Adaptive lighting method and system for combined LED lamps

Abstract

The present application provides an adaptive lighting method and system for combining LED lamps, and relates to the field of lighting technology. The method includes: obtaining the first and second lamp groups of LED lamps; collecting lighting data of the first lamp group, evaluating the lighting comfort impact, and obtaining a first impact index; setting a light sensor to obtain ambient light data; when the first impact index exceeds the standard, inputting the real-time lighting and ambient light data into an adaptive lighting control model, which optimizes the lighting parameters of the second lamp group and outputs control parameters for neutralizing lighting. The present application can solve the technical problem that the lighting system cannot provide the best lighting effect and energy efficiency due to the inability to monitor data in real time and adaptively control the existing technology, further affecting the user's work efficiency, comfort and overall lighting experience. It can dynamically respond to environmental changes, automatically adjust lighting conditions, and improve lighting comfort, energy efficiency and user satisfaction.

Description

Technical Field

[0001] The present application relates to the field of lighting technology, and in particular to an adaptive lighting method and system for combined LED lamps. Background Art

[0002] Adaptive lighting methods refer to technologies that automatically adjust the performance of lighting systems according to environmental conditions and user needs. In the field of LED lighting, this technology is particularly important because LED lamps have the characteristics of high energy efficiency, long life, good color stability and controllability. With the increasing global attention to energy conservation and emission reduction, the energy efficiency of lighting systems, as an important part of electricity consumption, has received widespread attention. LED lamps have become the first choice for energy-saving lighting due to their efficient energy conversion. Different application scenarios and different times require different light levels. For example, offices, hospitals, schools and other places have different lighting requirements than home lighting.

[0003] Currently, existing lighting systems may lack flexibility and intelligent adjustment capabilities, and are unable to automatically adjust lighting conditions according to environmental changes and user needs.

[0004] In summary, the existing technology cannot provide real-time data monitoring and adaptive control, resulting in the lighting system being unable to provide the best lighting effect and energy efficiency, further affecting the user's work efficiency, comfort and overall lighting experience. Summary of the invention

[0005] The purpose of this application is to provide an adaptive lighting method and system for combined LED lamps, so as to solve the technical problem that the prior art cannot provide the best lighting effect and energy efficiency due to the inability to monitor data in real time and adaptively control, further affecting the user's work efficiency, comfort and overall lighting experience.

[0006] In view of the above problems, the present application provides an adaptive lighting method and system for combined LED lamps.

[0007] In a first aspect, the present application provides an adaptive lighting method for a combination LED lamp, the method being implemented by an adaptive lighting system for a combination LED lamp, wherein the method comprises: obtaining a first LED lamp group and a second LED lamp group of the combination LED lamp, wherein the first LED lamp group is a lamp group arranged inside a lighting cavity, and the second LED lamp group is a lamp group arranged outside the lighting cavity; collecting a real-time lighting data set of the first LED lamp group; performing a strong lighting comfort impact assessment on the real-time lighting data set to obtain a first impact index; setting an external ambient light sensor, and obtaining an ambient light data set according to the external ambient light sensor; when the first impact index is greater than a preset impact index, inputting the real-time lighting data set and the ambient light data set into an adaptive lighting control model, wherein the adaptive lighting control model is connected to the second LED lamp group; the adaptive lighting control model optimizes the lighting parameters of the second LED lamp group with the preset impact index as an adaptive target, outputs the lighting control parameters, and controls the second LED lamp group to perform neutralizing lighting according to the lighting control parameters.

