A light source control system for adaptive adjustment of multi-primary color LEDs without phosphors

Abstract

The present invention relates to the field of LED control technology, and in particular to a light source control system for adaptively adjusting a phosphor-free multi-primary color LED. The system includes: a spectral distribution module for acquiring environmental multi-dimensional light data and an LED scene graph; mining spectral distribution characteristics of the environmental multi-dimensional light data to construct an environmental spectral distribution graph; an optimal demand module for performing optimal demand analysis on the environmental spectral distribution graph based on the LED scene graph to obtain optimal light source demand characteristic data; an optical characteristic module for identifying the current illumination color temperature of the phosphor-free multi-primary color LED array to obtain LED array color temperature data; generating current LED optical characteristic parameters based on the LED array color temperature data; and a dynamic color temperature adjustment module for dynamically adjusting the output color temperature of the current LED optical characteristic parameters based on the phosphor-free multi-primary color LED array to obtain dynamically adjusted light source color temperature parameters. The present invention realizes efficient and adaptive LED control.

Description

Technical Field

[0001] The invention relates to the technical field of LED control, and in particular to a light source control system for adaptively adjusting multi-primary color LEDs without fluorescent powder. Background Art

[0002] With the continuous development of lighting technology, LED light sources have become the mainstream choice in the lighting field due to their high efficiency, energy saving and long service life. Traditional LED light sources usually use phosphor conversion technology, using blue light or ultraviolet LED chips to excite phosphors to emit white light. However, this method has some defects, such as narrow spectrum, poor color rendering, and low color temperature stability. In contrast, phosphor-free multi-primary color LEDs have obvious advantages in spectral characteristics, color rendering and color adjustment capabilities due to their unique light-emitting mechanism. They use a variety of color LED chips (such as red, green, blue, and yellow) for direct mixed emission, do not require the use of phosphors, and can cover the entire visible light band, thereby achieving excellent color rendering and color temperature stability. By independently controlling the output of LED chips of different colors, the phosphor-free multi-primary LED also has rich dynamic color adjustment capabilities, which can meet the personalized needs of various lighting scenes. However, although the phosphor-free multi-primary LED has many advantages, its structure is more complex and the control strategy is more detailed. In practical applications, how to adaptively adjust the color and brightness of the LED light source according to different environmental conditions and usage requirements has always been a technical problem that needs to be solved urgently. The traditional manual adjustment method is inefficient and cannot adapt to environmental parameters to control the LED, which is difficult to meet the development needs of intelligent lighting. Therefore, an intelligent LED adaptive adjustment light source control system is needed to realize the intelligence of the lighting system. Summary of the invention

[0003] In order to solve the above technical problems, the present invention proposes a light source control system with adaptive adjustment of multi-primary color LEDs without phosphors to solve at least one of the above technical problems.

[0004] To achieve the above object, the present invention provides a light source control system for adaptively adjusting a multi-primary color LED without phosphor, comprising:

[0005] The spectrum distribution module is used to obtain the multi-dimensional light data of the environment and the LED scene map; the spectrum distribution characteristics of the multi-dimensional light data of the environment are mined to construct the spectrum distribution map of the environment;

[0006] The optimal demand module is used to perform optimal demand analysis on the environmental spectrum distribution map based on the LED scene map to obtain the optimal light source demand characteristic data;

[0007] The optical characteristic module is used to identify the current illumination color temperature of the phosphor-free multi-primary color LED array to obtain the LED array color temperature data; and to generate the current LED optical characteristic parameters based on the LED array color temperature data;

[0008] A dynamic color temperature adjustment module is used to dynamically adjust the output color temperature of the current LED optical characteristic parameters based on the phosphor-free multi-primary color LED array to obtain dynamically adjusted light source color temperature parameters;

[0009] The error compensation module is used to perform error compensation adjustment on the color temperature parameters of the dynamically adjusted light source according to the optimal light source demand characteristic data, thereby generating light source error compensation adjustment parameters; perform light source output control processing based on the light source error compensation adjustment parameters, and obtain light source dynamic response data;

[0010] The adaptive control module is used to calculate the driving current demand of each LED one by one based on the dynamic response data of the light source to obtain the LED adjustment driving current demand data; based on the LED adjustment driving current demand data, the adaptive parameter fine-tuning optimization is performed to construct an adaptive light source dynamic control strategy to execute the LED light source control operation.

[0011] The present invention comprehensively understands the ambient lighting conditions by analyzing the spectral distribution characteristics of the ambient multi-dimensional light data, provides data support for subsequent light source adjustment, constructs an ambient spectral distribution diagram to help the system better simulate the real lighting environment, provides a basic reference for LED light source adjustment, and determines the goal and direction of LED light source adjustment through optimal demand analysis, thereby improving the degree of optimization of the lighting effect and meeting the needs of specific scenes. The optimal light source demand characteristic data is obtained to help the system set appropriate light source parameters, thereby improving the efficiency and accuracy of LED light source adjustment. Through color temperature recognition and acquisition of optical characteristic parameters, the system accurately understands the performance and characteristics of the current LED light source, provides basic data for subsequent light source adjustment, generates the current LED optical characteristic parameter system, performs dynamic adjustment according to actual conditions, improves the adaptability and flexibility of the LED light source, and dynamically adjusts the light source color temperature parameters according to real-time The color temperature of the LED light source can be flexibly adjusted according to the needs to adapt to the lighting requirements of different scenes, and the adaptability and practicality of the light source can be improved. The error compensation adjustment can improve the accuracy and stability of the LED light source adjustment, reduce the impact of errors on the lighting effect, and improve the overall adjustment effect. The dynamic response data of the light source is obtained to help the system monitor the status and performance changes of the LED light source in real time, provide real-time feedback for dynamic control, calculate the specific driving parameters of each LED by the LED drive current demand, and realize fine control and adjustment of the LED light source. The adaptive parameter fine-tuning optimization and dynamic control strategy construction dynamically adjusts the parameters of the LED light source according to the real-time data and needs, making the control of the LED light source more intelligent and efficient. The LED light source control operation is executed to ensure that the LED light source is dynamically adjusted according to the set parameters and strategies to achieve the best balance between lighting effect and energy efficiency.

[0012] Preferably, the spectrum distribution module is specifically used for:

[0013] Identify the multi-dimensional light data of the environment based on the sensor; obtain the current LED scene map;

[0014] Calculate the light intensity of the environment multi-dimensional light data to obtain the value of the environment light intensity;

[0015] Perform time series change analysis on the multi-dimensional ambient light data to generate ambient light time series change data;

[0016] According to the ambient light intensity value, the light intensity fluctuation trend of the ambient light time series change data is analyzed to construct the ambient light intensity change curve;

[0017] The spectral distribution features are mined based on the ambient light intensity change curve to construct an ambient spectral distribution map.

