LED illumination adjusting method and system based on illumination self-adaption

Abstract

The invention belongs to the technical field of LED illumination adjustment, and provides an LED illumination adjustment method and system based on illumination self-adaption, and the method comprises the steps: evaluating whether the illumination change in a simulated illumination environment is gentle or not in an optimization period of an illumination adjustment speed, and if the illumination change is gentle, judging whether the illumination change is gentle; if yes, obtaining an instantaneous adjustment speed during LED illumination adjustment in the optimization period of the illumination adjustment speed, performing matching analysis on the instantaneous adjustment speed and an illumination change speed in the simulated illumination environment, and evaluating the risk degree of a glare phenomenon in the optimization period of the illumination adjustment speed; and analyzing whether the instantaneous adjustment speed is matched with the instantaneous illumination speed corresponding to the ambient brightness change in the illumination adjustment process, further quantifying the risk degree of the glare phenomenon, and if the risk degree is relatively high, obtaining the optimized instantaneous acceleration according to the simulated illumination ambient brightness speed change, and completing the dynamic adjustment work. And the risk of a glare phenomenon in the period of adjusting the speed of the LED lamp to optimize is reduced.

Description

Technical Field

[0001] This invention belongs to the field of LED lighting adjustment technology, specifically a method and system for LED lighting adjustment based on adaptive illumination. Background Technology

[0002] With the widespread application of LED lighting technology, people have increasingly higher requirements for the intelligence and adaptability of LED lighting systems. Under different lighting conditions, LED lighting systems often cannot adjust the brightness in a timely and accurate manner to meet the needs of users.

[0003] In existing technologies, when the lighting environment changes rapidly, LED lighting systems may experience adjustment delays, causing the lighting brightness to fail to adapt to the environmental changes in a timely manner, affecting the user's visual experience. However, in order to adapt the LED lighting brightness to environmental changes in a timely manner, unreasonable adjustment speeds during the lighting speed adjustment process may produce glare, which can harm the user's eyes. Therefore, how to achieve adaptive lighting adjustment of LED lighting systems, improve their timeliness and accuracy, and avoid glare has become an urgent problem to be solved. This application constructs an illumination matching library by simulating illumination under different lighting environments. Based on the illumination matching brightness in the library and combined with the initial illumination, the brightness adjustment range is obtained. Combined with the lighting adjustment speed, the actual adjustment time is obtained and compared with the adjustment time threshold. This allows for accurate evaluation of the performance of the LED lighting adjustment system, clarifies the timeliness and accuracy of LED brightness adjustment under different lighting environments, provides a quantitative basis for the optimization and improvement of LED photo adjustment systems, and obtains the adjustment speed optimization amount based on the brightness adjustment range, actual adjustment time, and lighting adjustment speed, thus solving the problem of delayed adjustment of LED lighting when responding to changes in illumination. Furthermore, during the optimization cycle of lighting adjustment speed, the smoothness of light change under simulated lighting conditions is assessed. If it is smooth, the instantaneous adjustment speed of LED lighting during the optimization cycle is obtained and matched with the light change speed under simulated lighting conditions. This assesses the risk of glare during the optimization cycle. If the risk is high, the instantaneous acceleration is obtained based on the brightness change speed under simulated lighting conditions to complete the dynamic adjustment. This helps reduce the risk of glare during the optimization cycle of LED light adjustment speed.

[0004] Therefore, the present invention provides an LED lighting adjustment method based on adaptive illumination. Summary of the Invention

[0005] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0006] The technical solution adopted by this invention to solve its technical problem is: Firstly, an LED lighting adjustment method based on adaptive illumination includes the following steps: Simulation experiments were conducted on LED lighting adjustment systems under different simulated lighting environments to obtain the lighting matching brightness corresponding to different simulated lighting environments, and these results were integrated and summarized into a lighting brightness matching library. Based on the illumination matching brightness in the illumination brightness matching library, and combined with the initial illumination brightness, assess whether the lighting adjustment is delayed; If there is a delay, the adjustment speed optimization amount is obtained, and the lighting adjustment speed is optimized based on the adjustment speed optimization amount. During the optimization cycle of lighting adjustment speed, assess whether the changes in lighting under simulated lighting conditions are gradual. If they are gradual, assess the risk of glare during the optimization cycle of lighting adjustment speed. If the risk of glare is high, the optimized instantaneous acceleration is obtained to complete the dynamic adjustment.

