A control method and system for improving the light effect of LED lamp beads

Abstract

The present invention discloses a control method and system for improving the light effect of LED lamp beads, and relates to the field of lighting control technology. It includes: a light effect improvement judgment module, a light illumination adjustment module, a light color temperature adjustment module and a real-time lamp bead light effect improvement module. The present invention can realize personalized lighting adjustment by monitoring the pupil diameter and real-time lighting information of the target user, and adjust the light brightness and color temperature according to the pupil diameter of the target user and the ambient lighting conditions, so as to provide a lighting effect that better meets the user's needs and comfort; it can obtain the user's pupil diameter and current lighting information in real time, and make a light illumination and color temperature adjustment strategy according to the analysis results. This real-time feedback adjustment can ensure that the lighting effect is always kept within a comfortable range, provide a more intelligent and personalized lighting experience, and improve the lighting effect of LED lamp beads without fluorescent powder.

Description

Technical Field

[0001] The present invention relates to the field of lighting control technology, and in particular to a control method and system for improving the light effect of LED lamp beads. Background Art

[0002] Existing LED lamp beads have problems with delay or inability to respond in real time in terms of brightness adjustment. The lack of an intelligent dimming system or feedback mechanism makes it impossible for LED lamp beads to adjust the brightness in real time according to changes in ambient light or user needs, affecting the flexibility and adaptability of the lamp. The light in some areas is too strong or too weak, causing visual fatigue or visual discomfort, affecting the user experience and comfort. The brightness cannot be adjusted in real time according to different scenarios or needs, limiting the scope of application and functionality of the lamp; uneven lighting and untimely brightness adjustment may lead to energy waste and reduce energy efficiency and energy-saving effects.

[0003] Therefore, we urgently need to provide a control method and system for improving the lighting effect of LED lamp beads with intelligent adjustment. Summary of the invention

[0004] The present invention aims to provide a control method and system for improving the light efficiency of LED lamp beads, and intelligently adjust the control parameters of fluorescent powder-free LED lamp beads according to user needs.

[0005] A control method for improving the light effect of LED lamp beads, comprising:

[0006] S1. Obtain the pupil diameter of the target user at the target location at a preset time interval to obtain the real-time user pupil diameter; compare the real-time user pupil diameter with the preset standard pupil diameter range to obtain the lamp bead light effect comfort result; if the real-time user pupil diameter exceeds the preset standard pupil diameter range, the lamp bead light effect comfort result is uncomfortable, and enter step S2; otherwise, continue to monitor the target user pupil diameter at preset time intervals;

[0007] S2. Acquire the current lighting information in the target location in real time to obtain real-time lighting information; the real-time lighting information includes the current light illumination information and the current light color temperature information; perform light illumination analysis based on the current light illumination information and the light illumination analysis model to obtain a real-time light illumination adjustment strategy; acquire the current temperature information, perform light color temperature analysis based on the current temperature information, the current light color temperature information and the light color temperature analysis model to obtain a light color temperature analysis result; match the light color temperature adjustment strategy in the light color temperature adjustment library based on the light color temperature analysis result to obtain a real-time light color temperature adjustment strategy; the light color temperature adjustment library is established based on the fuzzy control algorithm; use the real-time light illumination adjustment strategy and the real-time light color temperature adjustment strategy to improve the light efficiency of the phosphor-free LED lamp beads.

[0008] As a preferred technical solution of the present invention, the lighting illumination analysis model in step S2 includes a lighting uniformity analysis layer, a lighting illumination error calculation layer and a strategy optimization layer;

[0009] The target location is evenly divided into J grids G of the same size j , j = 1, 2, ..., J; the current light illumination information contains all the grids G j The light illuminance L measured at the center point j ;

[0010] The light uniformity analysis layer is used to use the formula U = [min (L1, L2, ..., L J ) / L p ], and obtain the uniformity of the illumination area U; L p Indicates the total light illuminance L j The average value of min(L1, L2, ..., L J ) represents the total light illuminance L j The minimum value of

[0011] The light illumination error calculation layer is used to use the formula V=Z1+Z2+…+Z j +…+Z J , get the lighting illumination error V; using the formula Z j =(L j -w) / Q, get the standardized value Z j ; Z j Indicates the light illuminance L j The standardized value calculated using the Z-score standardization method; w represents the target user's preset light illumination value; using the formula , we get the standard deviation of light illumination Q; Q represents the light illumination L j and the standard deviation of the target user’s preset light illumination value;

[0012] The strategy optimization layer is used to calculate the light illumination adjustment value K using the formula K=α*U+β*V; α represents the weight of U in the formula K=α*U+β*V; β represents the weight of V in the formula K=α*U+β*V; the group optimization algorithm is used to simulate dimming according to the light illumination adjustment value to obtain a real-time light illumination adjustment strategy.