[0018] The present invention uses a sensor to identify multi-dimensional ambient light data and obtain an LED scene graph. The system monitors the ambient lighting conditions in real time and provides real-time data support for LED light source adjustment. The LED scene graph acquisition system understands the layout and characteristics of the current lighting environment and provides an intuitive reference for subsequent light source adjustment. The ambient light intensity value is calculated to quantify the ambient lighting conditions and provide a specific numerical reference for subsequent light source adjustment. The ambient light intensity value obtained helps the system understand the strength of the ambient light and provides basic data support for light source adjustment. The time series change analysis helps the system understand the dynamic change of the ambient light and provides a basis for the dynamic adjustment of the LED light source. The system for generating the ambient light time series change data predicts the trend of the ambient light and provides a reference for the timing selection of light source adjustment. The light intensity fluctuation trend analysis helps the system understand the fluctuation of the ambient light and provides a reference for the stability of the light source adjustment. The ambient light intensity change curve system is constructed to intuitively display the change trend of the ambient light and provide guidance for subsequent light source adjustment. The spectral distribution feature mining helps the system understand the characteristics of the ambient spectrum and provides a basis for the color temperature adjustment of the LED light source. The ambient spectrum distribution map system is constructed to fully understand the distribution of the ambient spectrum and provide a detailed reference for the LED light source adjustment.

[0019] Preferably, the specific steps of mining the spectral distribution features based on the ambient light intensity variation curve to construct an ambient spectral distribution map are:

[0020] Based on the ambient light intensity change curve, the light source type is identified for the ambient multi-dimensional light data, thereby obtaining the ambient light source type;

[0021] Perform light source color temperature analysis based on the ambient light source type to obtain the ambient light source color temperature value;

[0022] Perform multi-band decomposition on the multi-dimensional light data of the environment to generate light intensity information of different frequencies;

[0023] Performing spectral intensity calculation on light intensity information of different frequencies to generate a spectral intensity curve;

[0024] Perform spectral morphology fitting on the spectral intensity curve based on the color temperature value of the ambient light source to generate spectral distribution morphology parameters;

[0025] The morphological characteristics of the spectral distribution morphological parameters are mined to construct the environmental spectral distribution map.

[0026] The present invention identifies the light source type through the light intensity change curve. The system accurately determines the light source type in the environment, provides guidance for the subsequent LED light source adjustment, obtains the ambient light source type, and the system understands the characteristics of the ambient lighting, providing basic data support for color temperature analysis and light source parameter adjustment. The color temperature analysis based on the ambient light source type helps the system determine the color temperature characteristics of the ambient light source, provides a basis for the color temperature adjustment of the LED light source, and obtains the ambient light source color temperature value. The system understands the characteristics of the ambient spectrum and provides a quantitative reference for the subsequent light source adjustment. Multi-band decomposition divides the light data into different frequency bands, helps the system understand the frequency characteristics of the ambient lighting, and provides more detailed data for the subsequent light source adjustment. According to support, the system that generates light intensity information of different frequencies analyzes the frequency distribution of ambient light and provides more accurate parameter optimization for light source adjustment. The spectral intensity calculation helps the system understand the distribution of light intensities of different frequencies and provides data support for spectral analysis and morphological fitting. The system that generates spectral intensity curves displays the changing trend of light intensities of different frequencies and provides a basis for the subsequent generation of spectral distribution morphological parameters. The spectral morphological fitting helps the system optimize the spectral intensity curve according to the color temperature value and provides a more accurate description of the morphological parameters of the ambient spectral distribution. The system that generates spectral distribution morphological parameters deeply understands the morphological characteristics of the ambient spectrum and provides a more accurate basis for the adjustment and control of LED light sources.

[0027] Preferably, the optimal demand module is specifically used for:

[0028] Perform visual feature analysis on the LED scene graph to obtain scene visual features;

[0029] Calculate the dynamic color temperature range of the ambient spectrum distribution diagram to obtain the dynamic color temperature range of the scene;

[0030] Calculate the optimal color temperature and brightness of the scene dynamic color temperature range based on the scene visual characteristics to generate the optimal color temperature and brightness of the scene;

[0031] Perform optimal demand analysis on the best color temperature and brightness of the scene to obtain the optimal light source demand characteristic data.

[0032] The present invention uses a visual feature analysis system to deeply understand the visual characteristics of the LED scene graph, including characteristics in terms of color, brightness, contrast, etc., to provide a visual reference for subsequent light source adjustment, and obtain the scene visual features to help the system quantitatively describe the visual performance of the LED scene, and provide basic data support for the dynamic color temperature range calculation and the optimal color temperature and brightness calculation. The dynamic color temperature range calculation system determines the range of change in color temperature of the LED scene, provides a basis for scene color temperature adjustment, and obtains the scene dynamic color temperature range to help the system understand the color temperature change requirements of the LED scene, and provides important data support for the calculation of optimal color temperature and brightness. The optimal color temperature and brightness calculation combines the scene visual features and the dynamic color temperature range to provide accurate color temperature and brightness settings for the optimal adjustment of the LED light source, and generates the scene optimal color temperature and brightness system to achieve the best lighting effect according to the scene needs, improve the adaptability and comfort of the light source, and the optimal demand analysis system understands the optimal color temperature and brightness requirements of the LED light source in different scenes, provides personalized customization for the light source adjustment control, and obtains the optimal light source demand feature data to help the system optimize the adjustment strategy of the LED light source, thereby improving the intelligence of the light source and the user experience.

[0033] Preferably, the optical property module is specifically used for:

[0034] Calculating the light intensity distribution of the phosphor-free multi-primary color LED array to obtain light intensity distribution data;

[0035] Based on the light intensity distribution data, the current light color temperature of the phosphor-free multi-primary color LED array is identified to obtain the LED array color temperature data;

[0036] The color rendering of the phosphor-free multi-primary LED array is analyzed to obtain the LED color rendering;

[0037] The optical characteristic parameters of the LED array color temperature data and LED color rendering are calculated to generate the current LED optical characteristic parameters.

[0038] The present invention uses a light intensity distribution calculation system to understand the illumination distribution of a phosphor-free multi-primary color LED array in space, and provides basic data support for subsequent light source characteristic analysis. The light intensity distribution data obtained helps the system to quantitatively describe the illumination intensity distribution of the LED array, and provides a data basis for color temperature recognition and color rendering analysis. The illumination color temperature recognition helps the system to determine the color temperature characteristics of the current LED array, and provides important information for subsequent optical characteristic parameter calculation. The LED array color temperature data system obtains to understand the color temperature properties of the LED light source, and provides a basis for light source adjustment and color rendering analysis. The color rendering analysis helps the system evaluate the color restoration ability of the LED array when illuminating an object, and provides an important reference for light source quality evaluation. The LED color rendering data obtained helps the system understand the color restoration effect of the LED array, and provides a basis for optical characteristic parameter calculation and light source adjustment. The optical characteristic parameter calculation combines color temperature data and color rendering analysis, provides the system with an optical characteristic description of the LED array, provides key parameters for light source adjustment control, and generates the current LED optical characteristic parameter system. The system has a deep understanding of the optical performance of the LED array, and provides important data support for the adaptive adjustment control of the LED light source.