[0008] In a second aspect, the present application further provides an adaptive lighting system for a combined LED lamp, which is used to execute the adaptive lighting method for a combined LED lamp as described in the first aspect, wherein the system comprises: a lamp group acquisition module, the lamp group acquisition module is used to acquire a first LED lamp group and a second LED lamp group of the combined LED lamp, wherein the first LED lamp group is a lamp group arranged inside the lighting cavity, and the second LED lamp group is a lamp group arranged outside the lighting cavity; a lighting data set acquisition module, the lighting data set acquisition module is used to collect a real-time lighting data set of the first LED lamp group; an impact index acquisition module, the impact index acquisition module is used to perform a strong lighting comfort impact assessment on the real-time lighting data set to obtain a first impact index; and an ambient light A data acquisition module, the ambient light data acquisition module is used to set an external ambient light sensor and acquire an ambient light data set according to the external ambient light sensor; a data processing module, the data processing module is used to input the real-time lighting data set and the ambient light data set into an adaptive lighting control model when the first influencing index is greater than a preset influencing index, wherein the adaptive lighting control model is connected to the second LED light group; a control lighting parameter output module, the control lighting parameter output module is used for the adaptive lighting control model to optimize the lighting parameters of the second LED light group with the preset influencing index as the adaptive target, output lighting control parameters, and control the second LED light group to perform neutral lighting according to the lighting control parameters.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] By acquiring a first LED light group and a second LED light group of a combined LED lamp, wherein the first LED light group is a light group arranged inside the lighting cavity, and the second LED light group is a light group arranged outside the lighting cavity; collecting a real-time lighting data set of the first LED light group; performing a strong lighting comfort impact assessment on the real-time lighting data set to obtain a first impact index; setting an external ambient light sensor, and obtaining an ambient light data set according to the external ambient light sensor; when the first impact index is greater than a preset impact index, inputting the real-time lighting data set and the ambient light data set into an adaptive lighting control model, wherein the adaptive lighting control model is connected to the second LED light group; the adaptive lighting control model optimizes the lighting parameters of the second LED light group with the preset impact index as an adaptive target, outputs the lighting control parameters, and controls the second LED light group to perform neutral lighting according to the lighting control parameters, effectively solving the technical problem that the lighting system cannot provide the best lighting effect and energy efficiency due to the inability to monitor data in real time and perform adaptive control in the prior art, further affecting the user's work efficiency, comfort and overall lighting experience, and can dynamically respond to environmental changes, automatically adjust lighting conditions, and improve lighting comfort, energy efficiency and user satisfaction.

[0011] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0013] Figure 1 A schematic diagram of the process of the adaptive lighting method for combined LED lamps in this application;

[0014] Figure 2 This is a schematic diagram of the structure of the adaptive lighting system for combined LED lamps in this application.

[0015] Description of reference numerals:

[0016] Light group acquisition module 11, lighting data set acquisition module 12, influence index acquisition module 13, ambient light data acquisition module 14, data processing module 15, and lighting control parameter output module 16. DETAILED DESCRIPTION

[0017] The present application provides an adaptive lighting method and system for combined LED lamps, thereby solving the technical problem in the prior art that the lighting system cannot provide the best lighting effect and energy efficiency due to the inability to monitor data in real time and adaptively control, further affecting the user's work efficiency, comfort and overall lighting experience. The application can dynamically respond to environmental changes, automatically adjust lighting conditions, and improve lighting comfort, energy efficiency and user satisfaction.

[0018] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0019] Embodiment 1

[0020] Please see attached Figure 1 The present application provides an adaptive lighting method for a combined LED lamp, wherein the method is applied to an adaptive lighting system for a combined LED lamp, and the method specifically comprises the following steps:

[0021] S1: Acquire a first LED lamp group and a second LED lamp group of a combined LED lamp, wherein the first LED lamp group is a lamp group disposed inside a lighting cavity, and the second LED lamp group is a lamp group disposed outside the lighting cavity.

[0022] Specifically, the first LED light group refers to the LED light group installed inside the lighting cavity, such as lamps in the ceiling, recessed lighting, or light groups fixed in other closed structures in the room. These light groups provide basic lighting, but may not be adjusted for specific areas or activities due to their fixed positions. The second LED light group refers to the LED light group installed outside the lighting cavity, such as adjustable angle wall lamps, table lamps or floor lamps. These light groups can adjust the direction and brightness more flexibly to meet different lighting needs.

[0023] S2: Collecting a real-time lighting data set of the first LED light group.

[0024] Specifically, appropriate sensors are installed near the first LED light group. These sensors can be light intensity sensors, photosensors or RGB color sensors, etc., to detect lighting conditions. The sensors monitor the lighting environment in real time and collect lighting data such as light intensity, color temperature, and light distribution. The collected raw data is processed and converted into useful information. This includes filtering noise, standardizing data formats, calculating average lighting levels, etc. The real-time data set is analyzed using data analysis tools to evaluate whether the lighting effect meets the preset standards. This includes comparing the current lighting conditions with the recommended lighting standards.