[0013] As a preferred technical solution of the present invention, the specific steps of using a swarm optimization algorithm to simulate dimming according to the light illumination adjustment value to obtain a real-time light illumination adjustment strategy include:

[0014] Use the best point set method to construct I lighting illumination adjustment strategy individuals H i , i=1, 2, ..., I; each lighting intensity adjustment strategy individual H iA set of parameters for adjusting the light effect of LED lamp beads without phosphors is included; I lighting illumination adjustment strategy individual H i Combine to obtain the iterative population of lighting illumination adjustment strategy; set the maximum number of iterations;

[0015] According to the lighting intensity adjustment strategy, the lighting intensity adjustment strategy individual H in the population is iterated i Perform simulated lighting illumination adjustment to obtain simulated lighting illumination adjustment value S i ; Calculate the simulated lighting illumination adjustment value S i The difference between the standard light illumination adjustment value and the adjustment error O i , the adjustment error O i The inverse of the lighting intensity adjustment strategy H i The fitness D i ;

[0016] Specific steps for simulating lighting illumination adjustment:

[0017] The lighting intensity adjustment strategy individual H i After adjusting the parameters of the light effect of the LED lamp without fluorescent powder in the simulation software, the simulated light illumination information is obtained; the simulated light illumination information is input into the light illumination analysis model for analysis, and the simulated light illumination adjustment value S is obtained. i ;

[0018] The Osprey optimization algorithm is used to converge the iterative population of the lighting illumination adjustment strategy. When the maximum number of iterations is reached, the lighting illumination adjustment strategy individual H corresponding to the maximum fitness is output. i , which is the optimal lighting illumination adjustment strategy individual; the parameters used to adjust the light effect of the non-fluorescent LED lamp beads in the optimal lighting illumination adjustment strategy individual are used as the real-time lighting illumination adjustment strategy.

[0019] As a preferred technical solution of the present invention, the light color temperature analysis model in step S2 includes a data preprocessing layer, a color temperature feature extraction layer, a comprehensive feature analysis layer and a result output layer;

[0020] The data preprocessing layer is used to preprocess the current light color temperature information in the real-time lighting information to obtain preprocessed light color temperature information;

[0021] The color temperature feature extraction layer is used to extract features based on the preprocessed light color temperature information to obtain the light color temperature feature value;

[0022] The comprehensive feature analysis layer is used to analyze the light color temperature characteristic value and the current temperature information to obtain the light color temperature analysis result;

[0023] The result output layer is used to output the light color temperature analysis results.

[0024] As a preferred technical solution of the present invention, the specific steps of training the comprehensive feature analysis layer in the light color temperature analysis model include:

[0025] Collect several groups of analysis result training samples with artificial fuzzy rule annotations; one group of analysis result training samples contains the characteristic value and temperature information of the light color temperature monitored at the same time; combine several groups of analysis result training samples with artificial fuzzy rule annotations to obtain a comprehensive feature analysis training set; the artificial fuzzy rule annotations are the target values ​​of a group of analysis result training samples;

[0026] The comprehensive feature analysis training set is input into the light color temperature analysis model to train the comprehensive feature analysis layer with the target value as the target, and an initial comprehensive feature analysis layer is obtained; a model evaluation is performed on the initial comprehensive feature analysis layer to obtain an evaluation result of the comprehensive feature analysis layer; if the evaluation result of the comprehensive feature analysis layer is passed, the trained initial comprehensive feature analysis layer is used as the comprehensive feature analysis layer; otherwise, the model training is continued using the comprehensive feature analysis training set.