[0039] Preferably, the dynamic color temperature adjustment module is specifically used for:

[0040] Perform LED structure distribution analysis on phosphor-free multi-primary color LED arrays and identify LED array layout structure data;

[0041] According to the light intensity distribution data, nonlinear correlation analysis between LED brightness is performed on the LED array layout structure data to obtain nonlinear data between array structure brightness;

[0042] Reconstruct the light source spectrum based on the nonlinear data between the brightness of the array structure, and construct the light source reconstruction spectrum;

[0043] The output color temperature of the reconstructed spectrum of the light source is dynamically adjusted to obtain dynamically adjusted light source color temperature parameters.

[0044] The present invention understands the layout structure of the LED array, including the arrangement mode and spatial distribution of LEDs, through the LED structure distribution analysis system, provides basic data support for subsequent optical characteristic analysis, identifies the LED array layout structure data to help the system accurately describe the position and quantity relationship of LEDs, and provides a basis for light source brightness distribution analysis. The LED brightness nonlinear correlation analysis system explores the nonlinear relationship between the brightness of LEDs, provides more precise control for light source brightness adjustment, obtains the array structure brightness nonlinear data to help the system understand the complex correlation between LED brightness, and provides a basis for light source spectrum reconstruction. The light source spectrum reconstruction assistance system reconstructs the spectral characteristics of the light source according to the structure and brightness data of the LED array, improves the color expression ability of the light source, constructs a light source reconstruction spectrum system to accurately describe the spectral characteristics of the LED light source, and provides a basis for dynamic color temperature adjustment and light source brightness control. The output color temperature dynamic adjustment assistance system realizes dynamic adjustment of color temperature according to the light source reconstruction spectrum to adapt to the lighting needs of different scenes, and obtains a dynamic adjustment light source color temperature parameter system to realize dynamic adjustment of LED light source color temperature according to actual needs, thereby improving the flexibility and adaptability of lighting effects.

[0045] Preferably, the error compensation module is specifically used for:

[0046] According to the optimal light source requirement characteristic data, the target light source error is calculated for the dynamically adjusted light source color temperature parameter to obtain the light source error parameter;

[0047] Performing error compensation adjustment on the dynamically adjusted light source color temperature parameter according to the light source error parameter, thereby generating a light source error compensation adjustment parameter;

[0048] The light source error compensation adjustment parameters are used to control the light source output of the phosphor-free multi-primary color LED array and obtain the dynamic response data of the light source.

[0049] The present invention calculates the target light source error, and the system evaluates the deviation between the color temperature parameters of the actual light source and the expected light source, providing a basis for subsequent error compensation adjustment, and obtaining the light source error parameters to help the system quantitatively describe the error situation of the light source, and provide a correction direction for the light source output control processing. The error compensation adjustment helps the system to adjust the light source color temperature parameters according to the light source error parameters to reduce or eliminate the light source error and improve the color performance consistency of the light source. The light source error compensation adjustment parameter generation system can realize fine adjustment of the light source according to the error situation and improve the accuracy and stability of the light source output. The light source output control processing helps the system to realize dynamic adjustment and control of the LED light source according to the error compensation adjustment parameters to meet the lighting requirements in different scenes. The light source dynamic response data acquisition system monitors the output of the LED light source in real time, and provides real-time feedback and adjustment basis for the adaptive adjustment control of the light source.

[0050] Preferably, the specific steps of calculating the target light source error for the dynamically adjusted light source color temperature parameter according to the optimal light source requirement characteristic data to obtain the light source error parameter are:

[0051] Calculating the light source parameter deviation of the dynamically adjusted light source color temperature parameter according to the optimal light source requirement characteristic data to obtain a target parameter deviation value; the target parameter deviation value includes a color temperature deviation value and a spectrum offset value;

[0052] Perform error superposition correlation analysis on color temperature deviation values ​​and spectrum shift values ​​to obtain error correlation data;

[0053] Performing iterative error calculation based on the error correlation data to obtain multiple light source error values;

[0054] Perform error range statistics on multiple light source error values ​​to obtain the error range;

[0055] A comprehensive light source error calculation is performed on the error range to obtain the light source error parameters.

[0056] The present invention helps the system evaluate the difference between actual light source parameters and optimal light source requirements, including color temperature deviation and spectral shift, through light source parameter deviation calculation, so as to provide basic data support for subsequent error analysis, obtain target parameter deviation value, and the system quantitatively describes the deviation of light source parameters, so as to provide a basis for error correlation analysis. The error superposition correlation analysis system comprehensively considers the relationship between color temperature deviation and spectral shift, so as to provide more comprehensive data support for subsequent error calculation, and obtains error correlation data to help the system understand the degree of correlation between parameter deviations, so as to provide a reference for iterative error calculation. The iterative error calculation helps the system gradually adjust the light source parameters according to the error correlation data, so as to reduce the light source error, improve the color consistency and stability of the light source, obtain multiple light source error value systems, optimize the light source error multiple times, and improve the precision and accuracy of the light source parameters. The error range statistics help the system evaluate the fluctuation range of the light source error, so as to provide a reference basis for subsequent error control, ensure the stability of the light source parameters, and obtain the error range system to understand the variation range of the light source error, so as to provide data support for comprehensive light source error calculation.

[0057] Preferably, the adaptive control module is specifically used for:

[0058] Calculating the response delay of the light source dynamic response data to obtain the light source response delay data;

[0059] Based on the light source response delay data, the light source error compensation adjustment parameters are dynamically optimized to generate response performance optimization parameters;

[0060] Calculate the driving current requirement of each LED for the response performance optimization parameter to obtain the LED adjustment driving current requirement data;

[0061] The LED drive current demand data is used to perform adaptive parameter fine-tuning optimization on the phosphor-free multi-primary color LED array, and an adaptive light source dynamic control strategy is constructed to perform LED light source control operations.

[0062] The present invention helps the system evaluate the speed and delay of the light source response through response delay calculation, provides a time parameter reference for subsequent dynamic adjustment, obtains the light source response delay data system to understand the light source response characteristics, and provides basic data support for response performance optimization. The dynamic response performance optimization helps the system adjust the error compensation adjustment parameters according to the light source response delay data, improves the system's adaptability to dynamic changes in the light source, generates a response performance optimization parameter system to achieve fine adjustment of the light source error compensation adjustment parameters, and improves the system's response speed and stability. The LED drive current demand calculation helps the system determine the drive current demand of each LED according to the response performance optimization parameters, and achieves precise control of the LED brightness. The LED adjustment drive current demand data system understands the specific requirements of the LED drive, and provides a basis for subsequent control strategy optimization. The adaptive parameter fine-tuning optimization helps the system to fine-tune the LED array according to the LED adjustment drive current demand data, improves the color performance and energy efficiency of the light source, and constructs an adaptive light source dynamic control strategy system to adjust the parameters of the LED light source according to real-time needs, and achieves more intelligent and efficient light source control operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 The present invention is a schematic diagram of an embodiment of a light source control system for adaptively adjusting a multi-primary color LED without phosphor. DETAILED DESCRIPTION

[0064] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0065] The example of this application provides a light source control system for adaptive adjustment of multi-primary color LEDs without phosphors. The execution subject of the light source control system for adaptive adjustment of multi-primary color LEDs without phosphors includes but is not limited to: mechanical equipment, data processing platform, cloud server node, network upload device, etc. equipped with the system can be regarded as the general computing node of this application, and the data processing platform includes but is not limited to: at least one of an audio and image management system, an information management system, and a cloud data management system.