[0007] As a preferred embodiment of the present invention, the construction process of the illumination intensity matching library is as follows: The simulated lighting environment is divided into regional grids to obtain lighting sub-regions. The illuminance corresponding to each lighting sub-region is obtained, averaged, and the simulated illuminance is output. The LED lighting adjustment system is then adjusted to the simulated illuminance to obtain the lighting matching brightness. The illumination matching brightness is sorted in ascending order to obtain the illumination brightness matching library.

[0008] A preferred embodiment of the present invention is: evaluating whether there is a delay in lighting adjustment, the process of which is as follows: The difference between the matching brightness and the initial brightness is taken, and the absolute value is output to obtain the brightness adjustment range. The ratio of brightness adjustment range to lighting adjustment speed is calculated, and the actual adjustment time is output. If the actual adjustment time is greater than the adjustment time threshold, the adjustment signal is delayed.

[0009] A preferred embodiment of the present invention is as follows: The process for obtaining the optimized adjustment speed is as follows: Input the brightness adjustment range, actual adjustment time, and lighting adjustment speed into the adjustment optimization formula, output the optimized adjustment speed, and sum it with the lighting adjustment speed to obtain the required lighting adjustment speed.

[0010] A preferred embodiment of the present invention is: evaluating whether the change in illumination under simulated lighting conditions is gradual, the process of which is as follows: The optimization cycle is divided into several optimization monitoring points. The illumination intensity under the simulated lighting environment corresponding to each optimization monitoring point is obtained, a simulated illumination intensity change curve is constructed, and the coordinates of all peak points and trough points are extracted. The coordinates of adjacent peak points and trough points are used as a peak-trough analysis group, and the average value of the change amplitude corresponding to all peak-trough analysis groups is obtained. The peak curve and the trough curve are respectively extracted from the simulated light intensity change curve, and the corresponding peak width and trough width are obtained respectively; The average value of the peak widths corresponding to all peak curves and the trough widths corresponding to all trough curves is obtained by averaging and taking the reciprocal. The average value of the change amplitude and the average value of the wavelength are analyzed and input into the geometric product model to obtain the simulated illumination smoothness value. If the simulated illumination smoothness value is greater than or equal to the simulated illumination smoothness threshold, the simulated illumination smoothness signal is generated.

[0011] A preferred embodiment of the present invention is as follows: if a simulated light intensity smooth signal is generated, the coordinates between adjacent optimized monitoring points are extracted on the simulated light intensity change curve, and the simulated light intensity instantaneous velocity is output through the velocity calculation formula. All simulated instantaneous velocities are sorted according to the time series to obtain the simulated light intensity instantaneous velocity sorting. The instantaneous adjustment speed between adjacent optimized monitoring points is obtained by using a photometer, and all instantaneous adjustment speeds are sorted according to time series to obtain the lighting instantaneous adjustment speed ranking.

[0012] A preferred embodiment of the present invention is as follows: A comparative analysis is performed based on the ranking of simulated instantaneous illumination speeds and the ranking of instantaneous illumination adjustment speeds, as follows: The instantaneous adjustment speed in the instantaneous lighting speed ranking is combined with the instantaneous simulated illumination speed in the instantaneous simulated illumination speed ranking to obtain multiple instantaneous speed analysis groups; Input all instantaneous velocity analysis groups into the Euclidean distance formula and output the velocity change matching degree.