[0027] As a preferred technical solution of the present invention, the specific steps of matching the light color temperature adjustment strategy in the light color temperature adjustment library according to the light color temperature analysis result include:

[0028] The light color temperature adjustment library contains R artificially set light color temperature fuzzy inference rules A r Sum and light color temperature fuzzy inference rule A r The corresponding light color temperature fuzzy output B r , r=1, 2, ..., R; light color temperature fuzzy output B r Contains control parameters for adjusting the color temperature of non-phosphor LED lamp beads;

[0029] The light color temperature analysis results and all light color temperature fuzzy inference rules A r Perform similarity analysis to obtain the target light color temperature fuzzy inference rule; the target light color temperature fuzzy inference rule represents the light color temperature fuzzy inference rule A that has the greatest similarity to the light color temperature analysis result. r ; The fuzzy output of the target light color temperature corresponding to the fuzzy inference rule is B r As a real-time lighting color temperature adjustment strategy.

[0030] As a preferred technical solution of the present invention, the group optimization algorithm used in the simulated dimming using the group optimization algorithm according to the light illumination adjustment value is a genetic algorithm.

[0031] A control method for improving the light effect of LED lamp beads, comprising:

[0032] The light effect improvement judgment module is used to obtain the pupil diameter of the target user at the target location at a preset time interval to obtain the real-time user pupil diameter; compare the real-time user pupil diameter with the preset standard pupil diameter range to obtain the lamp bead light effect comfort result; if the real-time user pupil diameter exceeds the preset standard pupil diameter range, the lamp bead light effect comfort result is uncomfortable, and enters step S2; otherwise, continue to monitor the target user pupil diameter at the preset time interval;

[0033] The lighting adjustment module is used to deploy the lighting illumination analysis model, obtain the current lighting information in the target location in real time, and obtain the real-time lighting information; the real-time lighting information includes the current lighting illumination information and the current lighting color temperature information; the lighting illumination analysis is performed according to the current lighting illumination information and the lighting illumination analysis model to obtain the real-time lighting illumination adjustment strategy;

[0034] The light color temperature adjustment module is used to deploy the light color temperature analysis model, obtain the current temperature information, perform light color temperature analysis based on the current temperature information, the current light color temperature information and the light color temperature analysis model, and obtain the light color temperature analysis result; match the light color temperature adjustment strategy in the light color temperature adjustment library according to the light color temperature analysis result, and obtain the real-time light color temperature adjustment strategy;

[0035] The real-time lamp bead light effect enhancement module is used to enhance the light effect of phosphor-free LED lamp beads by using the real-time light illumination adjustment strategy and the real-time light color temperature adjustment strategy.

[0036] The present invention has the following advantages:

[0037] 1. The present invention can realize personalized lighting adjustment by monitoring the pupil diameter and real-time lighting information of the target user; adjust the light brightness and color temperature according to the user's pupil diameter and ambient lighting conditions to provide a lighting effect that better meets the user's needs and comfort; can obtain the user's pupil diameter and current lighting information in real time, and make lighting illumination and color temperature adjustment strategies according to the analysis results. This real-time feedback adjustment can ensure that the lighting effect always remains within a comfortable range, provide a more intelligent and personalized lighting experience, and improve the lighting effect of phosphor-free LED lamp beads; personalized lighting adjustment and comfort analysis can enhance the user experience, so that users can enjoy lighting effects that meet their needs in different environments, and improve the comfort and efficiency of work, study and life by optimizing the light illumination and color temperature.

[0038] 2. The present invention can ensure uniform lighting in the lighting area through the application of the light uniformity analysis layer, avoiding visual discomfort or reduced work efficiency caused by uneven lighting; through the light illumination error calculation layer, the deviation between the illumination in each grid and the preset illumination can be accurately calculated, and through standardization processing, a basis for subsequent strategy optimization is provided; the strategy optimization layer adjusts the light illumination through a group optimization algorithm, aiming to achieve the optimal lighting effect while reducing unnecessary energy consumption; personalized lighting adjustments are performed according to the light illumination value preset by the user to meet the lighting needs of different users or scenes. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 The present invention is a schematic diagram of the structure of a control system for improving the light effect of LED lamp beads used in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to enable persons skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0041] Embodiment 1, a control method for improving the light effect of LED lamp beads, comprising:

[0042] S1. Obtain the pupil diameter of the target user at the target location at preset time intervals to obtain the real-time user pupil diameter; compare the real-time user pupil diameter with the preset standard pupil diameter range to obtain the lamp bead lighting effect comfort result; if the real-time user pupil diameter exceeds the preset standard pupil diameter range, the lamp bead lighting effect comfort result is uncomfortable, and enter step S2; otherwise, continue to monitor the target user pupil diameter at preset time intervals.