[0066] See also Figure 1 As shown, the present invention provides a light source control system for adaptively adjusting multi-primary color LEDs without phosphors, and the light source control system for adaptively adjusting multi-primary color LEDs without phosphors includes:

[0067] The spectrum distribution module is used to obtain the multi-dimensional light data of the environment and the LED scene map; the spectrum distribution characteristics of the multi-dimensional light data of the environment are mined to construct the spectrum distribution map of the environment;

[0068] The optimal demand module is used to perform optimal demand analysis on the environmental spectrum distribution map based on the LED scene map to obtain the optimal light source demand characteristic data;

[0069] The optical characteristic module is used to identify the current illumination color temperature of the phosphor-free multi-primary color LED array to obtain the LED array color temperature data; and to generate the current LED optical characteristic parameters based on the LED array color temperature data;

[0070] A dynamic color temperature adjustment module is used to dynamically adjust the output color temperature of the current LED optical characteristic parameters based on the phosphor-free multi-primary color LED array to obtain dynamically adjusted light source color temperature parameters;

[0071] The error compensation module is used to perform error compensation adjustment on the color temperature parameters of the dynamically adjusted light source according to the optimal light source demand characteristic data, thereby generating light source error compensation adjustment parameters; perform light source output control processing based on the light source error compensation adjustment parameters, and obtain light source dynamic response data;

[0072] The adaptive control module is used to calculate the driving current demand of each LED one by one based on the dynamic response data of the light source to obtain the LED adjustment driving current demand data; based on the LED adjustment driving current demand data, the adaptive parameter fine-tuning optimization is performed to construct an adaptive light source dynamic control strategy to execute the LED light source control operation.

[0073] The present invention comprehensively understands the ambient lighting conditions by analyzing the spectral distribution characteristics of the ambient multi-dimensional light data, provides data support for subsequent light source adjustment, constructs an ambient spectral distribution diagram to help the system better simulate the real lighting environment, provides a basic reference for LED light source adjustment, and determines the goal and direction of LED light source adjustment through optimal demand analysis, thereby improving the degree of optimization of the lighting effect and meeting the needs of specific scenes. The optimal light source demand characteristic data is obtained to help the system set appropriate light source parameters, thereby improving the efficiency and accuracy of LED light source adjustment. Through color temperature recognition and acquisition of optical characteristic parameters, the system accurately understands the performance and characteristics of the current LED light source, provides basic data for subsequent light source adjustment, generates the current LED optical characteristic parameter system, performs dynamic adjustment according to actual conditions, improves the adaptability and flexibility of the LED light source, and dynamically adjusts the light source color temperature parameters according to real-time The color temperature of the LED light source can be flexibly adjusted according to the needs to adapt to the lighting requirements of different scenes, and the adaptability and practicality of the light source can be improved. The error compensation adjustment can improve the accuracy and stability of the LED light source adjustment, reduce the impact of errors on the lighting effect, and improve the overall adjustment effect. The dynamic response data of the light source is obtained to help the system monitor the status and performance changes of the LED light source in real time, provide real-time feedback for dynamic control, calculate the specific driving parameters of each LED by the LED drive current demand, and realize fine control and adjustment of the LED light source. The adaptive parameter fine-tuning optimization and dynamic control strategy construction dynamically adjusts the parameters of the LED light source according to the real-time data and needs, making the control of the LED light source more intelligent and efficient. The LED light source control operation is executed to ensure that the LED light source is dynamically adjusted according to the set parameters and strategies to achieve the best balance between lighting effect and energy efficiency.

[0074] In the embodiment of the present invention, refer to Figure 1 , is a schematic diagram of an embodiment of a fluorescent powder-free multi-primary color LED adaptively adjustable light source control system of the present invention. In this example, the fluorescent powder-free multi-primary color LED adaptively adjustable light source control system includes:

[0075] The spectrum distribution module is used to obtain the multi-dimensional light data of the environment and the LED scene map; the spectrum distribution characteristics of the multi-dimensional light data of the environment are mined to construct the spectrum distribution map of the environment;

[0076] In this embodiment, a high-performance spectral sensor is used to collect spectrum covering a wide range of visible light, infrared, ultraviolet, etc., and multiple collection points are set in the target LED scene to obtain spatially distributed multidimensional light data. Environmental factor information such as temperature, humidity, and obstructions are recorded during the collection process. A high-definition camera is used to capture a panoramic image of the target LED scene, and the image contains information such as the position, quantity, and shape of LED lamps. Combined with the position information of the multidimensional light data collection point in the scene, a spectral analysis algorithm such as Fourier transform and principal component analysis is used to extract the spectral distribution characteristics of the multidimensional light data, analyze the spectral distribution differences of different collection points, and explore the spatial variation law of the spectral distribution. Combined with the LED scene image information, the correlation between the spectral distribution and the layout and parameters of the LED lamps is identified. According to the spectral distribution characteristics and combined with the LED scene map, an environmental spectral distribution map is constructed. The spectral distribution conditions of different areas in the environment are intuitively displayed using visualization methods such as heat maps and contour maps. For characteristic areas, corresponding data annotations are added, such as spectral peaks, main bands, and other information to form a complete environmental spectral distribution map, which provides a reference for subsequent lighting optimization, energy consumption management, etc.

[0077] The optimal demand module is used to perform optimal demand analysis on the environmental spectrum distribution map based on the LED scene map to obtain the optimal light source demand characteristic data;

[0078] In this embodiment, in combination with the multi-dimensional light data of the environment, an environmental spectral distribution map is superimposed on the LED scene image, the spectral distribution of different areas is analyzed, the areas with uneven spectral distribution are identified, and the lighting indicators of these areas, such as illuminance, color temperature, color rendering, etc., are evaluated and compared with the standard requirements. For the areas with uneven spectral distribution, the lighting indicators that need to be optimized are determined, such as increasing the illumination, adjusting the color temperature, etc. According to these optimization goals, light source selection algorithms, such as genetic algorithms and particle swarm optimization, are used to find the optimal LED light source parameters that meet the requirements. The optimization parameters include the color temperature, power, luminous flux, color rendering index, etc. of the LED light source, as well as the optimal position and quantity.

