A lighting control method and system for a phosphor-free multi-primary color LED street lamp

Abstract

The present invention relates to the field of LED control, and in particular to a method and system for controlling illumination of a fluorescent powder-free multi-primary color LED street lamp. The method comprises the following steps: obtaining a sample set of natural light spectrum parameters; performing a wavelength quantitative analysis on the sample set of natural light spectrum parameters, thereby obtaining an interval wavelength parameter characterization; obtaining a light source output parameter based on an LED lamp array; performing a luminous flux analysis on the light source output parameter, and mining the color temperature distribution characteristics, thereby obtaining the light source color temperature distribution characteristics; performing independent unit division processing on the LED lamp array, and performing illumination distribution field fitting to construct an illumination independent unit network; performing natural light compensation demand calculation on the illumination independent unit network based on the interval wavelength parameter characterization, and performing precise illumination compensation regulation to construct a natural light compensation regulation strategy. The present invention realizes efficient and adaptive illumination control of LED street lamps.

Description

Technical Field

[0001] The present invention relates to the field of LED control, and in particular to a lighting control method and system for a fluorescent powder-free multi-primary color LED lighting street lamp. Background Art

[0002] With the continuous development of urban construction, LED lighting has become the mainstream choice in the field of lighting for urban roads, buildings, etc. Traditional LED street lamps mostly use phosphor conversion technology, which has problems such as fixed color temperature and poor color rendering, and it is difficult to meet the increasingly diverse lighting needs. At the same time, these LED street lamps will also have problems such as light decay and failure during long-term use, which brings inconvenience to lighting maintenance. In the past, LED street lamp lighting control usually adopts manual fixed control, and the color and brightness cannot be changed in real time. The control efficiency is low and cannot be adjusted in real time. Therefore, it is urgent to develop an innovative LED street lamp lighting control solution to meet the diverse lighting needs of smart cities, improve the overall performance of LED lighting systems, and contribute to the transformation and upgrading of urban lighting systems. Summary of the invention

[0003] The present invention proposes a lighting control method and system for a phosphor-free multi-primary color LED lighting street lamp to solve at least one of the above technical problems.

[0004] To achieve the above object, the present invention provides a method for controlling illumination of a phosphor-free multi-primary color LED street lamp, wherein the phosphor-free multi-primary color LED street lamp comprises an LED lamp array, and the method comprises the following steps:

[0005] Step S1: obtaining a natural light spectrum parameter sample set; performing wavelength quantitative analysis on the natural light spectrum parameter sample set to obtain interval wavelength parameter representation;

[0006] Step S2: obtaining light source output parameters based on the LED lamp array; performing luminous flux analysis on the light source output parameters, and mining color temperature distribution characteristics, thereby obtaining light source color temperature distribution characteristics;

[0007] Step S3: Divide the LED light array into independent units, perform illumination distribution field fitting, and construct an illumination independent unit network;

[0008] Step S4: calculating the natural light compensation demand of the lighting independent unit network based on the interval wavelength parameter characterization, and performing precise control of the lighting compensation to construct a natural light compensation control strategy;

[0009] Step S5: dynamically controlling the color temperature of each unit of the lighting independent unit network based on the color temperature distribution characteristics of the light source, and generating an adaptive unit color temperature control strategy;

[0010] Step S6: Obtain pedestrian movement position data; based on the pedestrian movement position data, make light source control optimization decisions on the natural light compensation control strategy, the adaptive unit color temperature control strategy and the dynamic energy-saving control strategy, and build a lighting intelligent control model to perform lighting control operations.

[0011] Preferably, step S1 comprises the following steps:

[0012] Step S11: performing high-frequency spectrum sampling on ambient natural light based on a spectrum detection sensor, thereby obtaining a natural light spectrum parameter sample set;

[0013] Step S12: performing Fourier transform processing on the natural light spectrum parameter sample set to generate natural light spectrum frequency domain data;

[0014] Step S13: performing frequency domain characteristic change analysis on the natural light spectrum frequency domain data, thereby generating a spectrum frequency domain curve;

[0015] Step S14: performing curve morphology analysis on the spectrum frequency domain curve to generate natural light intensity data;

[0016] Step S15: performing wavelength quantitative analysis on the spectrum frequency domain curve based on the natural light intensity data, thereby obtaining interval wavelength parameter representation.

[0017] The present invention can capture the characteristics and changing laws of natural light in the environment through high-frequency spectral sampling, provide real-time ambient light data for the intelligent control of LED street lamps, obtain a sample set of natural light spectrum parameters to establish a basic model of ambient light, thereby intelligently adjusting the brightness and color temperature of LED street lamps according to actual ambient light conditions, improving energy efficiency and comfort, and converting the natural light spectrum parameters into the frequency domain through Fourier transform processing, making the frequency domain characteristics clearer and more visible, analyzing the energy distribution of light signals at different frequencies, and providing a data basis for subsequent frequency domain characteristic analysis. Through the analysis of frequency domain characteristic changes, the changing laws of natural light in the frequency domain, such as spectrum density, spectrum bandwidth, etc., can be revealed.

[0018] Through curve morphology analysis, the illumination intensity data of natural light, that is, the intensity value of the light signal, is extracted from the frequency domain curve to understand the intensity change of ambient light, providing key information for the brightness control of LED street lamps. Through wavelength quantitative analysis, the light characteristics of different wavelength ranges in the natural light spectrum, such as the energy distribution of light of different wavelengths, are identified, and the interval wavelength parameter characterization is obtained to convert the natural light wavelength information into quantitative data, providing support for the color temperature control and spectrum adjustment of LED street lamps.

[0019] Preferably, step S15 specifically comprises the following steps:

[0020] Performing filtering and smoothing optimization on the spectrum frequency domain curve to generate a smooth optimized spectrum frequency domain curve;

[0021] Perform wavelength quantitative analysis on the smooth optimized spectrum frequency domain curve to obtain the wavelength parameters of the curve;

[0022] Based on the wavelength parameters of the curve, the smooth optimized spectrum frequency domain curve is divided into wavelength intervals to obtain multiple wavelength interval curves;

[0023] Based on the natural light intensity data, the average light intensity of multiple wavelength interval curves is calculated to obtain the average light intensity value of the wavelength interval;

[0024] Perform light intensity distribution trend analysis on multiple wavelength interval curves to obtain wavelength interval light intensity distribution trend data;

[0025] The wavelength parameter characteristics of the wavelength interval average light intensity value and the wavelength interval light intensity distribution trend data are mined to obtain the interval wavelength parameter representation.

[0026] The present invention optimizes the spectrum frequency domain curve by filtering, smoothing, and removing noise and mutations in the curve, making the curve smoother and continuous, generating a smooth optimized spectrum frequency domain curve to more accurately analyze the frequency domain characteristics of the optical signal, and providing a more reliable data basis for subsequent wavelength quantitative analysis. Through the wavelength quantitative analysis, characteristic parameters of light of different wavelengths in the smooth optimized spectrum frequency domain curve, such as wavelength peak value, wavelength bandwidth, etc., can be accurately measured, and the wavelength parameters of the curve are obtained to quantitatively describe the wavelength characteristics of the optical signal, providing a basis for subsequent wavelength interval division. According to the wavelength parameters of the curve, the smooth optimized spectrum frequency domain curve is divided into wavelength intervals, decomposed into sections with different wavelength ranges, and a multi-segment wavelength interval curve is obtained to more carefully analyze the characteristic changes of the optical signal in different wavelength ranges, providing a basis for light intensity calculation and light intensity distribution trend analysis.

[0027] By calculating the average light intensity in intervals, the average light intensity value of each wavelength interval is obtained, which reflects the intensity of light signals within different wavelength ranges. The average light intensity value of the wavelength interval is obtained to understand the light intensity distribution of light of different wavelengths. Through the light intensity distribution trend analysis, the changing trend of light intensity in different wavelength intervals, such as the increase and decrease trend, fluctuation, etc., is revealed. The light intensity distribution trend data of the wavelength interval is obtained to understand the changing law of light signals within different wavelength ranges. Through the wavelength parameter feature mining, the characteristics of light intensity values ​​and light intensity distribution trends in different wavelength intervals are deeply analyzed, and the laws and correlations therein are found. The interval wavelength parameter characterization comprehensively considers the wavelength characteristics and light intensity distribution of light signals, providing an important reference for the formulation of control strategies for LED lighting street lamps.