[0025] S3: Perform strong lighting comfort impact assessment on the real-time lighting dataset to obtain a first impact index.

[0026] Specifically, the evaluation indicators are determined according to the standards for lighting comfort. These standards may include illumination level, light intensity distribution, color temperature, color consistency, flicker frequency, etc. The collected real-time lighting data is preprocessed to ensure the quality and consistency of the data. This includes removing outliers, filling missing data, smoothing data, etc. Using the preprocessed data, analysis is performed according to the established evaluation standards. This includes calculating illumination uniformity, evaluating glare risks, analyzing the impact of color temperature on human eye comfort, etc. Based on the analysis results, one or more impact indicators are calculated that reflect the impact of the lighting system on comfort. For example, a comprehensive scoring system can be used to take into account the weights of different factors, such as illumination, color temperature, and light distribution, to derive an overall comfort score.

[0027] S4: Setting an external ambient light sensor, and acquiring an ambient light data set according to the external ambient light sensor.

[0028] Specifically, choose the appropriate external ambient light sensor according to the application scenario and needs. These sensors can be photoresistors, photodiodes, or more advanced RGB color sensors that can detect light intensity in different wavelength ranges. Install the sensor in a location that can accurately reflect the external light conditions, which can be near a window or outside a building. The sensor should be installed away from direct sunlight and shading to ensure the accuracy of the data. The sensor monitors the external light conditions in real time and collects data, such as the illumination, color temperature, and light intensity changes of natural light.

[0029] S5: When the first impact index is greater than a preset impact index, inputting the real-time lighting data set and the ambient light data set into an adaptive lighting control model, wherein the adaptive lighting control model is connected to the second LED light group.

[0030] Specifically, a threshold is set as a preset impact indicator according to the lighting comfort standard and user needs. This threshold represents the minimum acceptable level of lighting comfort. The first impact indicator is compared with the preset impact indicator. If the first impact indicator exceeds the preset impact indicator, the adaptive control process will be triggered. The real-time lighting data set and the external ambient light data set are provided as input to the adaptive lighting control model. The adaptive lighting control model is an algorithm-based decision-making system that can process the input data and make suggestions for optimizing lighting based on the data. The model includes a machine learning algorithm that learns from historical data to predict and provide optimal lighting parameters. The model will output lighting control parameters such as brightness, color temperature, and light intensity distribution of the second LED light group to improve lighting conditions. Finally, according to the lighting control parameters output by the model, the settings of the second LED light group are adjusted through the lighting control system to achieve a more comfortable and efficient lighting environment.

[0031] S6: The adaptive lighting control model optimizes the lighting parameters of the second LED light group with the preset influencing index as the adaptive target, outputs the lighting control parameters, and controls the second LED light group to perform neutral lighting according to the lighting control parameters.

[0032] Specifically, the preset impact index is used as an adaptive target and is the benchmark for model optimization. This goal is to maintain a specific illumination level, color temperature, light distribution, etc., or a comprehensive comfort score that takes these factors into consideration. In the initial stage, the adaptive lighting control model needs to train historical data through a machine learning algorithm to learn how to optimize lighting parameters based on different input data, real-time lighting data sets, and ambient light data sets. The model uses optimization algorithms such as gradient descent, genetic algorithms, simulated annealing, etc. to find the best lighting control parameters. These parameters include the brightness, color temperature, switching time, etc. of the second LED light group to achieve the preset comfort target. The model outputs lighting control parameters based on the optimization results. These parameters will guide the lighting system on how to adjust the lighting settings of the second LED light group. The lighting control system adjusts the second LED light group in real time through a dimming module, a color temperature adjustment module, etc. based on the control parameters output by the model. For example, if the external light becomes dim, the model may increase the brightness of the internal lighting to maintain the comfort and consistency of the overall lighting effect. By adjusting the lighting parameters of the second LED light group, neutral lighting can be achieved, that is, balancing the impact of external light changes on indoor lighting, ensuring that indoor lighting always meets the user's comfort and functional needs.