[0013] A preferred embodiment of the present invention is as follows: assessing the risk level of glare during the lighting adjustment speed optimization cycle, the process of which is as follows: If the speed change matching degree is greater than the standard speed change matching degree, a high risk signal is generated; If the speed matching degree is less than or equal to the standard speed change matching degree, a small risk level signal is generated.

[0014] A preferred embodiment of the present invention is as follows: The optimized instantaneous acceleration is obtained based on the speed change of simulated lighting environment brightness, and the process is as follows: Arbitrarily select one instantaneous velocity analysis group as the target instantaneous velocity analysis group; The instantaneous adjustment velocity within the target instantaneous velocity analysis group is subtracted from the simulated instantaneous illumination velocity to obtain the unit instantaneous velocity difference; The instantaneous acceleration of the unit is obtained by calculating the ratio of the instantaneous velocity difference of the unit to the time between adjacent optimized monitoring points.

[0015] Secondly, an LED lighting adjustment system based on adaptive illumination includes the following modules: Matching library construction module: Conduct simulation experiments on LED lighting adjustment systems under different simulated lighting environments, obtain the lighting matching brightness corresponding to different simulated lighting environments, and integrate and summarize it into a lighting brightness matching library; Adjustment Delay Evaluation Module: Based on the illumination matching brightness in the illumination brightness matching library, and combined with the initial illumination brightness, evaluate whether the illumination adjustment is delayed; Adjustment delay optimization module: If there is a delay, obtain the adjustment speed optimization amount, and complete the optimization of the lighting adjustment speed based on the adjustment speed optimization amount; Glare Risk Assessment Module: During the optimization cycle of lighting adjustment speed, assess whether the lighting changes under the simulated lighting environment are gradual. If they are gradual, assess the risk level of glare during the optimization cycle of lighting adjustment speed. Dynamic adjustment module: If the risk of glare is high, the module obtains the optimized instantaneous acceleration and performs dynamic adjustment.

[0016] The beneficial effects of this invention are as follows: This invention conducts multiple simulation experiments on an LED lighting adjustment system under different simulated lighting environments to obtain the matching brightness corresponding to different simulated lighting environments. This data is then integrated and summarized into a brightness matching library, providing data support for the automated lighting adjustment of the LED lighting adjustment system. Based on the matching brightness in the brightness matching library and combined with the initial brightness, the brightness adjustment range is obtained. Combined with the lighting adjustment speed, the actual adjustment time is obtained and compared with an adjustment time threshold. This allows for accurate evaluation of the LED lighting adjustment system's performance, clarifying the timeliness and accuracy of LED brightness adjustment under different lighting environments. This provides a quantitative basis for the optimization and improvement of LED lighting adjustment systems. Furthermore, based on the brightness adjustment range, actual adjustment time, and lighting adjustment speed, an optimization amount for the adjustment speed is obtained, solving the problem of delayed adjustment of LED lighting when responding to changes in brightness. This invention evaluates whether the light change in the simulated lighting environment is gradual during the optimization cycle of lighting adjustment speed. If it is gradual, the instantaneous adjustment speed of LED lighting during the optimization cycle is obtained and matched with the light change speed in the simulated lighting environment. This analysis assesses the risk of glare during the optimization cycle and evaluates the approximation between the actual lighting adjustment system and the ideal simulated lighting system. It analyzes whether the instantaneous adjustment speed matches the instantaneous light speed corresponding to changes in ambient brightness, thus quantifying the risk of glare. If the risk is high, the optimized instantaneous acceleration is obtained based on the speed change of brightness in the simulated lighting environment to complete the dynamic adjustment, which helps reduce the risk of glare during the LED lighting adjustment speed optimization cycle. Attached Figure Description

[0017] The invention will now be further described with reference to the accompanying drawings.