[0028] Preferably, the specific steps of step S2 are:

[0029] Step S21: monitoring the current light source output of the LED lamp array to obtain light source output parameters;

[0030] Step S22: performing luminous flux analysis on the light source output parameters to generate light source luminous flux data;

[0031] Step S23: performing uniformity distribution calculation on the light source luminous flux data to obtain light source luminous flux distribution data;

[0032] Step S24: performing time series distribution trend evolution analysis on the light source luminous flux distribution data to generate luminous flux distribution trend evolution data;

[0033] Step S25: mining the color temperature distribution characteristics of the LED lamp array based on the luminous flux distribution trend evolution data, thereby obtaining the color temperature distribution characteristics of the light source.

[0034] The present invention monitors the current light source output parameters of the LED lamp array to understand the working status of the LED lighting system in real time, obtains the light source output parameters to evaluate the brightness and stability of the LED lamp array, and provides basic data for subsequent analysis. Through luminous flux analysis, the light output performance of the LED lamp array is quantified, including the overall light output intensity and the brightness characteristics of the light source. The light source luminous flux data is generated to understand the overall lighting effect of the LED lamp array, providing a data basis for subsequent uniformity distribution calculations. Through uniformity distribution calculations, the uniformity of the light source of the LED lamp array, that is, whether the luminous flux is uniformly distributed in space, is evaluated. The light source luminous flux distribution data is obtained to discover the uneven lighting phenomenon in the LED lamp array, providing a basis for the analysis of the luminous flux distribution trend evolution.

[0035] The time series distribution trend evolution analysis reveals the changing trend of the luminous flux distribution of the LED lamp array over time, including the evolution of the luminous flux uniformity. The luminous flux distribution trend evolution data is generated to understand the evolution of the lighting effect of the LED lighting system during long-term use, providing a reference for subsequent control and maintenance. Through the mining of color temperature distribution characteristics, the spatial distribution characteristics of the light source color temperature of the LED lamp array are deeply analyzed, including the uniformity and change law of color temperature. The color temperature distribution characteristics of the light source are obtained to optimize the lighting effect of LED lighting street lamps and improve lighting comfort and energy efficiency.

[0036] Preferably, step S3 specifically comprises the following steps:

[0037] Step S31: dividing the LED lamp array into independent units, thereby obtaining a plurality of LED lamp independent units;

[0038] Step S32: quantifying the dynamic illumination distribution of multiple LED lamp independent units based on the luminous flux distribution trend evolution data, thereby obtaining dynamic illumination distribution data of each independent unit;

[0039] Step S33: Fit the illumination distribution field of each independent unit's dynamic illumination distribution data to construct an illumination independent unit network.

[0040] The present invention decomposes an LED lamp array into multiple independent LED lamp units through independent unit division, realizes independent control and management of each LED lamp, obtains multiple LED lamp independent units to realize personalized lighting adjustment, improves the flexibility and customization of lighting, quantifies dynamic lighting distribution, realizes real-time lighting adjustment of each LED lamp independent unit according to luminous flux distribution trend data, obtains dynamic lighting distribution data of each independent unit, dynamically adjusts the lighting intensity and distribution of the LED lamp according to the environment and demand, integrates the lighting data of each independent unit into a lighting independent unit network through lighting distribution field fitting, realizes overall lighting control of the LED lighting system, constructs a lighting independent unit network to uniformly manage the lighting distribution of the LED lamp array, and improves the intelligence level and overall efficiency of the system.

[0041] Preferably, the specific steps of step S4 are:

[0042] Step S41: calculating the natural light compensation demand of the lighting independent unit network based on the interval wavelength parameter characterization, thereby obtaining a simulated natural light compensation demand value of each independent unit;

[0043] Step S42: performing unit compensation difference analysis on the simulated natural light compensation requirement value of each independent unit to generate an independent unit compensation difference gradient;

[0044] Step S43: performing uniform calculation of illumination compensation rate based on independent unit compensation difference gradient to generate unit network compensation uniform rate;

[0045] Step S44: Use the unit network compensation uniform rate to accurately control the illumination compensation of the illumination independent unit network, and construct a natural light compensation control strategy.

[0046] The present invention accurately calculates the natural light compensation demand of each independent unit within a specific wavelength range through interval wavelength parameter characterization, obtains the simulated natural light compensation demand value, understands the natural light compensation amount required for each independent unit, and provides a basis for subsequent compensation difference analysis. Through the compensation difference analysis, the natural light compensation demand value of each independent unit is compared, the compensation difference between different units is found, and the independent unit compensation difference gradient is generated to understand the compensation difference between each unit, providing a basis for the subsequent uniform calculation of the light compensation rate.

[0047] By compensating for the difference gradient, the rate of illumination compensation is calculated, making the compensation process of each independent unit more uniform and balanced. The uniform rate of unit network compensation is generated to formulate a unified illumination compensation strategy, improve the overall illumination control effect of the LED lamp array, and achieve precise control of the illumination independent unit network through the uniform rate of unit network compensation, ensuring that the illumination compensation effect of each unit is uniform and accurate. A natural light compensation control strategy is constructed to improve the adaptability of the LED lighting street lamp system to changes in natural light, and provide a more comfortable and efficient lighting environment.

[0048] Preferably, the specific steps of step S41 are:

[0049] Quantify the illumination intensity of each unit in the illumination independent unit network and generate the illumination intensity value of each independent unit;

[0050] Based on the interval wavelength parameter representation, the natural light variation characteristics are simulated to obtain the natural light wavelength simulation parameters;

[0051] The natural light compensation requirement is calculated for the light intensity value of each independent unit based on the natural light wavelength simulation parameter, thereby obtaining the simulated natural light compensation requirement value of each independent unit.

[0052] The present invention quantifies the light intensity of each unit one by one, accurately measures the light intensity value of each independent unit, provides basic data for subsequent light control, generates light intensity values ​​to understand the actual light conditions of each unit, provides accurate information for optimization and adjustment of the lighting system, simulates the changing characteristics of natural light through interval wavelength parameter characterization, simulates the wavelength change of natural light in different time periods, obtains natural light wavelength simulation parameters to understand the changing law of natural light, provides a basis for subsequent calculation of light compensation demand, calculates natural light compensation demand based on natural light wavelength simulation parameters, calculates the natural light compensation demand of each independent unit according to the wavelength characteristics of natural light, obtains simulated natural light compensation demand values ​​to determine the compensation demand of each unit under different light conditions, and provides support for providing a more comfortable and natural lighting environment.

[0053] Preferably, the specific steps of step S5 are:

[0054] Step S51: performing independent unit color temperature calculation on the illumination independent unit network based on the light source color temperature distribution characteristics to generate a plurality of independent unit color temperature values;

[0055] Step S52: performing color temperature offset analysis on multiple independent unit color temperature values ​​based on preset LED light source theoretical color temperature parameters to obtain independent unit color temperature offset data;

[0056] Step S53: performing color temperature offset distribution analysis on the independent unit color temperature offset data to obtain a color temperature offset distribution field;

[0057] Step S54: dynamically controlling the color temperature of each lighting independent unit network unit by unit according to the color temperature offset distribution field, and generating an adaptive unit color temperature control strategy.

[0058] The present invention calculates the color temperature of independent units through the color temperature distribution characteristics of the light source, accurately determines the color temperature value of each independent unit, reflects the lighting characteristics of different areas, generates multiple independent unit color temperature values ​​to understand the color temperature conditions of various areas in the LED lighting street lamp system, and provides basic data for subsequent color temperature offset analysis. By analyzing the color temperature offset of the independent unit, the difference between the actual color temperature and the preset theoretical color temperature is compared, the color temperature offset is identified, and the independent unit color temperature offset data is obtained to understand the color temperature adjustment requirements of each unit, providing a basis for subsequent color temperature offset distribution analysis.