[0033] Furthermore, the present application also includes:

[0034] Acquire real-time lighting parameters of the first LED light group, including lighting brightness, lighting color temperature and lighting range of the first LED light group; constrain the real-time lighting parameters of the second LED light group according to the real-time lighting parameters of the first LED light group, and obtain a lighting brightness threshold, a lighting color temperature threshold and a lighting range threshold; constrain the adaptive lighting control model according to the lighting brightness threshold, the lighting color temperature threshold and the lighting range threshold as constraint conditions.

[0035] Specifically, sensors and control systems are used to monitor the real-time lighting parameters of the first LED light group, including lighting brightness, lighting color temperature and lighting range. These parameters will directly affect the lighting effect and comfort. According to the real-time lighting parameters of the first LED light group, the constraints of the lighting parameters of the second LED light group are set. For example, if the brightness of the first LED light group is 1000 lumens, the brightness of the second LED light group may be constrained to be between 800 and 1200 lumens. Based on the set constraints, the lighting brightness threshold, lighting color temperature threshold and lighting range threshold of the second LED light group are calculated. These thresholds define the adjustable range of the second LED light group. The calculated thresholds are input into the adaptive lighting control model as constraints. In this way, the model will consider these constraints during the optimization process to ensure that the lighting parameters of the second LED light group will not exceed the set range. The model is optimized according to the new constraints and outputs the lighting control parameters of the second LED light group that meet the constraints. These parameters will ensure that the lighting of the second LED light group is coordinated with the first LED light group while meeting the overall lighting needs. Finally, according to the control parameters output by the model, the second LED light group is adjusted in real time through the dimming module, the color temperature adjustment module, etc. to achieve the optimized lighting effect.

[0036] Furthermore, step S5 of the present application also includes:

[0037] Acquire the spatial use characteristics of the combination LED lamp, wherein the spatial use characteristics include spatial user characteristics, spatial object characteristics, and spatial arrangement characteristics of the space where the combination LED lamp is located; perform lighting comfort impact analysis based on the spatial use characteristics, and configure preset impact indicators.

[0038] Specifically, analyze the main users of the space, including the user's age, activity type, such as work, study, rest, visual needs, etc. Objects and decorations in the space, such as furniture, artwork, exhibits, etc., which may require special lighting to highlight or protect. Analyze the layout and structure of the space, including the size, shape, window location, partitions, etc. of the room. Based on the space usage characteristics, perform lighting comfort impact analysis. For example, a space for reading may require higher brightness and warmer color temperature to reduce eye fatigue. Configure preset impact indicators based on the results of the lighting comfort impact analysis. These indicators will serve as the goals of the adaptive lighting control model to ensure that the lighting system meets the specific needs of the space. Adjust the parameters of the lighting system, such as brightness, color temperature, lighting range, etc., based on the space usage characteristics and preset impact indicators to provide the best lighting effect.

[0039] Furthermore, step S5 of the present application also includes:

[0040] Among them, the adaptive lighting control model includes an energy consumption feedback network layer; the real-time lighting data set and the ambient light data set are input into the adaptive lighting control model, and an energy consumption loss function is introduced to calculate the energy consumption data set of the lighting control parameters; the lighting control parameters are feedback optimized with minimizing the energy consumption data set as the feedback target of the energy consumption feedback network layer to obtain the optimized lighting control parameters; and the second LED light group is controlled according to the optimized lighting control parameters to perform neutralizing lighting.

[0041] Specifically, the real-time lighting dataset and the ambient light dataset are input into the adaptive lighting control model. These datasets contain all the necessary information for the model to make decisions. The energy consumption loss function is introduced into the model, which is a mathematical function used to evaluate the impact of lighting control parameters on energy consumption. The loss function calculates the energy consumption dataset corresponding to the lighting control parameters. The energy consumption dataset is input into the energy consumption feedback network layer, which is specially designed to process energy consumption-related information and use it as a feedback signal. The energy consumption feedback network layer performs feedback optimization on the lighting control parameters with the goal of minimizing the energy consumption dataset. Optimization algorithms such as gradient descent are used to adjust the parameters to find the lighting control strategy with the lowest energy consumption. After feedback optimization, the model outputs optimized lighting control parameters, which are designed to provide the desired lighting effect while minimizing energy consumption. Finally, based on the optimized lighting control parameters, the control system adjusts the lighting parameters of the second LED light group to achieve neutral lighting.