[0018] Figure 1 This is a flowchart of the steps of an LED lighting adjustment method based on adaptive illumination according to the present invention; Figure 2 This is a schematic diagram of an LED lighting adjustment system based on adaptive illumination according to the present invention. Detailed Implementation

[0019] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0020] Example 1: Please see Figure 1 As shown in the embodiment of the present invention, an LED lighting adjustment method based on adaptive illumination includes: Step 1: Conduct multiple simulation experiments on the LED lighting adjustment system under different simulated lighting environments to obtain the lighting matching brightness corresponding to different simulated lighting environments, and integrate and summarize it into a lighting brightness matching library. In some embodiments, based on any simulated lighting environment, the simulated lighting environment is divided according to a regional grid to obtain a lighting sub-region; The illuminance of each illuminated sub-region is obtained by a photometer, and the average value is processed to output the simulated illuminance. The LED lighting adjustment system is then adjusted to the simulated illuminance to obtain the illumination matching brightness. The illumination matching brightness is compared by size and sorted in ascending order to obtain the illumination brightness matching library; It should be noted that a simulated lighting environment corresponds to a lighting matching brightness; Step 2: Based on the illumination matching brightness in the illumination brightness matching library, and combined with the initial illumination brightness, obtain the brightness adjustment range, and combined with the illumination adjustment speed, obtain the actual adjustment time, and compare it with the adjustment time threshold to obtain the normal adjustment signal and the delayed adjustment signal respectively. It should be noted that the initial illuminance is the initial illuminance of the LED lighting control system under simulated lighting conditions; In some embodiments, the difference between the illumination matching brightness and the initial illumination brightness is taken, and the absolute value is output to obtain the brightness adjustment range. The ratio of brightness adjustment range to lighting adjustment speed is calculated, and the actual adjustment time is output. It should be noted that the lighting adjustment speed is the brightness adjustment speed set by those skilled in the art within the LED lighting adjustment system; The actual adjustment time is compared with the adjustment time threshold, as follows: If the actual adjustment time is greater than the adjustment time threshold, it indicates that the system failed to respond in time when adjusting according to the ambient light intensity, and the LED lighting brightness was not adjusted in time, resulting in a delayed adjustment signal. If the actual adjustment time is less than or equal to the adjustment time threshold, it indicates that the LED lighting brightness is adjusted in a timely manner when adjusting according to the ambient light intensity, and a normal adjustment signal is generated. It is understandable that the adjustment time threshold is the time it takes for the light intensity to change under simulated lighting conditions, as measured by a photometer. Step 3: Based on the delay adjustment signal, obtain the adjustment speed optimization amount according to the brightness adjustment amplitude, actual adjustment time and lighting adjustment speed, and complete the optimization of lighting adjustment speed according to the adjustment speed optimization amount; In some embodiments, the brightness adjustment range, the actual adjustment time, and the lighting adjustment speed are respectively input into the adjustment optimization formula, and the optimized adjustment speed is output. Specifically, the adjustment and optimization formula is as follows: The optimized adjustment speed was calculated. ,in, This represents the brightness adjustment range. This is expressed as the actual adjustment time. This refers to the lighting adjustment speed; The desired lighting adjustment speed is obtained by summing the optimized adjustment speed with the lighting adjustment speed. The embodiment of this invention involves conducting multiple simulation experiments on the LED lighting adjustment system under different simulated lighting environments to obtain the matching brightness corresponding to different simulated lighting environments. This data is then integrated and summarized into a brightness matching library, providing data support for the LED lighting adjustment system to achieve automated lighting adjustment. Based on the matching brightness in the brightness matching library and combined with the initial brightness, the brightness adjustment range is obtained. Combined with the lighting adjustment speed, the actual adjustment time is obtained and compared with the adjustment time threshold. This allows for accurate evaluation of the LED lighting adjustment system's performance, clarifying the timeliness and accuracy of LED brightness adjustment under different lighting environments. This provides a quantitative basis for the optimization and improvement of the LED lighting adjustment system. Furthermore, based on the brightness adjustment range, actual adjustment time, and lighting adjustment speed, an optimization amount for the adjustment speed is obtained, solving the problem of delayed adjustment of LED lighting when responding to changes in brightness.