[0059] Through color temperature offset distribution analysis, the color temperature offset of each independent unit is comprehensively considered to form an overall color temperature offset distribution scenario, and the color temperature offset distribution field is obtained to understand the demand trend and key areas of overall color temperature control, provide guidance for the formulation of color temperature control strategies, and perform dynamic color temperature control of each unit according to the color temperature offset distribution field to achieve personalized color temperature adjustment for different areas, improve lighting comfort and effect, and generate an adaptive unit color temperature control strategy to dynamically adjust the color temperature of the LED lighting street lamp system according to actual conditions, so as to achieve more intelligent and adaptable lighting control.

[0060] Preferably, the specific steps of step S6 are:

[0061] Step S61: obtaining pedestrian movement position data based on sensors;

[0062] Step S62: performing mobile positioning tracking on the pedestrian's mobile position data to generate a pedestrian's mobile positioning trajectory;

[0063] Step S63: calculating the street lamp distance change of the pedestrian movement positioning trajectory, thereby obtaining pedestrian distance change data;

[0064] Step S64: performing critical lighting analysis on pedestrian distance change data based on the preset maximum lighting distance of LED street lamps, and performing street lamp energy-saving dynamic control to generate a dynamic energy-saving control strategy;

[0065] Step S65: Optimize the light source control decision for the natural light compensation control strategy, the adaptive unit color temperature control strategy and the dynamic energy-saving control strategy, and build a lighting intelligent control model to perform lighting control operations.

[0066] The present invention obtains pedestrian movement position data, and the system monitors the position information of pedestrians within the lighting range in real time. The pedestrian position data collection system perceives changes in the surrounding environment and provides real-time input for subsequent intelligent control. Through mobile positioning and tracking, the system generates pedestrian movement trajectories and understands the activity paths of pedestrians in the area. The generation of pedestrian movement trajectories predicts the future movement trends of pedestrians, providing a basis for the intelligent regulation of street lighting. By calculating the distance change data of pedestrians, the system analyzes the distance change between pedestrians and street lamps. The acquisition of pedestrian distance change data evaluates the brightness demand between pedestrians and street lamps, providing a basis for energy-saving control.

[0067] Through critical lighting analysis, the system determines the optimal lighting distance between pedestrians and street lamps to ensure the safety and comfort of pedestrians. The generation of dynamic energy-saving control strategies adjusts the brightness of street lamps in real time according to changes in pedestrian positions, saving energy and extending the life of street lamps. Through the optimization decision of natural light compensation, unit color temperature regulation and dynamic energy-saving control strategies, the system comprehensively considers different factors to adjust the light source control. The construction of the intelligent lighting control model realizes intelligent lighting control, improves lighting effects and energy-saving effects, and provides support for the optimized management of LED lighting street lamp systems.

[0068] In this specification, a lighting control system for a phosphor-free multi-primary color LED lighting street lamp is provided, which is used to execute the lighting control method for the phosphor-free multi-primary color LED lighting street lamp as described above, including:

[0069] The interval wavelength module is used to obtain a sample set of natural light spectrum parameters; perform wavelength quantitative analysis on the sample set of natural light spectrum parameters to obtain interval wavelength parameter representation;

[0070] The color temperature distribution module is used to obtain the light source output parameters based on the LED light array; perform luminous flux analysis on the light source output parameters and mine the color temperature distribution characteristics to obtain the light source color temperature distribution characteristics;

[0071] Independent unit module, used to divide the LED light array into independent units, fit the illumination distribution field, and build an illumination independent unit network;

[0072] The natural light compensation module is used to calculate the natural light compensation demand of the independent lighting unit network based on the interval wavelength parameter characterization, and to perform precise control of the lighting compensation and build a natural light compensation control strategy;

[0073] A color temperature control module is used to dynamically control the color temperature of each unit of the lighting independent unit network based on the color temperature distribution characteristics of the light source, and generate an adaptive unit color temperature control strategy;

[0074] The intelligent control module is used to obtain pedestrian movement position data; based on the pedestrian movement position data, the natural light compensation control strategy, the adaptive unit color temperature control strategy and the dynamic energy-saving control strategy are used to make light source control optimization decisions, and a lighting intelligent control model is constructed to perform lighting control operations.

[0075] The beneficial effects of the present invention are:

[0076] The system of the present invention obtains a sample set of natural light spectrum parameters and performs quantitative wavelength analysis to obtain interval wavelength parameter representation to understand the spectral characteristics, and obtains the color temperature distribution characteristics of the light source through analysis of the light source output parameters and mining of the color temperature distribution characteristics. The acquisition of the light source color temperature distribution characteristics evaluates the lighting needs of different areas and provides a basis for color temperature control. The independent unit network of lighting is constructed through independent unit division processing and lighting distribution field fitting. The establishment of the independent unit network of lighting analyzes and manages the lighting conditions of different areas, providing a basis for subsequent regulation. The natural light compensation demand is calculated and precisely regulated to construct a natural light compensation regulation strategy.

[0077] The implementation of the natural light compensation control strategy is adjusted according to the ambient light conditions, which improves the lighting effect and energy-saving effect. Through the generation of a dynamic color temperature control strategy, the color temperature control of each unit can be achieved. The application of the adaptive unit color temperature control strategy adjusts the color temperature of the light source according to demand, which can provide a more comfortable lighting environment. By obtaining pedestrian movement position data and making light source control optimization decisions, an intelligent lighting control model is constructed. The model can adjust lighting parameters according to real-time needs, provide intelligent lighting management, and save energy at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 A schematic flow chart of the steps of a method for controlling illumination of a fluorescent powder-free multi-primary color LED street lamp according to the present invention;

[0079] Figure 2 Detailed implementation flow chart of step S1;

[0080] Figure 3 Detailed implementation flow chart of step S2;

[0081] Figure 4 Detailed implementation flow chart of step S3. DETAILED DESCRIPTION

[0082] 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.

[0083] The present application example provides a method and system for controlling the illumination of a phosphor-free multi-primary LED street lamp. The execution subject of the method and system for controlling the illumination of a phosphor-free multi-primary LED street lamp includes but is not limited to the following: 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 the present 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.

[0084] See also Figures 1 to 4 The present invention provides a method for controlling illumination of a phosphor-free multi-primary color LED street lamp, wherein the phosphor-free multi-primary color LED street lamp comprises an LED lamp array, comprising the following steps:

[0085] Step S1: obtaining a natural light spectrum parameter sample set; performing wavelength quantitative analysis on the natural light spectrum parameter sample set to obtain interval wavelength parameter representation;

[0086] Step S2: obtaining light source output parameters based on the LED lamp array; performing luminous flux analysis on the light source output parameters, and mining color temperature distribution characteristics, thereby obtaining light source color temperature distribution characteristics;

[0087] Step S3: Divide the LED light array into independent units, perform illumination distribution field fitting, and construct an illumination independent unit network;

[0088] Step S4: calculating the natural light compensation demand of the lighting independent unit network based on the interval wavelength parameter characterization, and performing precise control of the lighting compensation to construct a natural light compensation control strategy;

[0089] Step S5: dynamically controlling the color temperature of each unit of the lighting independent unit network based on the color temperature distribution characteristics of the light source, and generating an adaptive unit color temperature control strategy;

[0090] Step S6: Obtain pedestrian movement position data; based on the pedestrian movement position data, make light source control optimization decisions on the natural light compensation control strategy, the adaptive unit color temperature control strategy and the dynamic energy-saving control strategy, and build a lighting intelligent control model to perform lighting control operations.

[0091] The present invention can accurately describe the wavelength distribution of natural light through wavelength quantitative analysis, and provide a basic reference for subsequent lighting control. The interval wavelength parameter characterization helps to simplify complex spectral information into interval form, which is convenient for subsequent processing and analysis. Luminous flux analysis and color temperature distribution feature mining help to understand the light output characteristics of LED lamp arrays and provide basic data for lighting control. After obtaining the color temperature distribution characteristics of the light source, the color temperature distribution of the light source can be better understood, which provides a basis for subsequent color temperature control. The construction of an independent lighting unit network allows lighting to be more finely controlled and adjusted, improving the accuracy and controllability of lighting. The establishment of an independent lighting unit network helps to achieve personalized adjustment of lighting in different areas and improve lighting adaptability and flexibility.