[0042] Furthermore, step S5 of the present application also includes:

[0043] The real-time lighting data set and the ambient light data set are input into the adaptive lighting control model, wherein the adaptive lighting control model is connected to a comfort evaluation model; optimization is performed according to the adaptive lighting control model to obtain initial lighting control parameters; a simulation system is connected to simulate the initial lighting control parameters, the real-time lighting data set and the ambient light data set, and a simulation data set is output; the simulation data set is analyzed based on the comfort evaluation model to obtain initial impact indicators, until the preset impact indicators are met, and the lighting control parameters are output.

[0044] Specifically, the real-time lighting data set and the ambient light data set are input into the adaptive lighting control model. These data sets contain all the necessary information for the model to make decisions. The input data set is optimized using the adaptive lighting control model to obtain initial lighting control parameters. These parameters are preliminary optimization results based on the model algorithm and preset goals. The initial lighting control parameters, the real-time lighting data set and the ambient light data set are connected to the simulation system. The simulation system simulates the effects of these parameters in the actual environment. After the simulation system runs, a simulation data set is output, which contains the simulated lighting effects and possible impacts. The simulation data set is analyzed based on the comfort evaluation model to obtain initial impact indicators. These indicators reflect the impact of lighting control parameters on comfort. Repeat the above steps, continuously adjust the lighting control parameters, and use the simulation system and the comfort evaluation model for testing and evaluation until the preset impact indicators are met. When the analysis results of the simulation data set meet the preset impact indicators, the final lighting control parameters are output. These parameters will be used to control the second LED light group to achieve the optimized lighting effect.

[0045] Furthermore, the comfort evaluation model includes:

[0046]

[0047] Among them, C is the comfort impact index, L avg is the average illumination based on the simulated data set, UGR is the glare evaluation index, α is the weight coefficient of the average illuminance, β is the weight coefficient of the glare evaluation index, L b is the background brightness based on the simulated data set, n is the number of light sources, is the brightness of the i-th light source in the simulated data set, and w i Based on the solid angle of the ith light source in the simulated data set, p i is the viewing axis angle of the ith light source based on the simulated data set, BR i is the visual axis brightness ratio for the i-th light source based on the simulated data set.

[0048] Specifically, the comfort impact index is a calculated value used to evaluate the impact of the lighting system on human comfort. The average illuminance based on the simulation data set is the average illuminance value calculated from the simulation data set. Illuminance is an important parameter for evaluating lighting effects, which affects visual comfort and work efficiency. The glare rating index is an indicator used to evaluate the glare level in a lighting system. Glare may cause visual discomfort, so it needs to be controlled within a reasonable range. The weight coefficient of the average illuminance determines the importance of illuminance in the overall score when calculating the comfort impact index. The weight coefficient of the glare rating index determines the importance of the glare rating index in the overall score. The background brightness based on the simulation data set refers to the background brightness in the lighting environment, which may affect the lighting effect and visual comfort. The number of light sources refers to the total number of light sources in the lighting environment. The number and distribution of light sources affect the uniformity and comfort of lighting. The brightness of the i-th light source based on the simulation data set refers to the brightness value of the i-th light source in the simulation data set. The solid angle for the i-th light source based on the simulation data set is the angular range of the light source in the field of view, which affects the perception of glare. Based on the simulated data set, the visual axis angle of the ith light source refers to the angle of the ith light source relative to the visual axis and the direction of the observer's line of sight. Based on the simulated data set, the visual axis brightness ratio for the ith light source refers to the ratio of the brightness of the ith light source in the visual axis direction to the background brightness, which may be related to glare perception.

[0049] Furthermore, the present application also includes:

[0050] A comfort lighting sample is established, and the comfort assessment model is tested using the comfort lighting sample to obtain positive test samples and negative test samples; weight coefficients α, β of the comfort assessment model are optimized and adjusted according to the positive test samples and the negative test samples until the number of negative test samples is less than a preset threshold and the comfort assessment model converges.