[0021] Example 2: like Figure 1 As shown in the embodiment of the present invention, an LED lighting adjustment method based on adaptive illumination includes: Step 4: During the optimization cycle of lighting adjustment speed, assess whether the light change under the simulated lighting environment is gradual. If it is gradual, obtain the instantaneous adjustment speed of LED lighting during the optimization cycle of lighting adjustment speed, and perform a matching analysis with the light change speed under the simulated lighting environment to assess the risk level of glare during the optimization cycle of lighting adjustment speed. In some embodiments, the optimization period is equally divided into several optimization monitoring points; It should be noted that the time interval between adjacent optimized monitoring points is equal; The illuminance under simulated lighting conditions corresponding to each optimized monitoring point is obtained by using a photometer, and a simulated illuminance change curve is constructed with the X-axis representing time and the Y-axis representing illuminance. Extract the coordinates of all peak points and trough points from the simulated light intensity variation curve; The coordinates of adjacent peak points and trough points are grouped together for peak-trough analysis. Arbitrarily obtain the distance between the Y coordinates of adjacent peak points and the Y coordinates of adjacent valley points within the peak-valley analysis group, and average the distances between adjacent peak points and valley points within all peak-valley analysis groups to output the average value of the change. Arbitrarily select a peak or trough curve from the simulated light intensity variation curve; For example, taking the crest curve as an example, the coordinates of the endpoints of the crest curve are obtained respectively; Among them, the coordinates of the peak curve endpoints include the coordinates of the peak curve start point and the coordinates of the peak curve end point; The distance between the X-coordinate of the starting point and the X-coordinate of the ending point of the crest curve is obtained as the crest width. Taking the trough curve as an example, obtain the coordinates of the endpoints of the trough curve; The coordinates of the trough curve endpoints include the coordinates of the trough curve start point and the coordinates of the trough curve end point; The distance between the X-coordinate of the starting point and the X-coordinate of the ending point of the trough curve is used as the trough width. The average value of the peak widths corresponding to all peak curves and the trough widths corresponding to all trough curves is obtained by averaging and taking the reciprocal. The average variation amplitude and average wavelength are analyzed and input into the geometric product model to output the simulated illumination smoothness value. Specifically, the geometric product model is as follows: The simulated illumination smoothness value was calculated, where, Expressed as the average value of the change. Expressed as the mean beam width; It is understandable that the simulated illumination smoothness value represents a comprehensive index derived from the analysis of the simulated illumination intensity change curve. It reflects the smoothness of illumination changes under simulated illumination conditions. On the one hand, the average change amplitude reflects the average degree of change in illumination intensity in the dimension of fluctuation amplitude under simulated illumination conditions. On the other hand, the average width reflects the width of the peaks or troughs of illumination intensity under simulated illumination conditions, indirectly indicating that the illumination intensity remains stable for a relatively long time under simulated illumination conditions. Therefore, it not only reflects the degree of illumination intensity change under simulated illumination conditions, but also provides an early warning when adjusting and optimizing the lighting adjustment speed of LED illumination under simulated illumination conditions, and provides data support for the optimization and adjustment strategy of lighting adjustment speed. If the simulated illumination smoothness value is less than the simulated illumination smoothness threshold, it indicates that the amplitude of the illumination change fluctuation under the simulated illumination environment is large and the frequency of change is high. It is determined that the illumination change under the simulated illumination environment is not smooth, and a simulated illumination fluctuation signal is generated. If the simulated illumination smoothness value is greater than or equal to the simulated illumination smoothness threshold, it indicates that the amplitude of the illumination change fluctuation under the simulated illumination environment is small and the change frequency is low. It is determined that the illumination change under the simulated illumination environment is relatively smooth, and a simulated illumination smoothness signal is generated. Based on the simulated illumination smooth signal, the coordinates between adjacent optimized monitoring points are extracted on the simulated illumination intensity change curve, and the simulated instantaneous illumination velocity is output through the velocity calculation formula. All simulated instantaneous velocities are sorted according to the time series to obtain the simulated instantaneous illumination