[0092] The calculation of natural light compensation demand can accurately calculate the lighting compensation demand according to the wavelength characteristics of natural light to ensure the quality and comfort of indoor lighting. The construction of precise lighting compensation control strategy helps to match indoor natural light with human physiological needs and improve the comfort of living and working environment. The unit-by-unit dynamic color temperature control strategy can adjust the color temperature of the light source according to the needs of different areas to improve the comfort and adaptability of indoor lighting. Generating adaptive unit color temperature control strategy helps to adjust the color temperature of the light source according to actual needs and improve the adaptability and comfort of the indoor environment. The light source control optimization decision can adjust the lighting and color temperature in real time according to pedestrian location data to improve energy efficiency and comfort. The construction of intelligent lighting control model helps to realize the intelligent management of indoor lighting and improve the accuracy and intelligence level of lighting control.

[0093] In the embodiment of the present invention, refer to Figure 1 , is a schematic flow chart of the steps of a method for controlling illumination of a fluorescent powder-free multi-primary color LED street lamp according to the present invention. In this example, the steps of the method for controlling illumination of a fluorescent powder-free multi-primary color LED street lamp include:

[0094] Step S1: obtaining a natural light spectrum parameter sample set; performing wavelength quantitative analysis on the natural light spectrum parameter sample set to obtain interval wavelength parameter representation;

[0095] In this embodiment, a suitable portable spectrometer is selected, which can measure the spectral distribution of natural light and output spectral data. Different time periods and different locations are selected to measure the spectral parameters of natural light, for example, morning, noon, evening, sunny days, cloudy days, etc. The spectrometer is used to measure natural light and collect spectral data of natural light. The spectral data usually includes wavelength information and light intensity information. The collected spectral data is formatted, for example, the wavelength information is converted into nanometers (nm), and the light intensity information is converted into light intensity per unit area (for example, lux).

[0096] The collected spectral data are organized into a sample set, where each sample corresponds to the natural light spectral data of a time period and location. The natural light spectral data are divided according to wavelength. For example, the visible spectrum is divided into red light, orange light, yellow light, green light, blue light, indigo light, and purple light intervals. The spectral data of each wavelength interval are quantitatively analyzed. For example, the average light intensity, peak light intensity, valley light intensity, and light intensity variation range of each wavelength interval are calculated. The quantitative analysis results of each wavelength interval are organized into a table to form an interval wavelength parameter representation, which includes parameters such as the average light intensity, peak light intensity, valley light intensity, and light intensity variation range of each wavelength interval.

[0097] Step S2: obtaining light source output parameters based on the LED lamp array; performing luminous flux analysis on the light source output parameters, and mining color temperature distribution characteristics, thereby obtaining light source color temperature distribution characteristics;

[0098] In this embodiment, information of the LED lamp array is obtained, including the type, power, beam angle, position coordinates, etc. of each LED lamp, and the LED lamp array is measured using a photometer or other optical measuring equipment to obtain the light source output parameters of each LED lamp, such as luminous flux, color temperature, color rendering, etc. The measured light source output parameters are sorted to form a light source output parameter table.

[0099] Each LED lamp corresponds to a set of light source output parameters. The luminous flux in the light source output parameters is analyzed. For example, the luminous flux, total luminous flux, and luminous flux distribution of each LED lamp are calculated. The color temperature in the light source output parameters is analyzed to explore the distribution characteristics of the color temperature. For example, the average value, standard deviation, and variation range of the color temperature are calculated. The color temperature distribution characteristic analysis results are organized into a table to form a light source color temperature distribution characteristic table.

[0100] Step S3: Divide the LED light array into independent units, perform illumination distribution field fitting, and construct an illumination independent unit network;

[0101] In this embodiment, a suitable unit division standard is selected according to the structure and function of the LED lamp array. For example, the division is performed according to the arrangement of the LED lamps, the beam angle, the power, etc., and also according to the area that needs to be illuminated. A suitable unit division method is used, such as grid division, cluster division, area division, etc., to divide the LED lamp array into multiple independent units, and parameters are defined for each independent unit, such as unit number, position coordinates, light source type, power, etc.

[0102] Select a suitable lighting model, such as a point light source model, a surface light source model, a volume light source model, etc., to simulate the lighting distribution of each independent unit, use a photometer or other optical measurement equipment to measure each independent unit, collect lighting data, and use a fitting algorithm, such as the least squares method, a neural network, etc., to fit the lighting distribution field of each independent unit according to the lighting data and the lighting model, and integrate the lighting distribution field of each independent unit into a network to form a lighting independent unit network.

[0103] Step S4: calculating the natural light compensation demand of the lighting independent unit network based on the interval wavelength parameter characterization, and performing precise control of the lighting compensation to construct a natural light compensation control strategy;

[0104] In this embodiment, the target light intensity of each independent unit is set, for example, the target light intensity is set according to lighting requirements and safety standards, and the natural light compensation requirement of each independent unit is calculated based on the natural light spectrum data, the target light intensity and the interval wavelength parameter characterization. For example, if the light intensity of natural light is not sufficient to meet the target light intensity, natural light compensation is required. According to the natural light compensation requirement, the light source output of each independent unit is controlled, for example, the brightness, color temperature, switch, etc. of the light source are adjusted.

[0105] Use appropriate compensation algorithms, such as proportional compensation, linear compensation, nonlinear compensation, etc., to precisely control the light source to achieve natural light compensation. Set the compensation accuracy according to actual needs, for example, set the range of compensation error, integrate the rules for natural light compensation demand calculation and precise control of lighting compensation into one strategy to form a natural light compensation control strategy, and define the parameters of the natural light compensation control strategy, such as compensation threshold, compensation ratio, compensation time, etc.

[0106] Step S5: dynamically controlling the color temperature of each unit of the lighting independent unit network based on the color temperature distribution characteristics of the light source, and generating an adaptive unit color temperature control strategy;

[0107] In this embodiment, the color temperature of the light source of each independent unit is controlled according to the color temperature distribution characteristics of the light source and the color temperature target value. For example, PWM dimming technology or other color temperature control technology is used to dynamically adjust the color temperature of the light source of each independent unit according to the actual lighting effect and the color temperature target value to achieve the best lighting effect. The rules of color temperature target value setting, color temperature control and color temperature adjustment are integrated into one strategy to form an adaptive unit color temperature control strategy, and the parameters of the adaptive unit color temperature control strategy are defined, such as the color temperature adjustment range, color temperature adjustment speed, color temperature adjustment threshold, etc.

[0108] Step S6: Obtain pedestrian movement position data; based on the pedestrian movement position data, make light source control optimization decisions on the natural light compensation control strategy, the adaptive unit color temperature control strategy and the dynamic energy-saving control strategy, and build a lighting intelligent control model to perform lighting control operations.

[0109] In this embodiment, a suitable source of pedestrian movement position data is selected, for example, using cameras, sensors, mobile phone positioning and other technologies to obtain pedestrian movement position data, and the obtained pedestrian movement position data is formatted, for example, the data is converted into longitude and latitude coordinates, timestamps, etc., and the pedestrian movement position data is pre-processed, for example, noise data is removed, data is smoothed, data is clustered, etc. According to the pedestrian movement position data, the lighting area is divided into multiple sub-areas, for example, according to factors such as pedestrian density and activity type.

[0110] According to the pedestrian movement position data, the natural light compensation control strategy, the adaptive unit color temperature control strategy and the dynamic energy-saving control strategy are adjusted. For example, the light intensity is increased in pedestrian-dense areas and reduced in pedestrian-sparse areas. Based on the pedestrian movement position data and the strategy adjustment results, light source control optimization decisions are made, such as selecting the appropriate lighting mode, adjusting the light brightness, controlling the light switch, etc. The appropriate model structure is selected, such as a rule-based model, a machine learning-based model, etc., to build an intelligent lighting control model.