[0051] Specifically, data from a series of lighting scenarios are collected, which represent different lighting conditions and comfort levels. These samples should include positive examples, comfortable lighting, and negative examples, uncomfortable lighting. The comfort assessment model is tested using the established comfort lighting samples. The model will evaluate each sample and output a comfort score or classification result. Based on the test results, the samples are divided into positive test samples, which are samples that the model correctly identifies as comfortable lighting, and negative test samples, which are samples that the model incorrectly identifies or does not identify as comfortable lighting. The weight coefficients of the comfort assessment model are adjusted using positive test samples and negative test samples. The adjustment of the weight coefficients is based on optimization algorithms, such as gradient descent or genetic algorithms, to improve the performance of the model. The testing and adjustment process is repeated until the number of negative test samples is reduced below a preset threshold. This means that the model has been able to accurately identify most scenes of comfortable lighting. When the number of negative test samples reaches below the preset threshold and further iterations no longer significantly improve the performance of the model, the comfort assessment model can be considered to have converged. At this point, the model is considered to have been fully trained and can be used for actual lighting evaluation and optimization.

[0052] In summary, the adaptive lighting method for combined LED lamps provided in this application has the following technical effects:

[0053] By acquiring a first LED light group and a second LED light group of a combined LED lamp, wherein the first LED light group is a light group arranged inside the lighting cavity, and the second LED light group is a light group arranged outside the lighting cavity; collecting a real-time lighting data set of the first LED light group; performing a strong lighting comfort impact assessment on the real-time lighting data set to obtain a first impact index; setting an external ambient light sensor, and obtaining an ambient light data set according to the external ambient light sensor; when the first impact index is greater than a preset impact index, inputting the real-time lighting data set and the ambient light data set into an adaptive lighting control model, wherein the adaptive lighting control model is connected to the second LED light group; the adaptive lighting control model optimizes the lighting parameters of the second LED light group with the preset impact index as an adaptive target, outputs the lighting control parameters, and controls the second LED light group to perform neutral lighting according to the lighting control parameters, effectively solving the technical problem that the lighting system cannot provide the best lighting effect and energy efficiency due to the inability to monitor data in real time and perform adaptive control in the prior art, further affecting the user's work efficiency, comfort and overall lighting experience, and can dynamically respond to environmental changes, automatically adjust lighting conditions, and improve lighting comfort, energy efficiency and user satisfaction.

[0054] Embodiment 2

[0055] Based on the adaptive lighting method for combined LED lamps in the aforementioned embodiment, the present application also provides an adaptive lighting system for combined LED lamps, see the attached Figure 2 , the system comprising:

[0056] The light group acquisition module 11 is used to acquire a first LED light group and a second LED light group of the combined LED lamp, wherein the first LED light group is a light group arranged inside the lighting cavity, and the second LED light group is a light group arranged outside the lighting cavity.

[0057] The lighting data set acquisition module 12 is used to collect the real-time lighting data set of the first LED lamp group.

[0058] The impact index acquisition module 13 is used to evaluate the impact of strong lighting comfort on the real-time lighting data set to obtain a first impact index.

[0059] The ambient light data acquisition module 14 is used to set an external ambient light sensor and acquire an ambient light data set according to the external ambient light sensor.

[0060] The data processing module 15 is used to input the real-time lighting data set and the ambient light data set into an adaptive lighting control model when the first impact index is greater than a preset impact index, wherein the adaptive lighting control model is connected to the second LED light group.

[0061] The control lighting parameter output module 16 is used for the adaptive lighting control model to optimize the lighting parameters of the second LED light group with the preset influencing index as the adaptive target, output lighting control parameters, and control the second LED light group to perform neutral lighting according to the lighting control parameters.

[0062] Furthermore, the system further comprises a threshold value acquisition module, and the threshold value acquisition module is used to:

[0063] Acquire real-time lighting parameters of the first LED light group, including lighting brightness, lighting color temperature and lighting range of the first LED light group; constrain the real-time lighting parameters of the second LED light group according to the real-time lighting parameters of the first LED light group, and obtain a lighting brightness threshold, a lighting color temperature threshold and a lighting range threshold; constrain the adaptive lighting control model according to the lighting brightness threshold, the lighting color temperature threshold and the lighting range threshold as constraint conditions.