velocity sorting. The instantaneous adjustment rate between adjacent optimized monitoring points is obtained by using a photometer, and all instantaneous adjustment rates are sorted according to time series to obtain the lighting instantaneous adjustment rate ranking; The instantaneous adjustment speed in the instantaneous lighting speed ranking is combined with the instantaneous simulated illumination speed in the instantaneous simulated illumination speed ranking to obtain multiple instantaneous speed analysis groups; It should be noted that the instantaneous adjustment speed within the instantaneous speed analysis group corresponds to the simulated instantaneous illumination speed in the time dimension. For example, if the simulated instantaneous illumination speed in the instantaneous speed analysis group is ranked first in the simulated instantaneous illumination speed ranking, then the other instantaneous adjustment speed is also ranked first in the illumination instantaneous adjustment speed ranking. That is, if the simulated instantaneous illumination speed in the instantaneous speed analysis group is the speed between the first and second optimized monitoring points, then the other instantaneous adjustment speed is the speed between the first and second optimized monitoring points. Input all instantaneous velocity analysis groups into the Euclidean distance formula and output the velocity change matching degree. Specifically, the Euclidean distance formula is: The speed change matching degree was calculated. Where n represents the number of instantaneous velocity analysis groups, Represented as the first The instantaneous velocity analysis group simulates the instantaneous velocity of light illumination. Represented as the first Instantaneous speed analysis within each instantaneous speed group; Understandably, the purpose of the Euclidean distance formula is to assess the degree of similarity between an actual lighting adjustment system and an ideal simulated lighting system. Since the ambient brightness changes relatively gradually, if the instantaneous adjustment speed during lighting adjustment deviates significantly from the instantaneous illumination speed corresponding to the change in ambient brightness, it can easily lead to a sudden increase in the contrast between the luminaire brightness and the surrounding environment, resulting in glare. Therefore, the Euclidean distance formula is used to analyze whether the instantaneous adjustment speed during lighting adjustment matches the instantaneous illumination speed corresponding to the change in ambient brightness from an overall perspective, thereby quantifying the risk of glare. The speed variation matching degree is compared with the standard speed variation matching degree, as follows: If the speed change matching degree is greater than the standard speed change matching degree, it indicates that the instantaneous adjustment speed during the lighting adjustment process has a large deviation from the instantaneous illumination speed corresponding to the change in ambient brightness. This can easily lead to glare during the optimization cycle of the lighting adjustment speed, generating a high-risk signal. If the speed matching degree is less than or equal to the standard speed change matching degree, it means that the instantaneous adjustment speed and the instantaneous illumination speed corresponding to the change in ambient brightness are less mismatched during the lighting adjustment process, which is less likely to cause glare during the optimization cycle of lighting adjustment speed and generate a low risk signal. Step 5: If the risk of glare is high, obtain the optimized instantaneous acceleration based on the speed of change in the brightness of the simulated lighting environment, and complete the dynamic adjustment. In some embodiments, an instantaneous velocity analysis group is arbitrarily selected as the target instantaneous velocity analysis group; The instantaneous adjustment velocity within the target instantaneous velocity analysis group is subtracted from the simulated instantaneous illumination velocity to obtain the unit instantaneous velocity difference; The instantaneous acceleration of the unit is obtained by calculating the ratio of the instantaneous velocity difference of the unit to the time between adjacent optimized monitoring points; The specific solution of this invention is as follows: During the optimization cycle of lighting adjustment speed, the light change under simulated lighting environment is evaluated to determine whether it is gradual. If it is gradual, the instantaneous adjustment speed of LED lighting during the optimization cycle is obtained and matched with the light change speed under simulated lighting environment. The risk level of glare phenomenon during the lighting adjustment speed optimization cycle is assessed to evaluate the closeness between the actual lighting adjustment system and the ideal simulated lighting system. This allows for analysis of whether the instantaneous adjustment speed during lighting adjustment matches the instantaneous light speed corresponding to the change in ambient brightness, thereby quantifying the risk level of glare phenomenon. If the risk level is high, the optimized instantaneous acceleration is obtained based on the change in brightness speed under simulated lighting environment to complete the dynamic adjustment work, which helps to reduce the risk of glare phenomenon during the LED light adjustment speed optimization cycle.