[0111] Use pedestrian movement position data and light source control optimization decision results to train the intelligent lighting control model, for example, use supervised learning, reinforcement learning and other methods for training, and evaluate the intelligent lighting control model, for example, evaluate the accuracy, efficiency, robustness, etc. of the model. According to the output results of the intelligent lighting control model, generate light source control instructions, for example, control light brightness, color temperature, switch, etc., send the light source control instructions to the lighting system, execute lighting control operations, establish a feedback mechanism, monitor lighting effects in real time, adjust the light source control instructions according to actual conditions, and realize intelligent lighting control.

[0112] In this embodiment, refer to Figure 2 , is a flowchart of detailed implementation steps of step S1. In this embodiment, the detailed implementation steps of step S1 include:

[0113] Step S11: performing high-frequency spectrum sampling on ambient natural light based on a spectrum detection sensor, thereby obtaining a natural light spectrum parameter sample set;

[0114] Step S12: performing Fourier transform processing on the natural light spectrum parameter sample set to generate natural light spectrum frequency domain data;

[0115] Step S13: performing frequency domain characteristic change analysis on the natural light spectrum frequency domain data, thereby generating a spectrum frequency domain curve;

[0116] Step S14: performing curve morphology analysis on the spectrum frequency domain curve to generate natural light intensity data;

[0117] Step S15: performing wavelength quantitative analysis on the spectrum frequency domain curve based on the natural light intensity data, thereby obtaining interval wavelength parameter representation.

[0118] In this embodiment, a spectral detection sensor, such as a spectrometer, is used to perform high-frequency sampling of natural light in the environment. The spectrometer usually uses a grating or a prism to decompose natural light into a spectrum of different wavelengths, and detects the intensity of light of different wavelengths through a sensor. The sampling frequency needs to be high enough to capture the rapid changes in the natural light spectrum, for example, hundreds or thousands of times per second. The sampling results will be represented by a series of data points, each data point corresponding to a specific wavelength and a corresponding intensity value. The natural light spectrum parameter sample set is Fourier transformed. The Fourier transform is a mathematical tool that converts a time domain signal into a frequency domain signal. In spectral analysis, the Fourier transform converts the spectral parameter sample set from the wavelength domain to the frequency domain. The frequency domain data reflects the intensity of different frequency components in the natural light spectrum. The result after the Fourier transform will be a new set of data points, each data point corresponding to a specific frequency and a corresponding intensity value.

[0119] The natural light spectrum frequency domain data is analyzed to identify the intensity change trends of different frequency components. These change trends reflect the characteristics of the natural light spectrum, for example, the enhancement or weakening of specific frequency components. These change trends are plotted into curves to form spectral frequency domain curves. The spectral frequency domain curves intuitively show the changes in the natural light spectrum in the frequency domain. The spectral frequency domain curves are morphologically analyzed, for example, the peak value, valley value, slope and other features of the curve are identified. These features reflect the energy distribution of the natural light spectrum. Based on these features, the illumination intensity of natural light is calculated. The obtained natural light illumination intensity data is used to perform wavelength quantitative analysis on the obtained spectral frequency domain curves. The changes in spectral intensity within a specific wavelength range are analyzed, for example, the peak value and valley value within a specific wavelength range are identified. These analysis results are organized into interval wavelength parameter representations, for example, the average intensity, peak intensity, valley intensity, etc. within a specific wavelength range are recorded. The interval wavelength parameter representations describe the characteristics of the natural light spectrum in more detail and provide more accurate data for subsequent applications.

[0120] In this embodiment, the specific steps of step S15 are:

[0121] Performing filtering and smoothing optimization on the spectrum frequency domain curve to generate a smooth optimized spectrum frequency domain curve;

[0122] Perform wavelength quantitative analysis on the smooth optimized spectrum frequency domain curve to obtain the wavelength parameters of the curve;

[0123] Based on the wavelength parameters of the curve, the smooth optimized spectrum frequency domain curve is divided into wavelength intervals to obtain multiple wavelength interval curves;

[0124] Based on the natural light intensity data, the average light intensity of multiple wavelength interval curves is calculated to obtain the average light intensity value of the wavelength interval;

[0125] Perform light intensity distribution trend analysis on multiple wavelength interval curves to obtain wavelength interval light intensity distribution trend data;

[0126] The wavelength parameter characteristics of the wavelength interval average light intensity value and the wavelength interval light intensity distribution trend data are mined to obtain the interval wavelength parameter representation.

[0127] In this embodiment, a suitable filtering method is selected, such as moving average filtering, Gaussian filtering, median filtering, etc., and a suitable filter is selected according to the noise characteristics and requirements of the spectral frequency domain curve. According to the filtering method, filtering parameters, such as window size, filter variance, etc., are set to achieve the best smoothing effect, and the spectral frequency domain curve is filtered and smoothed to remove noise to obtain a smoothed and optimized spectral frequency domain curve. The smoothed and optimized spectral frequency domain curve is quantitatively analyzed to determine the changes in light intensity in different wavelength bands, such as peak values, valley values, inflection points, etc., and the analysis results are organized into curve wavelength parameters, such as light intensity values ​​and wavelength ranges in different wavelength bands, according to the curve wavelength parameters.

[0128] The smoothed optimized spectral frequency domain curve is divided into multiple wavelength intervals, such as visible light region, near infrared region, far infrared region, etc. The spectral frequency domain curve of each wavelength interval is extracted separately to form multiple wavelength interval curves. For each wavelength interval curve, its average light intensity is calculated to obtain the average light intensity value of the wavelength interval, and the shape and change trend of each wavelength interval curve are analyzed, such as monotonically increasing, monotonically decreasing, peak value, valley value, etc. The analysis results are organized into wavelength interval light intensity distribution trend data, such as light intensity change trend, peak position, valley value position, etc.

[0129] Analyze the average light intensity value in the wavelength interval and the light intensity distribution trend data in the wavelength interval, extract meaningful wavelength parameter characteristics, such as the average light intensity difference in different wavelength intervals, the change law of light intensity distribution trend, etc., and organize the mined wavelength parameter characteristics into interval wavelength parameter representation for subsequent thin film production process control and optimization.

[0130] In this embodiment, refer to Figure 3 , is a flowchart of detailed implementation steps of step S2. In this embodiment, the detailed implementation steps of step S2 include:

[0131] Step S21: monitoring the current light source output of the LED lamp array to obtain light source output parameters;

[0132] Step S22: performing luminous flux analysis on the light source output parameters to generate light source luminous flux data;

[0133] Step S23: performing uniformity distribution calculation on the light source luminous flux data to obtain light source luminous flux distribution data;

[0134] Step S24: performing time series distribution trend evolution analysis on the light source luminous flux distribution data to generate luminous flux distribution trend evolution data;

[0135] Step S25: mining the color temperature distribution characteristics of the LED lamp array based on the luminous flux distribution trend evolution data, thereby obtaining the color temperature distribution characteristics of the light source.

[0136] In this embodiment, the monitoring parameters include the brightness, color temperature, spectral distribution, etc. of the light source, and the light source output parameter data of each LED lamp is collected, for example, the brightness value, color temperature value, spectral distribution data, etc. of each LED lamp, and the collected data is sorted to form a light source output parameter data table. Each LED lamp corresponds to a set of light source output parameters. The luminous flux of each LED lamp is calculated according to the light source output parameters, such as light intensity, luminous area, etc. The calculated luminous flux data is stored to form light source luminous flux data, and the uniformity distribution calculation of the light source luminous flux data is performed, for example, the deviation of the luminous flux of each LED lamp from the average luminous flux is calculated to evaluate the uniformity of the luminous flux.

[0137] The calculated luminous flux distribution data is stored to form light source luminous flux distribution data, and time series analysis is performed on the light source luminous flux distribution data. For example, the luminous flux change trend of each LED lamp is analyzed over time to identify the law of luminous flux change. The analysis results are organized into luminous flux distribution trend evolution data, such as the luminous flux change trend and change rate of each LED lamp. The luminous flux distribution trend evolution data is analyzed to identify the color temperature change trend of different LED lamps, such as color temperature drift, color temperature difference, etc. The mined color temperature distribution features are organized into light source color temperature distribution features, such as average color temperature, color temperature deviation, color temperature change trend, etc.