[0064] Furthermore, the data processing module 15 in the system is also used for:

[0065] Acquire the spatial use characteristics of the combination LED lamp, wherein the spatial use characteristics include spatial user characteristics, spatial object characteristics, and spatial arrangement characteristics of the space where the combination LED lamp is located; perform lighting comfort impact analysis based on the spatial use characteristics, and configure preset impact indicators.

[0066] Furthermore, the data processing module 15 in the system is also used for:

[0067] Among them, the adaptive lighting control model includes an energy consumption feedback network layer; the real-time lighting data set and the ambient light data set are input into the adaptive lighting control model, and an energy consumption loss function is introduced to calculate the energy consumption data set of the lighting control parameters; the lighting control parameters are feedback optimized with minimizing the energy consumption data set as the feedback target of the energy consumption feedback network layer to obtain the optimized lighting control parameters; and the second LED light group is controlled according to the optimized lighting control parameters to perform neutralizing lighting.

[0068] Furthermore, the data processing module 15 in the system is also used for:

[0069] Input the real-time lighting data set and the ambient light data set into the adaptive lighting control model, wherein the adaptive lighting control model is connected to a comfort evaluation model; perform optimization according to the adaptive lighting control model to obtain initial lighting control parameters; access a simulation system to simulate the initial lighting control parameters, the real-time lighting data set and the ambient light data set, and output a simulation data set; analyze the simulation data set based on the comfort evaluation model to obtain initial impact indicators, until the preset impact indicators are met, and output the lighting control parameters. The comfort evaluation model includes:

[0070]

[0071] Among them, C is the comfort impact index, L avg is the average illumination based on the simulated data set, UGR is the glare evaluation index, α is the weight coefficient of the average illuminance, β is the weight coefficient of the glare evaluation index, L b is the background brightness based on the simulated data set, n is the number of light sources, is the brightness of the i-th light source in the simulated data set, and w i Based on the solid angle of the ith light source in the simulated data set, p i is the viewing axis angle of the ith light source based on the simulated data set, BR i is the visual axis brightness ratio for the i-th light source based on the simulated data set.

[0072] Furthermore, the system further includes an optimization and adjustment module, which is used to:

[0073] A comfort lighting sample is established, and the comfort assessment model is tested using the comfort lighting sample to obtain positive test samples and negative test samples; weight coefficients α, β of the comfort assessment model are optimized and adjusted according to the positive test samples and the negative test samples until the number of negative test samples is less than a preset threshold and the comfort assessment model converges.

[0074] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1 The adaptive lighting method and specific examples for combined LED lamps in the first embodiment are also applicable to the adaptive lighting system for combined LED lamps in the present embodiment. Through the above detailed description of the adaptive lighting method for combined LED lamps, those skilled in the art can clearly understand the adaptive lighting system for combined LED lamps in the present embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0075] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. 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 application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0076] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. An adaptive lighting method for a combined LED lamp, characterized in that: The method comprises: Acquire a first LED lamp group and a second LED lamp group of the combined LED lamp, wherein the first LED lamp group is a lamp group arranged inside the lighting cavity, and the second LED lamp group is a lamp group arranged outside the lighting cavity; Collecting a real-time lighting data set of the first LED lamp group; Performing a strong lighting comfort impact assessment on the real-time lighting data set to obtain a first impact index; Setting an external ambient light sensor, and acquiring an ambient light data set according to the external ambient light sensor; When the first impact index is greater than a preset impact index, inputting the real-time lighting data set and the ambient light data set into an adaptive lighting control model, wherein the adaptive lighting control model is connected to the second LED light group; The adaptive lighting control model optimizes the lighting parameters of the second LED light group with the preset influencing index as the adaptive target, outputs the lighting control parameters, and controls the second LED light group to perform neutral lighting according to the lighting control parameters.

2. The adaptive lighting method for combined LED lamps according to claim 1, characterized in that: The method further comprises: Acquire real-time lighting parameters of the first LED light group, including lighting brightness, lighting color temperature, and lighting range of the first LED light group; Constraining the real-time lighting parameters of the second LED light group according to the real-time lighting parameters of the first LED light group to obtain a lighting brightness threshold, a lighting color temperature threshold, and a lighting range threshold; The adaptive lighting control model is constrained according to the lighting brightness threshold, the lighting color temperature threshold and the lighting range threshold as constraint conditions.