[0079] The optical characteristic module is used to identify the current illumination color temperature of the phosphor-free multi-primary color LED array to obtain the LED array color temperature data; and to generate the current LED optical characteristic parameters based on the LED array color temperature data;

[0080] In this embodiment, a color temperature calculation algorithm, such as the Planckian radiation method, the CIE chromaticity coordinate method, etc., is used to calculate the color temperature value of the LED array based on the spectral data, and the color temperature values ​​of different regions are statistically analyzed to identify the color temperature distribution characteristics of the LED array. In combination with the geometric size information of the LED array, a color temperature distribution diagram of the LED array is constructed. Based on the color temperature distribution information of the LED array and the driving parameters, the optical characteristic parameters such as the luminous flux and luminous efficiency of each LED element are calculated. Using optical simulation software, such as LightTools and TracePro, an optical model of the LED array is established, the identified LED optical characteristic parameters are imported into the model, and the simulation results are calibrated to determine the degree of fit with the measured data.

[0081] A dynamic color temperature adjustment module is used to dynamically adjust the output color temperature of the current LED optical characteristic parameters based on the phosphor-free multi-primary color LED array to obtain dynamically adjusted light source color temperature parameters;

[0082] In this embodiment, a color temperature adjustment method based on an optimization algorithm, such as nonlinear programming, genetic algorithm, etc., is adopted. According to the target color temperature requirements, the optimal driving parameters of the LED array are calculated. The target color temperature is a fixed value and also changes dynamically, such as simulating natural light changes. The adjustment algorithm needs to consider factors such as the light decay characteristics of the LED array and the color temperature stability to ensure the reliability of the adjustment effect. A microcontroller-based LED driving circuit is designed, which can collect the working parameters of the LED array in real time and adjust the driving output according to the color temperature dynamic adjustment algorithm. The adjustment algorithm is embedded in the firmware of the driving circuit to realize automatic dynamic adjustment of the color temperature of the LED array. The optical characteristic parameter changes of the LED array are regularly detected, and the algorithm model is updated to ensure continuous optimization of the adjustment effect.

[0083] The error compensation module is used to perform error compensation adjustment on the color temperature parameters of the dynamically adjusted light source according to the optimal light source demand characteristic data, thereby generating light source error compensation adjustment parameters; perform light source output control processing based on the light source error compensation adjustment parameters, and obtain light source dynamic response data;

[0084] In this embodiment, the color temperature data obtained by the LED array during the dynamic adjustment process is compared and analyzed with the color temperature reference data of the optimal light source, and an adaptive adjustment algorithm, such as PID control, fuzzy logic, etc., is used to calculate the compensation amount of the color temperature error, and the driving parameters of the LED array are adjusted according to the compensation amount so that its output color temperature approaches the color temperature characteristics of the optimal light source. A mapping relationship model between the color temperature of the LED array and the driving parameters is established, and the color temperature error compensation amount is converted into a specific driving parameter. The color temperature error compensation under different working conditions is integrated to form a comprehensive light source error compensation adjustment parameter, and the light source error compensation adjustment parameter is saved in a database for subsequent light source output control. A fast spectrometer and other equipment are used to measure the dynamic light output response of the LED array after the error compensation adjustment, and the spectral data, color coordinate changes, etc. of the LED array during the color temperature switching, brightness change, etc. are recorded. The dynamic characteristics of the LED array, such as the response time and stability, are analyzed, and the effectiveness of the error compensation adjustment is evaluated.

[0085] The adaptive control module is used to calculate the driving current demand of each LED one by one based on the dynamic response data of the light source to obtain the LED adjustment driving current demand data; based on the LED adjustment driving current demand data, the adaptive parameter fine-tuning optimization is performed to construct an adaptive light source dynamic control strategy to execute the LED light source control operation.

[0086] In this embodiment, the dynamic response test data of the light source is analyzed, including the light output characteristics and color temperature changes of the LED array under different working conditions. For each LED unit, the required adjustment driving current is calculated according to the target light output characteristics and the current actual output, and a mapping relationship model between the driving current of the LED unit and the light output characteristics is established to provide a basis for subsequent adaptive control. An optimization algorithm, such as a genetic algorithm, a particle swarm optimization, etc., is used to iteratively optimize the LED driving current demand data. The optimization goal is to minimize the error between the actual output of the LED array and the target light output characteristics. At the same time, the power consumption factor is considered. By fine-tuning the parameters, an LED driving current setting value that meets the light output requirements and has the best power consumption is obtained. A light output characteristic prediction model based on the LED driving current is established, and the optimized current setting value is associated with the expected light output characteristics. The prediction model is integrated into the LED driving control system to form an adaptive light source dynamic control strategy. The control strategy includes: real-time adjustment of LED driving current, color temperature / brightness closed-loop control, dynamic response compensation and other functions. The optimized adaptive light source dynamic control strategy is integrated into the LED driving control system to form an integrated solution.

[0087] In this embodiment, the spectrum distribution module is specifically used for:

[0088] Identify the multi-dimensional light data of the environment based on the sensor; obtain the current LED scene map;

[0089] Calculate the light intensity of the environment multi-dimensional light data to obtain the value of the environment light intensity;

[0090] Perform time series change analysis on the multi-dimensional ambient light data to generate ambient light time series change data;

[0091] According to the ambient light intensity value, the light intensity fluctuation trend of the ambient light time series change data is analyzed to construct the ambient light intensity change curve;

[0092] The spectral distribution features are mined based on the ambient light intensity change curve to construct an ambient spectral distribution map.

[0093] In this embodiment, a multi-spectral sensor is used to collect multi-dimensional light data in the environment, including parameters such as light intensity, color temperature, and spectrum. The sensor data is calibrated and calibrated to ensure the accuracy and reliability of the data. A data acquisition system is established to record the dynamic changes of ambient light in real time. A camera and other equipment are used to capture a scene diagram of the distribution of LED light sources in the environment. The total light intensity value in the environment is calculated based on the collected multi-dimensional light data. The light intensity calculation formula is: E=ΣEi, where Ei is the light intensity of each spectral band. The calculated ambient light intensity value is stored in a database to provide a basis for subsequent analysis. The recorded ambient light intensity time series data is analyzed to extract the change trend of light intensity. Time series analysis methods such as Fourier transform and small wavelet transform are used. Wave analysis, etc., conduct frequency domain and time domain analysis on the light intensity change, generate the ambient light intensity time series change curve, describe the dynamic change characteristics of light intensity in the time dimension, combine with the ambient light intensity value, analyze the time series change curve, extract the fluctuation trend of light intensity, identify the periodic change and sudden change of light intensity, and quantitatively describe it, construct the ambient light intensity change curve, characterize the fluctuation characteristics of light intensity over time, based on the ambient light intensity change curve, further analyze the characteristics of spectral distribution, extract spectral distribution data at different time points, draw the ambient spectral distribution diagram, analyze the peak position, half-peak width, relative intensity and other parameters of spectral distribution, characterize the dynamic change of spectrum, associate the spectral distribution characteristics with the light intensity change trend, and reveal the dynamic evolution law of ambient spectrum.