[0022] Example 2: Based on the same inventive concept as the light-adaptive LED lighting adjustment method in the foregoing embodiments, such as Figure 2 As shown, this application provides an LED lighting adjustment system based on adaptive illumination, wherein the system specifically includes: Matching library construction module: Conduct simulation experiments on LED lighting adjustment systems under different simulated lighting environments, obtain the lighting matching brightness corresponding to different simulated lighting environments, and integrate and summarize it into a lighting brightness matching library; Adjustment Delay Evaluation Module: Based on the illumination matching brightness in the illumination brightness matching library, and combined with the initial illumination brightness, evaluate whether the illumination adjustment is delayed; Adjustment delay optimization module: If there is a delay, obtain the adjustment speed optimization amount, and complete the optimization of the lighting adjustment speed based on the adjustment speed optimization amount; Glare Risk Assessment Module: During the optimization cycle of lighting adjustment speed, assess whether the lighting changes under the simulated lighting environment are gradual. If they are gradual, assess the risk level of glare during the optimization cycle of lighting adjustment speed. Dynamic adjustment module: If the risk of glare is high, the module obtains the optimized instantaneous acceleration and performs dynamic adjustment.

[0023] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for adjusting LED lighting based on adaptive illumination, characterized in that: include: Simulation experiments were conducted on LED lighting adjustment systems under different simulated lighting environments to obtain the lighting matching brightness corresponding to different simulated lighting environments, and these results were integrated and summarized into a lighting brightness matching library. Based on the illumination matching brightness in the illumination brightness matching library, and combined with the initial illumination brightness, assess whether the lighting adjustment is delayed; If there is a delay, the adjustment speed optimization amount is obtained, and the lighting adjustment speed is optimized based on the adjustment speed optimization amount. During the optimization cycle of lighting adjustment speed, assess whether the changes in lighting under simulated lighting conditions are gradual. If they are gradual, assess the risk of glare during the optimization cycle of lighting adjustment speed. If the risk of glare is high, the optimized instantaneous acceleration is obtained to complete the dynamic adjustment.

2. The LED lighting adjustment method based on adaptive illumination according to claim 1, characterized in that: The construction process of the light intensity matching library is as follows: The simulated lighting environment is divided into regional grids to obtain lighting sub-regions. The illuminance corresponding to each lighting sub-region is obtained, averaged, and the simulated illuminance is output. The LED lighting adjustment system is then adjusted to the simulated illuminance to obtain the lighting matching brightness. The illumination matching brightness is sorted in ascending order to obtain the illumination brightness matching library.

3. The LED lighting adjustment method based on adaptive illumination according to claim 1, characterized in that: The process for assessing whether there is a delay in lighting adjustment is as follows: The difference between the matching brightness and the initial brightness is taken, and the absolute value is output to obtain the brightness adjustment range. The ratio of brightness adjustment range to lighting adjustment speed is calculated, and the actual adjustment time is output. If the actual adjustment time is greater than the adjustment time threshold, the adjustment signal is delayed.

4. The LED lighting adjustment method based on adaptive illumination according to claim 3, characterized in that: The process for obtaining the adjustment speed optimization value is as follows: Input the brightness adjustment range, actual adjustment time, and lighting adjustment speed into the adjustment optimization formula, output the optimized adjustment speed, and sum it with the lighting adjustment speed to obtain the required lighting adjustment speed.