3. The adaptive lighting method for combined LED lamps according to claim 1, characterized in that: When the first impact indicator is greater than a preset impact indicator, the method includes: Acquire the spatial use characteristics of the combined LED lamp, wherein the spatial use characteristics include spatial user characteristics, spatial object characteristics, and spatial arrangement characteristics of the space where the combined LED lamp is located; Perform lighting comfort impact analysis based on the space usage characteristics and configure preset impact indicators.

4. The adaptive lighting method for combined LED lamps according to claim 1, characterized in that: The real-time lighting data set and the ambient light data set are input into an adaptive lighting control model. The method further include: Wherein, the adaptive lighting control model includes an energy consumption feedback network layer; Inputting the real-time lighting data set and the ambient light data set into the adaptive lighting control model, and introducing an energy consumption loss function to calculate the energy consumption data set of the lighting control parameters; Performing feedback optimization on the lighting control parameters by taking the minimization of the energy consumption data set as the feedback target of the energy consumption feedback network layer to obtain the optimized lighting control parameters; The second LED lamp group is controlled to perform neutralizing lighting according to the optimized lighting control parameters.

5. The adaptive lighting method for combined LED lamps according to claim 1, characterized in that: Inputting the real-time lighting data set and the ambient light data set into an adaptive lighting control model, the method comprising: Inputting the real-time lighting data set and the ambient light data set into the adaptive lighting control model, wherein the adaptive lighting control model is connected to a comfort assessment model; Perform optimization according to the adaptive lighting control model to obtain initial lighting control parameters; Accessing a simulation system to simulate the initial lighting control parameters, the real-time lighting data set and the ambient light data set, and outputting a simulation data set; The simulation data set is analyzed based on the comfort evaluation model to obtain an initial impact index, and the lighting control parameter is output until the preset impact index is met.

6. The adaptive lighting method for combined LED lamps according to claim 5, characterized in that: The comfort evaluation model includes: Among them, C is the comfort impact index, L avg is the average illumination based on the simulated data set, UGR is the glare evaluation index, α is the weight coefficient of the average illuminance, β is the weight coefficient of the glare evaluation index, L b is the background brightness based on the simulated data set, n is the number of light sources, L i is the brightness of the i-th light source in the simulated data set, w i Based on the solid angle of the ith light source in the simulated data set, p i is the viewing axis angle of the ith light source based on the simulated data set, BR i is the visual axis brightness ratio for the i-th light source based on the simulated data set.

7. The adaptive lighting method for combined LED lamps according to claim 6, characterized in that: The method further comprises: Establishing a comfort lighting sample, using the comfort lighting sample to test the comfort evaluation model, and obtaining a positive test sample and a negative test sample; The weight coefficients α and β of the comfort evaluation model are optimized and adjusted according to the positive test samples and the negative test samples until the number of the negative test samples is less than a preset threshold and the comfort evaluation model converges.

8. An adaptive lighting system for a combined LED lamp, characterized in that, The system is used to implement the steps of the adaptive lighting method for combined LED lamps according to any one of claims 1 to 7, the system comprising: A lamp group acquisition module, the lamp group acquisition module is used to acquire a first LED lamp group and a second LED lamp group of the combined LED lamp, wherein the first LED lamp group is a lamp group arranged inside the lighting cavity, and the second LED lamp group is a lamp group arranged outside the lighting cavity; An illumination data set acquisition module, the illumination data set acquisition module is used to collect a real-time illumination data set of the first LED lamp group; An impact index acquisition module, the impact index acquisition module is used to evaluate the impact of strong lighting comfort on the real-time lighting data set to obtain a first impact index; An ambient light data acquisition module, the ambient light data acquisition module is used to set an external ambient light sensor and acquire an ambient light data set according to the external ambient light sensor; a data processing module, wherein when the first impact index is greater than a preset impact index, the data processing module is used to input the real-time lighting data set and the ambient light data set into an adaptive lighting control model, wherein the adaptive lighting control model is connected to the second LED light group; A lighting parameter control output module is used for the adaptive lighting control model to optimize the lighting parameters of the second LED light group with the preset influencing index as the adaptive target, output lighting control parameters, and control the second LED light group to perform neutral lighting according to the lighting control parameters.

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