[0094] In this embodiment, the specific steps of mining spectral distribution features based on the ambient light intensity variation curve to construct an ambient spectral distribution map are as follows:

[0095] Based on the ambient light intensity change curve, the light source type is identified for the ambient multi-dimensional light data, thereby obtaining the ambient light source type;

[0096] Perform light source color temperature analysis based on the ambient light source type to obtain the ambient light source color temperature value;

[0097] Perform multi-band decomposition on the multi-dimensional light data of the environment to generate light intensity information of different frequencies;

[0098] Performing spectral intensity calculation on light intensity information of different frequencies to generate a spectral intensity curve;

[0099] Perform spectral morphology fitting on the spectral intensity curve based on the color temperature value of the ambient light source to generate spectral distribution morphology parameters;

[0100] The morphological characteristics of the spectral distribution morphological parameters are mined to construct the environmental spectral distribution map.

[0101] In this embodiment, the characteristics of the ambient light intensity change curve, including the fluctuation frequency, amplitude, duration, etc., are analyzed. According to the typical characteristics of the light source, such as incandescent lamp, fluorescent lamp, LED, etc., a light source type recognition model is established. The ambient light intensity change curve is associated with the light source type by using machine learning or pattern matching methods to identify the light source type in the current environment. In combination with the identified light source type, relevant standards or references are consulted to obtain the color temperature ranges of different types of light sources. The spectral distribution characteristics in the ambient multidimensional light data are analyzed. In combination with the light source type information, the color temperature value of the current ambient light source is estimated. The color measurement or spectrophotometry method is used to directly measure the color temperature parameters of the light source in the environment to improve the accuracy of the analysis. The collected ambient multidimensional light data is subjected to frequency decomposition to extract light intensity information in different frequency ranges. Signal processing methods such as Fourier transform and wavelet transform are used to divide the light intensity data into different frequency bands. For each frequency band, the corresponding light intensity value is calculated to form light intensity values ​​at different frequencies. Strong information, according to the multi-band light intensity information, draw the spectral intensity curve, the horizontal axis of the spectral intensity curve is the spectral wavelength, and the vertical axis is the light intensity value of the corresponding wavelength. Through interpolation or spectral reconstruction methods, fill in the missing data points in the spectral curve to make the curve smoother. Combined with the color temperature value of the ambient light source, select a suitable spectral distribution model for curve fitting. Commonly used spectral distribution models include blackbody radiation model, Gaussian distribution model, etc., and estimate the parameters of the spectral distribution model, such as peak value, half-peak width, shape coefficient, etc. through the least squares method or other optimization algorithms. Use the information such as light source type, color temperature value, spectral morphology parameters, etc. to draw the ambient spectral distribution map. The horizontal axis of the spectral distribution map is the spectral wavelength, and the vertical axis is the light intensity value. Different light intensity levels are represented by color coding. Combined with 3D scene data, the spectral distribution information is mapped to the spatial model to display the spatial characteristics of the spectral distribution in the environment. The uniformity and correlation of the spectral distribution can be further analyzed to provide a reference for the design and optimization of the lighting system.

[0102] In this embodiment, the optimal demand module is specifically used for:

[0103] Perform visual feature analysis on the LED scene graph to obtain scene visual features;

[0104] Calculate the dynamic color temperature range of the ambient spectrum distribution diagram to obtain the dynamic color temperature range of the scene;

[0105] Calculate the optimal color temperature and brightness of the scene dynamic color temperature range based on the scene visual characteristics to generate the optimal color temperature and brightness of the scene;

[0106] Perform optimal demand analysis on the best color temperature and brightness of the scene to obtain the optimal light source demand characteristic data.

[0107] In this embodiment, a 3D model or 2D image data of an LED scene is obtained to represent the light source distribution and lighting conditions in the environment. Computer vision and image processing technology are used to extract and analyze features of the LED scene graph, extract visual features such as key points, edges, textures, and colors in the scene, and describe the geometric structure and visual style of the scene. Machine learning or deep learning models are used to classify and identify visual features to obtain semantic labels and attribute information of the scene. The extracted visual features of the scene are stored in a database to provide a basis for subsequent calculation of the optimal color temperature and brightness. Combined with the aforementioned constructed environmental spectral distribution map, the dynamic change characteristics of the spectral distribution are analyzed, and the corresponding color temperature value range is calculated for different areas of the spectral distribution map. The color temperature change range of the scene at different time points is obtained through time series analysis, and the dynamic color temperature range data of the scene is recorded in the database to provide the optimal color temperature and brightness. The calculation provides input, combines the scene visual characteristics and dynamic color temperature range information, establishes a correlation model of suitable color temperature and brightness for the scene, considers factors such as human visual comfort and object color restoration, determines the best color temperature and brightness parameters in the scene, and uses an optimization algorithm to find the color temperature and brightness combination that makes the scene visually optimal. The calculated optimal color temperature and brightness parameters are stored in the database to provide input for subsequent optimal light source demand analysis. Combined with the optimal color temperature and brightness parameters of the scene, the light source product database is queried to find the light source type that meets the demand, analyzes the light source's spectral distribution, color temperature adjustment range, luminous flux and other parameters, and evaluates whether it can meet the scene requirements. For different areas, select appropriate light sources for matching, build the optimal lighting system solution, and record the characteristic data of the optimal light source requirements, such as light source type, color temperature range, luminous flux, etc., in the database to provide a reference for lighting design.

[0108] In this embodiment, the optical property module is specifically used for:

[0109] Calculating the light intensity distribution of the phosphor-free multi-primary color LED array to obtain light intensity distribution data;

[0110] Based on the light intensity distribution data, the current light color temperature of the phosphor-free multi-primary color LED array is identified to obtain the LED array color temperature data;

[0111] The color rendering of the phosphor-free multi-primary LED array is analyzed to obtain the LED color rendering;

[0112] The optical characteristic parameters of the LED array color temperature data and LED color rendering are calculated to generate the current LED optical characteristic parameters.

[0113] In this embodiment, a 3D model of a phosphor-free multi-primary color LED array is obtained, and an optical simulation model of the LED array is established, including the geometric dimensions, optical path parameters, and installation positions of the light-emitting diodes. A ray tracing or finite element method is used to perform numerical simulation calculations on the light intensity distribution of the LED array. Factors such as the directivity and light decay characteristics of the LED light source are considered to obtain light intensity distribution data of the LED array in different regions. A color perception model, such as the CIE1931 chromaticity diagram, is used to calculate the color coordinates of each region based on the light intensity distribution data. The color coordinates are mapped to a color temperature trajectory to determine the corresponding correlated color temperature value. The color temperature values ​​of different regions of the LED array are analyzed to obtain the overall color temperature distribution characteristics. The identified LED array color temperature data is recorded in a database to provide data support for subsequent color rendering analysis, and the spectral distribution data of the LED light source is obtained. Combined with the visual characteristic model of the CIE standard observer, the color difference of the LED light source under different color rendering index (CRI) test color samples is calculated to obtain the overall color rendering index. The color rendering performance of the LED light source under specific directions and positions is further analyzed to obtain local color rendering data. The overall and local color rendering data of the LED array are recorded in the database to provide a basis for the calculation of optical characteristic parameters. Combined with the aforementioned LED array color temperature data and color rendering data, an association model of LED optical characteristic parameters is established. Considering factors such as human eye visual comfort and object color reproduction, the optimal color temperature and color rendering parameters of the LED light source are determined. For different areas, appropriate LED light sources are selected for matching to build the optimal lighting system solution. The calculated LED optical characteristic parameters, such as color temperature range, color rendering index, luminous flux, etc., are stored in the database.