[0043] Among them, LED lamp beads are specifically limited to LED lamp beads without fluorescent powder.

[0044] The preset standard pupil diameter range is set by professional technicians according to actual conditions. For example, the preset standard pupil diameter range is between 3.25mm and 3.85mm. The real-time user pupil diameter can be obtained through an infrared camera; infrared light is used to illuminate the eyes and the reflected light is measured to obtain the eye movement and pupil diameter; for example, an eye tracker can be used in conjunction, and the eye tracker usually measures the diameter by calculating the reflected light of the pupil, usually in the millimeter range; or an ordinary camera and computer vision technology can be used to estimate the pupil diameter by taking an eye image and analyzing the pupil area. In the eye area, morphological processing methods are applied to detect the outline of the pupil and calculate the diameter of the circumscribed circle or ellipse of the pupil outline; infrared scanning can also be used to accurately measure the pupil diameter. The infrared camera can accurately obtain the changes in the pupil by illuminating the eye and capturing the infrared signal reflected by the pupil; the preset time interval is set by professional technicians according to actual conditions, and the interval should not be too short. Frequent adjustment of lighting is not conducive to the user experience; phosphor-free LED lamp beads are installed in the target location for lighting needs, and the target location contains natural light and artificial light; artificial light is only provided by phosphor-free LED lamp beads to be adjusted.

[0045] S2. Acquire the current lighting information in the target location in real time to obtain real-time lighting information; the real-time lighting information includes the current light illumination information and the current light color temperature information; perform light illumination analysis based on the current light illumination information and the light illumination analysis model to obtain a real-time light illumination adjustment strategy; acquire the current temperature information, perform light color temperature analysis based on the current temperature information, the current light color temperature information and the light color temperature analysis model to obtain a light color temperature analysis result; match the light color temperature adjustment strategy in the light color temperature adjustment library based on the light color temperature analysis result to obtain a real-time light color temperature adjustment strategy; the light color temperature adjustment library is established based on the fuzzy control algorithm; use the real-time light illumination adjustment strategy and the real-time light color temperature adjustment strategy to improve the light efficiency of the phosphor-free LED lamp beads.

[0046] The lighting illumination analysis model in step S2 includes a lighting uniformity analysis layer, a lighting illumination error calculation layer and a strategy optimization layer.

[0047] The target location is evenly divided into J grids G of the same size j , j = 1, 2, ..., J; the current light illumination information contains all the grids G j The light illuminance L measured at the center point j。

[0048] The light uniformity analysis layer is used to use the formula U = [min (L1, L2, ..., L J ) / L p ], and obtain the uniformity of the illumination area U; L pIndicates the total light illuminance L j The average value of min(L1, L2, ..., L J ) represents the total light illuminance L j The minimum value of .

[0049] The light illumination error calculation layer is used to use the formula V=Z1+Z2+…+Z j +…+Z J , get the lighting illumination error V; using the formula Z j =(L j -w) / Q, get the standardized value Z j ; Z j Indicates the light illuminance L j The standardized value calculated using the Z-score standardization method; w represents the target user's preset light illumination value; using the formula , we get the standard deviation of light illumination Q; Q represents the light illumination L j and the standard deviation of the target user's preset light illumination value.

[0050] The strategy optimization layer is used to calculate the light illumination adjustment value K using the formula K=α*U+β*V; α represents the weight of U in the formula K=α*U+β*V; β represents the weight of V in the formula K=α*U+β*V; the group optimization algorithm is used to simulate dimming according to the light illumination adjustment value to obtain a real-time light illumination adjustment strategy; the values ​​of α and β are set by professional technicians according to actual conditions, and α+β=1.

[0051] Through the calculation of the illumination uniformity analysis layer, the uniformity U of the illumination area can be obtained. This helps to ensure uniform illumination distribution in the entire area, improve visual comfort and work efficiency; the formula V of the lighting illumination error calculation layer can help evaluate the accuracy of illumination. j The calculation can reduce lighting errors, ensure that the light illumination is close to the user's expected value, and improve the lighting quality; the formula K in the strategy optimization layer combines the weights of uniformity U and error V to calculate the light illumination adjustment value K, which can help optimize the light illumination adjustment strategy, adjust the light according to real-time needs and conditions, and improve lighting effects and energy efficiency.

