the plurality of lighting lamps by using the particle swarm algorithm, including the following steps: S01, establish the objective function Dis_sum(w) of the particle swarm algorithm: Where λ represents the peak wavelength of the lighting lamp; np represents the number of points that can be obtained by continuously taking points at fixed intervals within the wavelength range of the lighting lamp; Test(λ)_n represents the test spectral power value of the nth point, Sun(λ)_n represents the daylight spectral power value of the nth point, n∈[1,np]; w represents the luminous flux ratio vector, w=[w1,w2...wq] T , q represents the number of lighting lamps; S02, initialize the particle swarm algorithm parameters: initialize the population size Size_pop, space dimension Dim, maximum number of iterations Ger, position parameter range [P min ,P max ]、Speed ​​parameter range [V min ,V max ], inertia weight C1, self-learning factor C2 and group learning factor C3; S03, setting color temperature CCT and color rendering index CRI as constraints of the particle swarm algorithm; S04. When the function value that satisfies the objective function Dis_sum(w) is minimized by using the particle swarm algorithm, the luminous flux ratio vector of each lighting lamp is the optimal luminous flux ratio.

4. The sunlight spectrum real-time reproduction system according to claim 3, characterized in that: In step S01, the peak wavelength λ∈[380nm, 780nm] of the lighting lamp, the fixed interval is 1nm, and np=401; In step S02, the population size Size_pop is initialized to 500, the space dimension Dim is equal to the number of lighting lamps, the maximum number of iterations Ger is 500, and the position parameter range [P min ,P max ]=[0,1], speed parameter range [V min ,V max ]=[-1,1], inertia weight C1=0.8, self-learning factor C2=0.5, group learning factor C3=0.

5.

5. The sunlight spectrum real-time reproduction system according to claim 3, characterized in that: In step S03, the calculation formula of the color temperature CCT is: CCT=669(M) 4 -779(M) 3 +3360(M) 2 -7047M+5652; Wherein, x and y are the color coordinates corresponding to the test spectrum information, and the constraint condition of the color temperature CCT is: |CCT_Sun-CCT|<1k; Among them, CCT_Sun represents the color temperature of daylight; The constraints of the color rendering index CRI are: CRI>80.

6. The sunlight spectrum real-time reproduction system according to claim 3, 4 or 5, characterized in that: The blending calculation unit performs spectrum blending calculation according to the following steps: The Gaussian model is used to calculate the spectral power T of a single lighting lamp. m : Among them, T m (λ) represents the spectral power of the mth lighting fixture, m represents the number of the lighting fixture, and λ m represents the peak wavelength of the mth illuminator, σ represents the standard deviation associated with the full width at half maximum; The spectral power of the lighting lamp group T(λ)=[T1(λ), ​​T2(λ)...Tq(λ)]; The blending result is expressed as: Test'(λ)=T(λ)*w, Wherein, Test'(λ) represents the optimized test spectrum information.

7. The sunlight spectrum real-time reproduction system according to claim 2, characterized in that: The optimization algorithm is a gradient descent method or a genetic algorithm.

8. A cabin daylight simulation lighting source, characterized in that: It comprises a plurality of lighting lamps and a daylight spectrum real-time reproduction system as claimed in any one of claims 1 to 7, wherein the daylight spectrum real-time reproduction system is connected to the lighting lamp signals and is used to control the lighting lamps to perform lighting actions according to the deployment results.

9. The cabin daylight simulation lighting source according to claim 8, characterized in that: The number of the lighting lamps is nine.

10. The cabin daylight simulation lighting source according to claim 9, characterized in that: The peak wavelengths of the nine lighting lamps are 420nm, 450nm, 480nm, 520nm, 560nm, 600nm, 640nm, 680nm and 750nm respectively, and the full width at half maximum are 40nm, 45nm, 50nm, 100nm, 105nm, 110nm, 80nm, 75nm and 90nm respectively.

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