[0114] In this embodiment, the dynamic color temperature adjustment module is specifically used for:

[0115] Perform LED structure distribution analysis on phosphor-free multi-primary color LED arrays and identify LED array layout structure data;

[0116] According to the light intensity distribution data, nonlinear correlation analysis between LED brightness is performed on the LED array layout structure data to obtain nonlinear data between array structure brightness;

[0117] Reconstruct the light source spectrum based on the nonlinear data between the brightness of the array structure, and construct the light source reconstruction spectrum;

[0118] The output color temperature of the reconstructed spectrum of the light source is dynamically adjusted to obtain dynamically adjusted light source color temperature parameters.

[0119] In this embodiment, a 3D model or disassembly data of an LED array is obtained, the geometric position and arrangement of each LED light source are determined, a topological structure model of the LED array is established, the mutual relationship and layout characteristics between each LED light source are described, and layout information such as the position and arrangement of each LED light source is extracted from the measured data of the LED array by using techniques such as image processing or machine learning. The extracted LED array layout structure data is stored in a database to provide a basis for subsequent brightness correlation analysis. Combined with the aforementioned light intensity distribution calculation data, the brightness coupling relationship between each LED light source is analyzed, and factors such as optical interference and thermal coupling between LED light sources are considered to establish a nonlinear mathematical model of LED array brightness. Using an optimization algorithm or a machine learning method, the nonlinear correlation data between the brightness of each LED light source in the LED array structure is fitted. Using the optimization algorithm, according to the structural layout of the LED array and the nonlinear data between the brightness, the LED light source spectrum that meets the target spectral characteristics is reconstructed. Considering factors such as the light decay characteristics of the LED light source and the influence of the optical path, a stable and reliable LED light source reconstructed spectrum is further optimized, the real-time light intensity distribution and color temperature distribution data of the LED array are monitored, the current optical characteristic parameters are obtained, and according to the expected color temperature adjustment target, the brightness distribution of each area of ​​the LED array is adjusted using the optimization algorithm. Combined with the aforementioned LED light source reconstruction spectrum data, the LED light source spectrum that meets the color temperature adjustment target is dynamically reconstructed.

[0120] In this embodiment, the error compensation module is specifically used for:

[0121] According to the optimal light source requirement characteristic data, the target light source error is calculated for the dynamically adjusted light source color temperature parameter to obtain the light source error parameter;

[0122] Performing error compensation adjustment on the dynamically adjusted light source color temperature parameter according to the light source error parameter, thereby generating a light source error compensation adjustment parameter;

[0123] The light source error compensation adjustment parameters are used to control the light source output of the phosphor-free multi-primary color LED array and obtain the dynamic response data of the light source.

[0124] In this embodiment, based on the optimal light source requirement characteristic data of the application scenario, such as color temperature, color rendering index, etc., the deviation between the current LED light source output and the target light source is calculated, the target light source error parameters are read, the error characteristics of the LED light source output are analyzed, a mathematical mapping relationship between the LED light source output and the target light source characteristics is established, the error compensation adjustment strategy is determined, and the LED light source adjustment parameters that can compensate for the target light source error are calculated using an optimization algorithm or an intelligent control method. The light source error compensation adjustment parameters are read, and the driving current, PWM control, etc. of the LED array are adjusted in real time. The optical response data of the LED array such as the light intensity distribution and color temperature distribution during the dynamic adjustment process are collected, and the sensor feedback mechanism is used to continuously optimize the output control of the LED light source until the target light source characteristic requirements are met.

[0125] In this embodiment, the specific steps of calculating the target light source error for the dynamically adjusted light source color temperature parameter according to the optimal light source requirement characteristic data to obtain the light source error parameter are:

[0126] Calculating the light source parameter deviation of the dynamically adjusted light source color temperature parameter according to the optimal light source requirement characteristic data to obtain a target parameter deviation value; the target parameter deviation value includes a color temperature deviation value and a spectrum offset value;

[0127] Perform error superposition correlation analysis on color temperature deviation values ​​and spectrum shift values ​​to obtain error correlation data;

[0128] Performing iterative error calculation based on the error correlation data to obtain multiple light source error values;

[0129] Perform error range statistics on multiple light source error values ​​to obtain the error range;

[0130] A comprehensive light source error calculation is performed on the error range to obtain the light source error parameters.

[0131] In this embodiment, the dynamically adjusted light source color temperature parameters are compared with the target light source requirements, and the color temperature deviation value and the spectral offset value between the two are calculated to obtain the target parameter deviation value. The correlation and coupling relationship between the color temperature deviation value and the spectral offset value are analyzed, and a mathematical model between the color temperature deviation value and the spectral offset value is established to describe their coupling relationship. An iterative optimization algorithm is used to calculate multiple light source error values, including color temperature error values, spectral error values, etc. The statistical distribution characteristics of these error values ​​are analyzed, the upper and lower limits of the light source error are determined, and the color temperature error, spectral error and other factors are comprehensively considered to calculate the final light source error parameters.

[0132] In this embodiment, the adaptive control module is specifically used for:

[0133] Calculating the response delay of the light source dynamic response data to obtain the light source response delay data;

[0134] Based on the light source response delay data, the light source error compensation adjustment parameters are dynamically optimized to generate response performance optimization parameters;

[0135] Calculate the driving current requirement of each LED for the response performance optimization parameter to obtain the LED adjustment driving current requirement data;

[0136] The LED drive current demand data is used to perform adaptive parameter fine-tuning optimization on the phosphor-free multi-primary color LED array, and an adaptive light source dynamic control strategy is constructed to perform LED light source control operations.

[0137] In this embodiment, a photoelectric sensor or other measuring equipment is used to collect dynamic response data of the LED light source in real time, including changes in parameters such as luminous flux and color temperature. The collected dynamic response data is analyzed, and the delay time of the LED light source in responding to changes in the target parameters is calculated to obtain light source response delay data. According to different application scenarios, in combination with human visual characteristics, reasonable light source response time requirements are determined. An optimization algorithm is used to calculate the optimal value of the light source error compensation adjustment parameter, that is, the response performance optimization parameter, according to the light source response delay data and the target response time requirements. In combination with the electrical characteristic model of the LED light source, for each lamp bead of the phosphor-free multi-primary LED array, the required driving current value of each LED unit is calculated to obtain LED adjustment driving current demand data. According to the current demand value of each LED unit, the driving circuit of the LED array is adaptively parameterized according to the current demand value of each LED unit, the output characteristics of the LED light source are optimized, and a dynamic control strategy of the LED light source based on adaptive parameter fine-tuning is constructed to perform real-time LED light source control operations. According to real-time environmental requirements and feedback information, the color temperature parameters and brightness of the LED are adjusted to achieve the best lighting effect and energy efficiency.