[0138] In this embodiment, reference Figure 4 The above is a schematic flow chart of the detailed implementation steps of step S3. In this embodiment, the detailed implementation steps of step S3 include:

[0139] Step S31: dividing the LED lamp array into independent units, thereby obtaining a plurality of LED lamp independent units;

[0140] Step S32: quantifying the dynamic illumination distribution of multiple LED lamp independent units based on the luminous flux distribution trend evolution data, thereby obtaining dynamic illumination distribution data of each independent unit;

[0141] Step S33: Fit the illumination distribution field of each independent unit's dynamic illumination distribution data to construct an illumination independent unit network.

[0142] In this embodiment, the standard for dividing independent units is determined according to the structure and function of the LED lamp array. For example, each LED lamp is regarded as an independent unit, or multiple LED lamps form an independent unit. A suitable unit division method is adopted, such as division according to the physical position of the LED lamp, control signal, etc., and the information of each independent unit after division is recorded, such as unit number, number of LED lamps, position coordinates, etc. The luminous flux of each LED lamp is distributed to the independent unit to which it belongs according to the luminous flux distribution trend evolution data.

[0143] Based on the luminous flux distribution result, the illumination intensity of each independent unit is calculated, and the dynamic illumination distribution data of each independent unit is obtained according to the time series data. The dynamic illumination distribution data of each independent unit is stored to form the dynamic illumination distribution data of each independent unit. A suitable model is selected to fit the dynamic illumination distribution data of each independent unit, such as a Gaussian model, a polynomial model, etc. The dynamic illumination distribution data of each independent unit is parameter-fitted using the fitting model to obtain the illumination distribution field model of each independent unit. The illumination distribution field models of all independent units are integrated to form an illumination independent unit network, which describes the illumination distribution of the entire LED lamp array.

[0144] In this embodiment, step S4 includes the following steps:

[0145] Step S41: calculating the natural light compensation demand of the lighting independent unit network based on the interval wavelength parameter characterization, thereby obtaining a simulated natural light compensation demand value of each independent unit;

[0146] Step S42: performing unit compensation difference analysis on the simulated natural light compensation requirement value of each independent unit to generate an independent unit compensation difference gradient;

[0147] Step S43: performing uniform calculation of illumination compensation rate based on independent unit compensation difference gradient to generate unit network compensation uniform rate;

[0148] Step S44: Use the unit network compensation uniform rate to accurately control the illumination compensation of the illumination independent unit network, and construct a natural light compensation control strategy.

[0149] In this embodiment, the wavelength distribution and light intensity of natural light are analyzed, and the natural light compensation requirements of each independent unit in different wavelength bands are calculated according to the light distribution field model of each independent unit. The natural light compensation requirements of each independent unit in different wavelength bands are integrated to obtain the simulated natural light compensation requirement value of each independent unit. The simulated natural light compensation requirement values ​​of each independent unit are compared, and the compensation differences between each independent unit are calculated. The compensation differences of each independent unit are sorted according to size to form an independent unit compensation difference gradient for subsequent compensation strategy formulation.

[0150] According to the compensation difference gradient of independent units, the light compensation rate is distributed to each independent unit to ensure that the unit with larger compensation difference obtains a higher compensation rate. The compensation rate of each independent unit is integrated to form a unit network compensation uniform rate for subsequent compensation regulation. According to the unit network compensation uniform rate, the light intensity of each independent unit is precisely regulated to achieve natural light compensation. The light intensity of each independent unit is monitored in real time, and the compensation rate is adjusted according to the monitoring results to ensure the stability of the compensation effect. The light compensation control and compensation effect monitoring are integrated to form a natural light compensation regulation strategy for automatically adjusting the light intensity of the LED light array to simulate the natural light environment.

[0151] In this embodiment, the specific steps of step S41 are:

[0152] Quantify the illumination intensity of each unit in the illumination independent unit network and generate the illumination intensity value of each independent unit;

[0153] Based on the interval wavelength parameter representation, the natural light variation characteristics are simulated to obtain the natural light wavelength simulation parameters;

[0154] The natural light compensation requirement is calculated for the light intensity value of each independent unit based on the natural light wavelength simulation parameter, thereby obtaining the simulated natural light compensation requirement value of each independent unit.

[0155] In this embodiment, a photometer or other optical measuring equipment is used to measure the light intensity of each independent unit in the lighting independent unit network. The measurement parameters include light intensity, color temperature, spectral distribution, etc. The light intensity data of each independent unit is collected, for example, the light intensity value, color temperature value, spectral distribution data, etc. of each independent unit. The collected data is sorted to form a light intensity value table for each independent unit. Each independent unit corresponds to a light intensity value. Based on the interval wavelength parameter characterization, the wavelength distribution of natural light and the law of light intensity variation are analyzed, and a suitable model is selected to simulate the wavelength variation characteristics of natural light, such as a sinusoidal model, a polynomial model, etc.

[0156] The fitting model is used to perform parameter fitting on the natural light data to obtain natural light wavelength simulation parameters, such as wavelength variation amplitude and period, etc. The light intensity value of each independent unit is compared with the natural light wavelength simulation parameters, and the light intensity deviation of each independent unit in different wavelength ranges is calculated. According to the light intensity deviation, the simulated natural light compensation demand value of each independent unit is calculated. The compensation demand value reflects the light intensity that needs to be increased or decreased for each independent unit to simulate the lighting environment of natural light. The simulated natural light compensation demand values ​​of each independent unit are organized into a table to form a simulated natural light compensation demand value table for each independent unit.

[0157] In this embodiment, step S5 includes the following steps:

[0158] Step S51: performing independent unit color temperature calculation on the illumination independent unit network based on the light source color temperature distribution characteristics to generate a plurality of independent unit color temperature values;

[0159] Step S52: performing color temperature offset analysis on multiple independent unit color temperature values ​​based on preset LED light source theoretical color temperature parameters to obtain independent unit color temperature offset data;

[0160] Step S53: performing color temperature offset distribution analysis on the independent unit color temperature offset data to obtain a color temperature offset distribution field;

[0161] Step S54: dynamically controlling the color temperature of each lighting independent unit network unit by unit according to the color temperature offset distribution field, and generating an adaptive unit color temperature control strategy.

[0162] In this embodiment, the color temperature value of each independent unit is calculated based on the color temperature distribution characteristics of the light source and combined with the position information of each independent unit. For example, the color temperature value of each independent unit is calculated based on the average color temperature and the color temperature standard deviation, and the color temperature value is adjusted considering the color temperature change amplitude. The color temperature value of each independent unit is organized into a table to form an independent unit color temperature value table, and the theoretical color temperature parameters of the LED light source are preset, such as the theoretical color temperature value of the LED light source, the color temperature deviation range, etc. The color temperature value of each independent unit is compared with the preset theoretical color temperature parameters of the LED light source, and the color temperature offset value of each independent unit is calculated. The color temperature offset value reflects the deviation between the actual color temperature of each independent unit and the theoretical color temperature. The color temperature offset value of each independent unit is organized into a table to form an independent unit color temperature offset data table.

[0163] Analyze the color temperature offset data of independent units, identify the distribution pattern of color temperature offset, for example, the concentrated area of ​​color temperature offset, the gradient of color temperature offset, etc., visualize the color temperature offset distribution analysis results to form a color temperature offset distribution field, for example, draw a color temperature offset distribution diagram, or establish a color temperature offset distribution model, etc. According to the color temperature offset distribution field, dynamically adjust the color temperature of each independent unit, for example, in areas with larger color temperature offset, increase the amplitude of color temperature control to reduce color temperature deviation; in areas with smaller color temperature offset, reduce the amplitude of color temperature control to maintain color temperature stability, and dynamically adjust the color temperature control strategy of each independent unit according to changes in the color temperature offset distribution field to ensure that the entire lighting independent unit network can maintain a consistent color temperature environment.