[0052] According to the light illumination adjustment value, the swarm optimization algorithm is used to simulate dimming and obtain the specific steps of the real-time light illumination adjustment strategy, including:

[0053] Use the best point set method to construct I lighting illumination adjustment strategy individuals H i , i=1, 2, ..., I; each lighting intensity adjustment strategy individual H i A set of parameters for adjusting the light effect of LED lamp beads without phosphors is included; I lighting illumination adjustment strategy individual Hi Combination, get the iterative population of lighting illumination adjustment strategy; set the maximum number of iterations; the best point set method can cover the entire search space as evenly as possible with fewer sample points; the maximum number of iterations is set by professional and technical personnel according to actual conditions; in terms of computational complexity, the implementation of the good point set method is usually relatively simple and does not require a lot of randomness or tedious calculation process, which makes it easier to operate in practical applications. In order to improve the diversity of the population, the good point set method is used to initialize the population so that individuals can reflect the information of the solution space as much as possible.

[0054] According to the lighting intensity adjustment strategy, the lighting intensity adjustment strategy individual H in the population is iterated i Perform simulated lighting illumination adjustment to obtain simulated lighting illumination adjustment value S i ; Calculate the simulated lighting illumination adjustment value S i The difference between the standard light illumination adjustment value and the adjustment error O i , the adjustment error O i The inverse of the lighting intensity adjustment strategy H i The fitness D i。

[0055] Specific steps for simulating lighting illumination adjustment:

[0056] The lighting intensity adjustment strategy individual H i After adjusting the parameters of the light effect of the LED lamp without fluorescent powder in the simulation software, the simulated light illumination information is obtained; the simulated light illumination information is input into the light illumination analysis model for analysis, and the simulated light illumination adjustment value S is obtained. i ; During the simulation calculation, the current natural light value is calculated according to the light illumination adjustment value. According to the light illumination value and the known value of artificial light emitted by the LED lamp beads, the current natural light value can be obtained through a simple subtraction operation. The same natural light conditions must be maintained during the simulation calculation.

[0057] The Osprey optimization algorithm is used to converge the iterative population of the lighting illumination adjustment strategy. When the maximum number of iterations is reached, the lighting illumination adjustment strategy individual H corresponding to the maximum fitness is output. i , which is the optimal lighting illumination adjustment strategy individual; the parameters used to adjust the light effect of the non-fluorescent LED lamp beads in the optimal lighting illumination adjustment strategy individual are used as the real-time lighting illumination adjustment strategy.

[0058] When the swarm optimization algorithm is a genetic algorithm, the Osprey optimization algorithm is used to converge the iterative population of the light illumination adjustment strategy and change the position update process, so that the algorithm pays more attention to the accuracy and efficiency of local search, which helps the algorithm to achieve better search results in complex optimization problems and improve the solution quality and efficiency.

[0059] The light color temperature analysis model in step S2 includes a data preprocessing layer, a color temperature feature extraction layer, a comprehensive feature analysis layer and a result output layer.

[0060] The data preprocessing layer is used to preprocess the current light color temperature information in the real-time lighting information to obtain preprocessed light color temperature information.

[0061] The color temperature feature extraction layer is used to extract features based on the preprocessed light color temperature information to obtain light color temperature feature values.

[0062] The comprehensive feature analysis layer is used to analyze the light color temperature characteristic value and the current temperature information to obtain the light color temperature analysis result.

[0063] The result output layer is used to output the light color temperature analysis results.

[0064] The color temperature feature extraction layer performs feature extraction based on the preprocessed light color temperature information to obtain the light color temperature characteristic value, which helps to accurately capture the key features of the light color temperature and improve the accuracy and effectiveness of feature extraction; the comprehensive feature analysis layer performs analysis based on the light color temperature characteristic value and the current temperature information to obtain the light color temperature analysis result, which can improve the reliability and accuracy of the analysis result and provide a more reliable basis for light color temperature adjustment and optimization.

[0065] The specific steps for training the comprehensive feature analysis layer in the light color temperature analysis model include:

[0066] Collect several groups of analysis result training samples with artificial fuzzy rule annotations; one group of analysis result training samples contains light color temperature feature values ​​and temperature information monitored at the same time; combine several groups of analysis result training samples with artificial fuzzy rule annotations to obtain a comprehensive feature analysis training set; the artificial fuzzy rule annotations are used as target values ​​for a group of analysis result training samples; the content of the artificial fuzzy rule annotations is, for example, based on the temperature information and the light color temperature feature values, if the indoor temperature is detected to be lower than the human comfort temperature and there is a trend of decreasing, the artificial fuzzy rule annotation is used to enhance the warmth of the color temperature.