[0138] The above is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A light source control system with adaptive adjustment of multi-primary color LED without phosphor, characterized in that: The light source control system for adaptively adjusting the non-phosphor multi-primary color LED comprises a non-phosphor multi-primary color LED array, a spectrum distribution module, an optimal demand module, an optical characteristic module, a dynamic color temperature adjustment module, an error compensation module and an adaptive control module; The spectrum distribution module is used to obtain the multi-dimensional light data of the environment and the LED scene map; the spectrum distribution characteristics of the multi-dimensional light data of the environment are mined to construct the spectrum distribution map of the environment; The optimal demand module is used to perform optimal demand analysis on the environmental spectrum distribution map based on the LED scene map to obtain the optimal light source demand characteristic data; The optical characteristic module is used to identify the current illumination color temperature of the phosphor-free multi-primary color LED array to obtain the LED array color temperature data; and to generate the current LED optical characteristic parameters based on the LED array color temperature data; A dynamic color temperature adjustment module is used to dynamically adjust the output color temperature of the current LED optical characteristic parameters based on the phosphor-free multi-primary color LED array to obtain dynamically adjusted light source color temperature parameters; The error compensation module is used to perform error compensation adjustment on the color temperature parameters of the dynamically adjusted light source according to the optimal light source demand characteristic data, thereby generating light source error compensation adjustment parameters; perform light source output control processing based on the light source error compensation adjustment parameters, and obtain light source dynamic response data; The adaptive control module is used to calculate the driving current demand of each LED one by one based on the dynamic response data of the light source to obtain the LED adjustment driving current demand data; Based on the LED adjustment driving current demand data, adaptive parameter fine-tuning optimization is performed to build an adaptive light source dynamic control strategy to perform LED light source control operations; The spectrum distribution module is specifically used for: Identify multi-dimensional light data of the environment based on sensors; obtain the current LED scene map; Calculate the light intensity of the environment multi-dimensional light data to obtain the value of the environment light intensity; Perform time series change analysis on the multi-dimensional ambient light data to generate ambient light time series change data; According to the ambient light intensity value, the light intensity fluctuation trend of the ambient light time series change data is analyzed to construct the ambient light intensity change curve; Mining the spectral distribution features based on the ambient light intensity change curve to construct an ambient spectral distribution map; The adaptive control module is specifically used for: Calculating the response delay of the light source dynamic response data to obtain the light source response delay data; Based on the light source response delay data, the light source error compensation adjustment parameters are dynamically optimized to generate response performance optimization parameters; Calculate the driving current requirement of each LED for the response performance optimization parameter to obtain the LED adjustment driving current requirement data; The LED drive current demand data is used to perform adaptive parameter fine-tuning optimization on the phosphor-free multi-primary color LED array, and an adaptive light source dynamic control strategy is constructed to perform LED light source control operations.

2. The light source control system for adaptive adjustment of multi-primary color LED without phosphor according to claim 1, characterized in that: The specific steps of mining the spectral distribution features based on the ambient light intensity variation curve to construct the ambient spectral distribution map are as follows: Based on the ambient light intensity change curve, the light source type is identified for the ambient multi-dimensional light data, thereby obtaining the ambient light source type; Perform light source color temperature analysis based on the ambient light source type to obtain the ambient light source color temperature value; Perform multi-band decomposition on the multi-dimensional light data of the environment to generate light intensity information of different frequencies; Performing spectral intensity calculation on light intensity information of different frequencies to generate a spectral intensity curve; Perform spectral morphology fitting on the spectral intensity curve based on the color temperature value of the ambient light source to generate spectral distribution morphology parameters; The morphological characteristics of the spectral distribution morphological parameters are mined to construct the environmental spectral distribution map.

3. The light source control system for adaptive adjustment of multi-primary color LED without phosphor according to claim 1, characterized in that: The optimal demand module is specifically used for: Perform visual feature analysis on the LED scene graph to obtain scene visual features; Calculate the dynamic color temperature range of the ambient spectrum distribution diagram to obtain the dynamic color temperature range of the scene; Calculate the optimal color temperature and brightness of the scene dynamic color temperature range based on the scene visual characteristics to generate the optimal color temperature and brightness of the scene; Perform optimal demand analysis on the best color temperature and brightness of the scene to obtain the optimal light source demand characteristic data.

4. The phosphor-free multi-primary color LED adaptive light source control system according to claim 1, characterized in that: The optical property module is specifically used for: Calculating the light intensity distribution of the phosphor-free multi-primary color LED array to obtain light intensity distribution data; Based on the light intensity distribution data, the current light color temperature of the phosphor-free multi-primary color LED array is identified to obtain the LED array color temperature data; The color rendering of the phosphor-free multi-primary LED array is analyzed to obtain the LED color rendering; The optical characteristic parameters of the LED array color temperature data and LED color rendering are calculated to generate the current LED optical characteristic parameters.

5. The phosphor-free multi-primary color LED adaptive light source control system according to claim 1, characterized in that: The dynamic color temperature adjustment module is specifically used for: Perform LED structure distribution analysis on phosphor-free multi-primary color LED arrays and identify LED array layout structure data; According to the light intensity distribution data, nonlinear correlation analysis between LED brightness is performed on the LED array layout structure data to obtain nonlinear data between array structure brightness; Reconstruct the light source spectrum based on the nonlinear data between the brightness of the array structure, and construct the light source reconstruction spectrum; The output color temperature of the reconstructed spectrum of the light source is dynamically adjusted to obtain dynamically adjusted light source color temperature parameters.

6. The phosphor-free multi-primary color LED adaptive light source control system according to claim 1, characterized in that: The error compensation module is specifically used for: According to the optimal light source requirement characteristic data, the target light source error is calculated for the dynamically adjusted light source color temperature parameter to obtain the light source error parameter; Performing error compensation adjustment on the dynamically adjusted light source color temperature parameter according to the light source error parameter, thereby generating a light source error compensation adjustment parameter; The light source error compensation adjustment parameters are used to control the light source output of the phosphor-free multi-primary color LED array and obtain the dynamic response data of the light source.

7. The phosphor-free multi-primary color LED adaptive light source control system according to claim 6, characterized in that: The specific steps of calculating the target light source error for dynamically adjusting the light source color temperature parameter according to the optimal light source requirement characteristic data to obtain the light source error parameter are: Calculating the light source parameter deviation of the dynamically adjusted light source color temperature parameter according to the optimal light source requirement characteristic data to obtain a target parameter deviation value; the target parameter deviation value includes a color temperature deviation value and a spectrum offset value; Perform error superposition correlation analysis on color temperature deviation values ​​and spectrum shift values ​​to obtain error correlation data; Performing iterative error calculation based on the error correlation data to obtain multiple light source error values; Perform error range statistics on multiple light source error values ​​to obtain the error range; A comprehensive light source error calculation is performed on the error range to obtain the light source error parameters.

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