5. The LED lighting adjustment method based on adaptive illumination according to claim 1, characterized in that: The process for evaluating whether the changes in illumination under simulated lighting conditions are gradual is as follows: The optimization cycle is divided into several optimization monitoring points. The illumination intensity under the simulated lighting environment corresponding to each optimization monitoring point is obtained, a simulated illumination intensity change curve is constructed, and the coordinates of all peak points and trough points are extracted. The coordinates of adjacent peak points and trough points are used as a peak-trough analysis group, and the average value of the change amplitude corresponding to all peak-trough analysis groups is obtained. The peak curve and the trough curve are respectively extracted from the simulated light intensity change curve, and the corresponding peak width and trough width are obtained respectively; The average value of the peak widths corresponding to all peak curves and the trough widths corresponding to all trough curves is obtained by averaging and taking the reciprocal. The average value of the change amplitude and the average value of the wavelength are analyzed and input into the geometric product model to obtain the simulated illumination smoothness value. If the simulated illumination smoothness value is greater than or equal to the simulated illumination smoothness threshold, the simulated illumination smoothness signal is generated.

6. The LED lighting adjustment method based on adaptive illumination according to claim 5, characterized in that: If a simulated light intensity smooth signal is generated, the coordinates between adjacent optimized monitoring points are extracted from the simulated light intensity change curve, and the simulated instantaneous light intensity is output through the speed calculation formula. All simulated instantaneous intensities are then sorted according to the time series to obtain the simulated instantaneous light intensity sorting. The instantaneous adjustment speed between adjacent optimized monitoring points is obtained by using a photometer, and all instantaneous adjustment speeds are sorted according to time series to obtain the lighting instantaneous adjustment speed ranking.

7. The LED lighting adjustment method based on adaptive illumination according to claim 6, characterized in that: Based on the ranking of instantaneous illumination velocity and instantaneous lighting adjustment velocity, a comparative analysis was conducted, as follows: The instantaneous adjustment speed in the instantaneous lighting speed ranking is combined with the instantaneous simulated illumination speed in the instantaneous simulated illumination speed ranking to obtain multiple instantaneous speed analysis groups; Input all instantaneous velocity analysis groups into the Euclidean distance formula and output the velocity change matching degree.

8. The LED lighting adjustment method based on adaptive illumination according to claim 1, characterized in that: The risk of glare during the lighting adjustment speed optimization cycle is assessed as follows: If the speed change matching degree is greater than the standard speed change matching degree, a high risk signal is generated; If the speed matching degree is less than or equal to the standard speed change matching degree, a small risk level signal is generated.

9. The LED lighting adjustment method based on adaptive illumination according to claim 1, characterized in that: The optimized instantaneous acceleration is obtained based on the speed change of simulated ambient light intensity. The process is as follows: Arbitrarily select one instantaneous velocity analysis group as the target instantaneous velocity analysis group; The instantaneous adjustment velocity within the target instantaneous velocity analysis group is subtracted from the simulated instantaneous illumination velocity to obtain the unit instantaneous velocity difference; The instantaneous acceleration of the unit is obtained by calculating the ratio of the instantaneous velocity difference of the unit to the time between adjacent optimized monitoring points.

10. An LED lighting adjustment system based on adaptive illumination, implementing the steps of an LED lighting adjustment method based on adaptive illumination as described in any one of claims 1-9, characterized in that: include: Matching library construction module: Conduct simulation experiments on LED lighting adjustment systems under different simulated lighting environments, obtain the lighting matching brightness corresponding to different simulated lighting environments, and integrate and summarize it into a lighting brightness matching library; Adjustment Delay Evaluation Module: Based on the illumination matching brightness in the illumination brightness matching library, and combined with the initial illumination brightness, evaluate whether the illumination adjustment is delayed; Adjustment delay optimization module: If there is a delay, obtain the adjustment speed optimization amount, and complete the optimization of the lighting adjustment speed based on the adjustment speed optimization amount; Glare Risk Assessment Module: During the optimization cycle of lighting adjustment speed, assess whether the lighting changes under the simulated lighting environment are gradual. If they are gradual, assess the risk level of glare during the optimization cycle of lighting adjustment speed. Dynamic adjustment module: If the risk of glare is high, the module obtains the optimized instantaneous acceleration and performs dynamic adjustment.

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