[0067] The comprehensive feature analysis training set is input into the light color temperature analysis model to train the comprehensive feature analysis layer with the target value as the target, and an initial comprehensive feature analysis layer is obtained; a model evaluation is performed on the initial comprehensive feature analysis layer to obtain an evaluation result of the comprehensive feature analysis layer; if the evaluation result of the comprehensive feature analysis layer is passed, the trained initial comprehensive feature analysis layer is used as the comprehensive feature analysis layer; otherwise, the model training is continued using the comprehensive feature analysis training set.

[0068] The specific steps of matching the light color temperature adjustment strategy in the light color temperature adjustment library according to the light color temperature analysis results include:

[0069] The light color temperature adjustment library contains R artificially set light color temperature fuzzy inference rules A r Sum and light color temperature fuzzy inference rule A r The corresponding light color temperature fuzzy output B r , r=1, 2, ..., R; light color temperature fuzzy output B r It contains control parameters for adjusting the color temperature of non-phosphor LED lamp beads.

[0070] The light color temperature analysis results and all light color temperature fuzzy inference rules A r Perform similarity analysis to obtain the target light color temperature fuzzy inference rule; the target light color temperature fuzzy inference rule represents the light color temperature fuzzy inference rule A that has the greatest similarity to the light color temperature analysis result. r ; The fuzzy output of the target light color temperature corresponding to the fuzzy inference rule is B r As a real-time lighting color temperature adjustment strategy.

[0071] Fuzzy inference rule for all light color temperatures A r It is established by professional technicians according to the actual color temperature and temperature changes, and the corresponding light color temperature fuzzy output B is constructed according to the target light color temperature fuzzy inference rules. r Before turning into a real-time light color temperature adjustment strategy, it is also necessary to fuzzy the light color temperature output B r Perform clarification processing; perform similarity analysis on the light color temperature analysis results and all light color temperature fuzzy inference rules, and find the target light color temperature fuzzy inference rule with the highest similarity to the analysis results; through similarity analysis and matching the most appropriate light color temperature fuzzy inference rule, accurate light color temperature adjustment is achieved, improving the lighting effect and comfort; select the target light color temperature fuzzy output B r As a real-time adjustment strategy, the system can respond to analysis results instantly and quickly adjust the light color temperature to meet actual needs.

[0072] Example 2, a control system for improving the light effect of LED lamp beads, see Figure 1 As shown, including:

[0073] The light effect improvement judgment module is used to obtain the pupil diameter of the target user at the target location at a preset time interval to obtain the real-time user pupil diameter; compare the real-time user pupil diameter with the preset standard pupil diameter range to obtain the lamp bead light effect comfort result; if the real-time user pupil diameter exceeds the preset standard pupil diameter range, the lamp bead light effect comfort result is uncomfortable, and enters step S2; otherwise, continue to monitor the target user pupil diameter at the preset time interval;

[0074] The lighting adjustment module is used to deploy the lighting illumination analysis model, obtain the current lighting information in the target location in real time, and obtain the real-time lighting information; the real-time lighting information includes the current lighting illumination information and the current lighting color temperature information; the lighting illumination analysis is performed according to the current lighting illumination information and the lighting illumination analysis model to obtain the real-time lighting illumination adjustment strategy;

[0075] The light color temperature adjustment module is used to deploy the light color temperature analysis model, obtain the current temperature information, perform light color temperature analysis based on the current temperature information, the current light color temperature information and the light color temperature analysis model, and obtain the light color temperature analysis result; match the light color temperature adjustment strategy in the light color temperature adjustment library according to the light color temperature analysis result, and obtain the real-time light color temperature adjustment strategy;

[0076] The real-time lamp bead light effect enhancement module is used to enhance the light effect of phosphor-free LED lamp beads by using the real-time light illumination adjustment strategy and the real-time light color temperature adjustment strategy.

[0077] It should be understood that those skilled in the art can make improvements or changes based on the above description, and all such improvements and changes should fall within the scope of protection of the appended claims of the present invention. Parts not described in detail in this specification belong to the prior art known to those skilled in the art.