[0164] In this embodiment, step S6 includes the following steps:

[0165] Step S61: obtaining pedestrian movement position data based on sensors;

[0166] Step S62: performing mobile positioning tracking on the pedestrian's mobile position data to generate a pedestrian's mobile positioning trajectory;

[0167] Step S63: calculating the street lamp distance change of the pedestrian movement positioning trajectory, thereby obtaining pedestrian distance change data;

[0168] Step S64: performing critical lighting analysis on pedestrian distance change data based on the preset maximum lighting distance of LED street lamps, and performing street lamp energy-saving dynamic control to generate a dynamic energy-saving control strategy;

[0169] Step S65: Optimize the light source control decision for the natural light compensation control strategy, the adaptive unit color temperature control strategy and the dynamic energy-saving control strategy, and build a lighting intelligent control model to perform lighting control operations.

[0170] In this embodiment, a suitable sensor is selected, such as a camera, an infrared sensor, an ultrasonic sensor, etc., to obtain pedestrian movement position data. The sensor is used to collect pedestrian movement position data, such as the coordinate position, movement direction, movement speed, etc. of the pedestrian. The collected data is formatted, for example, the coordinate position is converted into longitude and latitude coordinates, and the movement speed is converted into meters per second, etc.

[0171] Using a positioning and tracking algorithm, such as a Kalman filter and a particle filter, etc., the pedestrian movement position data is processed to track the movement trajectory of the pedestrian. According to the result of the positioning and tracking algorithm, a pedestrian movement positioning trajectory is generated, such as drawing a pedestrian movement trajectory map, or storing pedestrian movement trajectory data, etc. The location information of the street lamp is obtained, such as the coordinate position and height of the street lamp. According to the pedestrian movement positioning trajectory and the street lamp location information, the distance change between the pedestrian and the street lamp is calculated, such as calculating the distance change between the pedestrian and each street lamp, or calculating the distance change between the pedestrian and the nearest street lamp. The calculated distance change data is sorted into a table to form a pedestrian distance change data table. The maximum lighting distance of the LED lighting street lamp is preset, for example, the maximum lighting distance of the street lamp is determined according to parameters such as the power and beam angle of the street lamp. According to the pedestrian distance change data and the maximum lighting distance, it is judged whether the pedestrian is within the lighting range of the street lamp. For example, if the distance between the pedestrian and the street lamp is less than the maximum lighting distance, the pedestrian is considered to be within the lighting range; otherwise, the pedestrian is considered to be within the non-lighting range.

[0172] According to the critical lighting analysis results, the street lights are dynamically controlled. For example, when pedestrians are in the non-lighting range, the street lights are dimmed or turned off to save energy; when pedestrians are in the lighting range, the street lights are kept bright or turned on to ensure the safety of pedestrians. The dynamic energy-saving control rules are organized into a table to form a dynamic energy-saving control strategy table. According to the natural light compensation control strategy, the adaptive unit color temperature control strategy and the dynamic energy-saving control strategy.

[0173] Comprehensively consider factors such as lighting environment, energy-saving requirements, and safety requirements to make control optimization decisions for light sources. For example, when there is sufficient natural light, reduce the brightness of artificial light sources; when pedestrians approach street lights, increase the brightness of street lights; when the lighting environment changes, adjust the color temperature of the light source, etc. Integrate the light source control optimization decision rules into a model to form a lighting intelligent control model. The model can automatically adjust the control parameters of the light source according to different scenarios and needs to achieve intelligent lighting control. Apply the lighting intelligent control model to the actual lighting control system to perform lighting control operations, such as controlling the brightness, color temperature, and switching of street lights.

[0174] Example:

[0175] The camera is used to obtain pedestrian movement position data, such as the pedestrian's coordinate position, movement direction, movement speed, etc. The Kalman filter algorithm is used to process the pedestrian movement position data, track the pedestrian's movement trajectory, and generate the pedestrian movement positioning trajectory.

[0176] According to the pedestrian's moving positioning trajectory and street lamp position information, the distance change between the pedestrian and the street lamp is calculated. For example, the distance between the pedestrian and the street lamp gradually increases from 10 meters to 25 meters. According to the pedestrian distance change data and the maximum lighting distance, it is determined whether the pedestrian is within the lighting range of the street lamp.

[0177] For example, when the distance between a pedestrian and a street lamp is less than 20 meters, the pedestrian is in the lighting range; when the distance between a pedestrian and a street lamp is greater than 20 meters, the pedestrian is in the non-lighting range. According to the critical lighting analysis results, the street lamp is dynamically controlled, for example, when the pedestrian is in the non-lighting range, the brightness of the street lamp is reduced or turned off; when the pedestrian is in the lighting range, the brightness of the street lamp is maintained or turned on.

[0178] According to the natural light compensation control strategy, adaptive unit color temperature control strategy and dynamic energy-saving control strategy, the lighting environment, energy-saving requirements, safety requirements and other factors are comprehensively considered to make control optimization decisions for street lights. For example, when there is sufficient natural light, the brightness of the street lights is reduced; when pedestrians are close to the street lights, the brightness of the street lights is increased; when the lighting environment changes, the color temperature of the street lights is adjusted, etc. The light source control optimization decision rules are integrated into a model to form a lighting intelligent control model, which is applied to the actual street light control system to perform lighting control operations.

[0179] In this embodiment, a lighting control system for a phosphor-free multi-primary color LED street lamp is provided, which is used to execute the lighting control method for the phosphor-free multi-primary color LED street lamp as described above, including:

[0180] The interval wavelength module is used to obtain a sample set of natural light spectrum parameters; perform wavelength quantitative analysis on the sample set of natural light spectrum parameters to obtain interval wavelength parameter representation;

[0181] The color temperature distribution module is used to obtain the light source output parameters based on the LED light array; perform luminous flux analysis on the light source output parameters and mine the color temperature distribution characteristics to obtain the light source color temperature distribution characteristics;

[0182] Independent unit module, used to divide the LED light array into independent units, fit the illumination distribution field, and build an illumination independent unit network;

[0183] The natural light compensation module is used to calculate the natural light compensation demand of the independent lighting unit network based on the interval wavelength parameter characterization, and to perform precise control of the lighting compensation and build a natural light compensation control strategy;

[0184] A color temperature control module is used to dynamically control the color temperature of each unit of the lighting independent unit network based on the color temperature distribution characteristics of the light source, and generate an adaptive unit color temperature control strategy;

[0185] The intelligent control module is used to obtain pedestrian movement position data; based on the pedestrian movement position data, the natural light compensation control strategy, the adaptive unit color temperature control strategy and the dynamic energy-saving control strategy are used to make light source control optimization decisions, and a lighting intelligent control model is constructed to perform lighting control operations.

[0186] The present invention obtains a sample set of natural light spectrum parameters and performs quantitative wavelength analysis, and the system obtains interval wavelength parameter representation. The acquisition of interval wavelength parameters understands the spectral characteristics. The system obtains the color temperature distribution characteristics of the light source through analysis of the light source output parameters and mining of color temperature distribution characteristics. The acquisition of the light source color temperature distribution characteristics evaluates the lighting needs of different areas and provides a basis for color temperature control. The system constructs a lighting independent unit network through independent unit division processing and lighting distribution field fitting. The establishment of the lighting independent unit network analyzes and manages the lighting conditions of different areas, providing a basis for subsequent regulation.

[0187] Through the calculation and precise control of natural light compensation needs, the system constructs a natural light compensation control strategy. The implementation of the natural light compensation control strategy is adjusted according to the ambient light conditions to improve the lighting effect and energy-saving effect. Through the generation of dynamic color temperature control strategy, the system realizes color temperature control of each unit. The application of adaptive unit color temperature control strategy adjusts the color temperature of the light source according to the demand to provide a more comfortable lighting environment. By obtaining pedestrian movement position data and making light source control optimization decisions, the system constructs an intelligent lighting control model. The establishment of the intelligent lighting control model adjusts the lighting parameters according to real-time needs, provides intelligent lighting management, and saves energy at the same time.