Claims

1. A control method for improving the light effect of LED lamp beads, characterized in that: include: S1. Obtain the pupil diameter of the target user at the target location at a preset time interval to obtain the real-time user pupil diameter; Compare the real-time user pupil diameter with the preset standard pupil diameter range to obtain the lamp bead lighting effect comfort result; If the real-time user pupil diameter exceeds the preset standard pupil diameter range, the lamp bead light effect comfort result is uncomfortable, and the process goes to step S2; otherwise, the target user pupil diameter is continuously monitored at preset time intervals; S2. Obtain the current lighting information within the target location in real time to obtain real-time lighting information; Real-time lighting information includes current lighting illumination information and current lighting color temperature information; perform lighting illumination analysis based on current lighting illumination information and lighting illumination analysis model to obtain real-time lighting illumination adjustment strategy; obtain current temperature information, perform lighting color temperature analysis based on current temperature information, current lighting color temperature information and lighting color temperature analysis model to obtain lighting color temperature analysis result; match lighting color temperature adjustment strategy in lighting color temperature adjustment library based on lighting color temperature analysis result to obtain real-time lighting color temperature adjustment strategy; lighting color temperature adjustment library is established based on fuzzy control algorithm; utilize real-time lighting illumination adjustment strategy and real-time lighting color temperature adjustment strategy to improve the lighting efficiency of LED lamp beads without phosphor; In step S2, the lighting illumination analysis model includes a lighting uniformity analysis layer, a lighting illumination error calculation layer and a strategy optimization layer; The target location is evenly divided into J grids G of the same size j , j = 1, 2, ..., J; the current light illumination information contains all the grids G j The light illuminance L measured at the center point j ; The light uniformity analysis layer is used to use the formula U = [min (L1, L2, ..., L J ) / L p ], and obtain the uniformity of the illumination area U; L p Indicates the total light illuminance L j The average value of min(L1, L2, ..., L J ) represents the total light illuminance L j The minimum value of The light illumination error calculation layer is used to use the formula V=Z1+Z2+…+Z j +…+Z J , get the lighting illumination error V; using the formula Z j =(L j -w) / Q, get the standardized value Z j ; Z j Indicates the light illuminance L j The normalized value calculated using the Z-score normalization method; w represents the target user preset light illumination value; Using the formula , we get the standard deviation of light illumination Q; Q represents the light illumination L j and the standard deviation of the target user’s preset light illumination value; The strategy optimization layer is used to calculate the light illumination adjustment value K using the formula K=α*U+β*V; α represents the weight of U in the formula K=α*U+β*V; β represents the weight of V in the formula K=α*U+β*V; the group optimization algorithm is used to simulate dimming according to the light illumination adjustment value to obtain the real-time light illumination adjustment strategy; According to the light illumination adjustment value, the swarm optimization algorithm is used to simulate dimming and obtain the specific steps of the real-time light illumination adjustment strategy, including: Use the best point set method to construct I lighting illumination adjustment strategy individuals H i , i=1, 2, ..., I; each lighting intensity adjustment strategy individual H i A set of parameters for adjusting the light effect of LED lamp beads without phosphors is included; I lighting illumination adjustment strategy individual H i Combine to obtain the iterative population of lighting illumination adjustment strategy; set the maximum number of iterations; According to the lighting intensity adjustment strategy, the lighting intensity adjustment strategy individual H in the population is iterated i Perform simulated lighting illumination adjustment to obtain simulated lighting illumination adjustment value S i ; Calculate the simulated lighting illumination adjustment value S i The difference between the standard light illumination adjustment value and the adjustment error O i , the adjustment error O i The inverse of the lighting intensity adjustment strategy H i The fitness D i ; Specific steps for simulating lighting illumination adjustment: The lighting intensity adjustment strategy individual H i After adjusting the parameters of the light effect of the LED lamp without fluorescent powder in the simulation software, the simulated light illumination information is obtained; the simulated light illumination information is input into the light illumination analysis model for analysis, and the simulated light illumination adjustment value S is obtained. i ; The Osprey optimization algorithm is used to converge the iterative population of the lighting illumination adjustment strategy. When the maximum number of iterations is reached, the lighting illumination adjustment strategy individual H corresponding to the maximum fitness is output. i , which is the optimal lighting illumination adjustment strategy individual; the parameters used to adjust the light effect of the non-fluorescent LED lamp beads in the optimal lighting illumination adjustment strategy individual are used as the real-time lighting illumination adjustment strategy.

2. A control method for improving the light effect of LED lamp beads according to claim 1, characterized in that: The light color temperature analysis model in step S2 includes a data preprocessing layer, a color temperature feature extraction layer, a comprehensive feature analysis layer and a result output layer; The data preprocessing layer is used to preprocess the current light color temperature information in the real-time lighting information to obtain preprocessed light color temperature information; The color temperature feature extraction layer is used to extract features based on the preprocessed light color temperature information to obtain the light color temperature feature value; The comprehensive feature analysis layer is used to analyze the light color temperature characteristic value and the current temperature information to obtain the light color temperature analysis result; The result output layer is used to output the light color temperature analysis results.

3. A control method for improving the light effect of LED lamp beads according to claim 2, characterized in that: The specific steps for training the comprehensive feature analysis layer in the light color temperature analysis model include: Collect several groups of analysis result training samples with artificial fuzzy rule annotations; one group of analysis result training samples contains the characteristic value and temperature information of the light color temperature monitored at the same time; combine several groups of analysis result training samples with artificial fuzzy rule annotations to obtain a comprehensive feature analysis training set; the artificial fuzzy rule annotations are the target values ​​of a group of analysis result training samples; The comprehensive feature analysis training set is input into the light color temperature analysis model to train the comprehensive feature analysis layer with the target value as the target, and an initial comprehensive feature analysis layer is obtained; a model evaluation is performed on the initial comprehensive feature analysis layer to obtain an evaluation result of the comprehensive feature analysis layer; if the evaluation result of the comprehensive feature analysis layer is passed, the trained initial comprehensive feature analysis layer is used as the comprehensive feature analysis layer; otherwise, the model training is continued using the comprehensive feature analysis training set.

4. A control method for improving the light effect of LED lamp beads according to claim 3, characterized in that: The specific steps of matching the light color temperature adjustment strategy in the light color temperature adjustment library according to the light color temperature analysis results include: The light color temperature adjustment library contains R artificially set light color temperature fuzzy inference rules A r Sum and light color temperature fuzzy inference rule A r The corresponding light color temperature fuzzy output B r , r=1, 2, ..., R; light color temperature fuzzy output B r Contains control parameters for adjusting the color temperature of non-phosphor LED lamp beads; The light color temperature analysis results and all light color temperature fuzzy inference rules A r Perform similarity analysis to obtain the target light color temperature fuzzy inference rule; the target light color temperature fuzzy inference rule represents the light color temperature fuzzy inference rule A that has the greatest similarity to the light color temperature analysis result. r ; The fuzzy output of the target light color temperature corresponding to the fuzzy inference rule is B r As a real-time lighting color temperature adjustment strategy.

5. The control method for improving the light effect of LED lamp beads according to claim 1, characterized in that: The group optimization algorithm used in the simulated dimming according to the light illumination adjustment value is a genetic algorithm.

6. A control system for improving the light effect of LED lamp beads, characterized in that: The system applies a control method for improving the light effect of LED lamp beads as described in any one of claims 1 to 5, including: The light effect improvement judgment module is used to obtain the pupil diameter of the target user at the target location at a preset time interval to obtain the real-time user pupil diameter; compare the real-time user pupil diameter with the preset standard pupil diameter range to obtain the lamp bead light effect comfort result; if the real-time user pupil diameter exceeds the preset standard pupil diameter range, the lamp bead light effect comfort result is uncomfortable, and enters step S2; otherwise, continue to monitor the target user pupil diameter at the preset time interval; The lighting adjustment module is used to deploy the lighting illumination analysis model, obtain the current lighting information in the target location in real time, and obtain the real-time lighting information; the real-time lighting information includes the current lighting illumination information and the current lighting color temperature information; the lighting illumination analysis is performed according to the current lighting illumination information and the lighting illumination analysis model to obtain the real-time lighting illumination adjustment strategy; The light color temperature adjustment module is used to deploy the light color temperature analysis model, obtain the current temperature information, perform light color temperature analysis based on the current temperature information, the current light color temperature information and the light color temperature analysis model, and obtain the light color temperature analysis result; match the light color temperature adjustment strategy in the light color temperature adjustment library according to the light color temperature analysis result, and obtain the real-time light color temperature adjustment strategy; The real-time lamp bead light effect enhancement module is used to enhance the light effect of phosphor-free LED lamp beads by using the real-time light illumination adjustment strategy and the real-time light color temperature adjustment strategy.

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