[0188] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0189] 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 method for controlling illumination of a phosphor-free multi-primary color LED street lamp, characterized in that: The phosphor-free multi-primary color LED lighting street lamp includes an LED lamp array, including the following steps: Step S1: obtaining a natural light spectrum parameter sample set; performing wavelength quantitative analysis on the natural light spectrum parameter sample set to obtain interval wavelength parameter representation; Step S2: obtaining light source output parameters based on the LED lamp array; performing luminous flux analysis on the light source output parameters, and mining color temperature distribution characteristics, thereby obtaining light source color temperature distribution characteristics; Step S3: Divide the LED light array into independent units, perform illumination distribution field fitting, and construct an illumination independent unit network; Step S4: calculating the natural light compensation demand of the lighting independent unit network based on the interval wavelength parameter characterization, and performing precise control of the lighting compensation to construct a natural light compensation control strategy; Step S5: dynamically controlling the color temperature of each unit of the lighting independent unit network based on the color temperature distribution characteristics of the light source, and generating an adaptive unit color temperature control strategy; Step S6: Obtain pedestrian movement position data; based on the pedestrian movement position data, make light source control optimization decisions on the natural light compensation control strategy, the adaptive unit color temperature control strategy and the dynamic energy-saving control strategy, and build a lighting intelligent control model to perform lighting control operations; The specific steps of step S4 are: Step S41: calculating the natural light compensation demand of the lighting independent unit network based on the interval wavelength parameter characterization, thereby obtaining a simulated natural light compensation demand value of each independent unit; Step S42: performing unit compensation difference analysis on the simulated natural light compensation requirement value of each independent unit to generate an independent unit compensation difference gradient; Step S43: Calculating the uniform rate of illumination compensation based on the independent unit compensation difference gradient to generate a unit network compensation uniform rate; Step S44: Use the unit network compensation uniform rate to accurately control the illumination compensation of the illumination independent unit network, and construct a natural light compensation control strategy.

2. The illumination control method of the phosphor-free multi-primary color LED lighting street lamp according to claim 1, characterized in that: The specific steps of step S1 are: Step S11: performing high-frequency spectrum sampling on ambient natural light based on a spectrum detection sensor, thereby obtaining a natural light spectrum parameter sample set; Step S12: performing Fourier transform processing on the natural light spectrum parameter sample set to generate natural light spectrum frequency domain data; Step S13: performing frequency domain characteristic change analysis on the natural light spectrum frequency domain data, thereby generating a spectrum frequency domain curve; Step S14: performing curve morphology analysis on the spectrum frequency domain curve to generate natural light intensity data; Step S15: performing wavelength quantitative analysis on the spectrum frequency domain curve based on the natural light intensity data, thereby obtaining interval wavelength parameter representation.

3. The illumination control method of the phosphor-free multi-primary color LED lighting street lamp according to claim 2, characterized in that: The specific steps of step S15 are: Performing filtering and smoothing optimization on the spectrum frequency domain curve to generate a smooth optimized spectrum frequency domain curve; Perform wavelength quantitative analysis on the smooth optimized spectrum frequency domain curve to obtain the wavelength parameters of the curve; Based on the wavelength parameters of the curve, the smooth optimized spectrum frequency domain curve is divided into wavelength intervals to obtain multiple wavelength interval curves; Based on the natural light intensity data, the average light intensity of multiple wavelength interval curves is calculated to obtain the average light intensity value of the wavelength interval; Perform light intensity distribution trend analysis on multiple wavelength interval curves to obtain wavelength interval light intensity distribution trend data; The wavelength parameter characteristics of the wavelength interval average light intensity value and the wavelength interval light intensity distribution trend data are mined to obtain the interval wavelength parameter representation.

4. The illumination control method of the phosphor-free multi-primary color LED lighting street lamp according to claim 1, characterized in that: The specific steps of step S2 are: Step S21: monitoring the current light source output of the LED lamp array to obtain light source output parameters; Step S22: performing luminous flux analysis on the light source output parameters to generate light source luminous flux data; Step S23: performing uniformity distribution calculation on the light source luminous flux data to obtain light source luminous flux distribution data; Step S24: performing time series distribution trend evolution analysis on the light source luminous flux distribution data to generate luminous flux distribution trend evolution data; Step S25: mining the color temperature distribution characteristics of the LED lamp array based on the luminous flux distribution trend evolution data, thereby obtaining the color temperature distribution characteristics of the light source.

5. The illumination control method of the phosphor-free multi-primary color LED lighting street lamp according to claim 1, characterized in that: The specific steps of step S3 are: Step S31: dividing the LED lamp array into independent units, thereby obtaining a plurality of LED lamp independent units; Step S32: quantifying the dynamic illumination distribution of multiple LED lamp independent units based on the luminous flux distribution trend evolution data, thereby obtaining dynamic illumination distribution data of each independent unit; Step S33: Fit the illumination distribution field of each independent unit's dynamic illumination distribution data to construct an illumination independent unit network.

6. The illumination control method of the phosphor-free multi-primary color LED lighting street lamp according to claim 1, characterized in that: The specific steps of step S41 are: Quantify the illumination intensity of each unit in the illumination independent unit network and generate the illumination intensity value of each independent unit; Based on the interval wavelength parameter representation, the natural light variation characteristics are simulated to obtain the natural light wavelength simulation parameters; The natural light compensation requirement is calculated for the light intensity value of each independent unit based on the natural light wavelength simulation parameter, thereby obtaining the simulated natural light compensation requirement value of each independent unit.

7. The illumination control method of the phosphor-free multi-primary color LED lighting street lamp according to claim 1, characterized in that: The specific steps of step S5 are: Step S51: performing independent unit color temperature calculation on the illumination independent unit network based on the light source color temperature distribution characteristics to generate a plurality of independent unit color temperature values; Step S52: performing color temperature offset analysis on multiple independent unit color temperature values ​​based on preset LED light source theoretical color temperature parameters to obtain independent unit color temperature offset data; Step S53: performing color temperature offset distribution analysis on the independent unit color temperature offset data to obtain a color temperature offset distribution field; Step S54: dynamically controlling the color temperature of each lighting independent unit network unit by unit according to the color temperature offset distribution field, and generating an adaptive unit color temperature control strategy.

8. The illumination control method of the phosphor-free multi-primary color LED lighting street lamp according to claim 1, characterized in that: The specific steps of step S6 are: Step S61: obtaining pedestrian movement position data based on sensors; Step S62: performing mobile positioning tracking on the pedestrian's mobile position data to generate a pedestrian's mobile positioning trajectory; Step S63: calculating the street lamp distance change of the pedestrian movement positioning trajectory, thereby obtaining pedestrian distance change data; Step S64: performing critical lighting analysis on pedestrian distance change data based on the preset maximum lighting distance of LED street lamps, and performing street lamp energy-saving dynamic control to generate a dynamic energy-saving control strategy; Step S65: Optimize the light source control decision for the natural light compensation control strategy, the adaptive unit color temperature control strategy and the dynamic energy-saving control strategy, and build a lighting intelligent control model to perform lighting control operations.

9. A lighting control system for a phosphor-free multi-primary color LED lighting street lamp, characterized in that: The method for executing the illumination control method of the phosphor-free multi-primary color LED lighting street lamp according to claim 1 comprises: The interval wavelength module is used to obtain a sample set of natural light spectrum parameters; perform wavelength quantitative analysis on the sample set of natural light spectrum parameters to obtain interval wavelength parameter representation; The color temperature distribution module is used to obtain the light source output parameters based on the LED light array; perform luminous flux analysis on the light source output parameters and perform color temperature distribution feature mining to obtain the light source color temperature distribution features; Independent unit module, used to divide the LED light array into independent units, fit the illumination distribution field, and build an illumination independent unit network; The natural light compensation module is used to calculate the natural light compensation demand of the independent lighting unit network based on the interval wavelength parameter characterization, and to perform precise control of the lighting compensation and build a natural light compensation control strategy; A color temperature control module is used to dynamically control the color temperature of each unit of the lighting independent unit network based on the color temperature distribution characteristics of the light source, and generate an adaptive unit color temperature control strategy; The intelligent control module is used to obtain pedestrian movement position data; based on the pedestrian movement position data, the natural light compensation control strategy, the adaptive unit color temperature control strategy and the dynamic energy-saving control strategy are used to make light source control optimization decisions, and a lighting intelligent control model is constructed to perform lighting control operations.

Images