LED lamp strip light emission control method and controller

Abstract

The application discloses an LED lamp strip light-emitting control method and a controller, relates to the technical field of LED lamp strips, and realizes comprehensive perception of the spatial heat distribution and the light output distribution of the LED lamp strip by arranging a plurality of collection points in the mounting area of the LED lamp strip and combining the equidistant arrangement and the key area encryption arrangement mode, realizes high-precision collection and transmission of data through a multi-channel A / D conversion circuit and a bus interface, stores temperature data and luminous flux data in a two-dimensional matrix form, and carries out dimensionless processing, so that a standard feature set is formed, the standard feature set can accurately reflect the temperature change trend and the luminous flux distribution characteristics of the LED lamp strip in different areas, and provides a data basis for subsequent heat aggregation identification and power correction. Multidimensional space heat and light joint monitoring is realized, so that the controller can complete accurate identification at the initial stage of heat anomaly, thereby preventing local overheating diffusion.

Description

Technical Field

[0001] This invention relates to the field of LED light strip technology, specifically to an LED light strip light emission control method and controller. Background Technology

[0002] In LED lighting applications, LED strip lights are widely used in shopping malls, exhibition halls, greenhouses, museums, and stage decorations due to their compact structure and flexible installation. In these settings, LED strip lights typically operate in long-distance series or parallel connections, and their luminous characteristics, heat distribution features, and energy efficiency are all affected by the combined effects of the installation structure, heat dissipation conditions, and changes in ambient temperature.

[0003] Therefore, the coordinated control of the spatial thermal characteristics and luminous flux characteristics of LED light strips has become an important research direction in the field of intelligent lighting control.

[0004] Currently, most existing LED light strip control methods employ constant power driving or single-point feedback control based on global average temperature. While these methods are simple in structure, they neglect the spatial temperature distribution differences and local heat accumulation effects of the light strip. In practical applications, especially in shopping mall display areas or greenhouse seedling environments, different areas of the light strip experience uneven temperature rise due to factors such as installation height, airflow direction, and environmental obstruction. Traditional constant power driving methods cannot specifically suppress power or redistribute energy in local high-temperature areas. Furthermore, existing light output control algorithms are generally based on feedback from a single light sensor, failing to achieve the fusion analysis of multi-point luminous flux data and temperature distribution data. When light decay in a certain area intensifies or the temperature becomes too high, the system often cannot adjust the output in time, leading to uneven brightness, color drift, and accelerated device aging, thereby reducing the overall lifespan and energy efficiency of the LED light strip.

[0005] The main reason for uneven heat distribution and insufficient light output control precision in existing technologies is the lack of a spatial feedback closed-loop mechanism in the control strategy. Due to the failure to monitor and respond to the temperature gradient function at different locations on the LED strip surface in real time, the controller will cause local nodes to be in high-heat areas for a long time when executing constant power output, resulting in a "heat accumulation" phenomenon. The heat accumulation area not only causes the junction temperature of the LED chip to rise, but also causes a decrease in luminous efficiency and spectral drift, which significantly reduces the uniformity of illuminance of the LED strip. At the same time, the cumulative effect of heat may lead to an imbalance in the power distribution between adjacent LED chips, forming local areas that are too bright and too dark, which in turn causes instability in the overall lighting visual effect. In long-term operation, thermal imbalance will also accelerate the aging of LED packaging materials, causing solder joint detachment, overload of the drive circuit, and even premature failure. Therefore, there is an urgent need for an LED strip light emission control method that can dynamically adjust the PWM duty cycle and power output based on real-time feedback of spatial heat distribution, so as to achieve a coordinated balance between temperature and luminous flux in local areas, thereby improving energy efficiency, extending life and ensuring consistent light output. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides an LED light strip illumination control method and controller, which solves the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an LED strip light emission control method, comprising the following steps:

[0008] S1. Set up multiple acquisition points in the installation area of ​​the LED light strip, periodically collect temperature data and luminous flux data, and transmit the temperature data and luminous flux data to the controller, where they are preprocessed to obtain a standard feature set;

[0009] S2. Mark the heat accumulation area based on the standard feature set and execute the first control strategy. After the first control strategy is executed, perform heat balance analysis. If the heat distribution is still abnormal, trigger the thermo-optical coupling correction mechanism.

[0010] S3. After triggering the thermo-optical coupling correction mechanism, the controller performs thermo-optical coupling correction calculation and adaptively corrects the power output of the LED strip based on the calculation results.

[0011] S4. After correction, perform difference calculation based on the thermal-optical coupling correction result, and perform graded adjustment control on the PWM duty cycle of each region based on the difference calculation result.

[0012] Preferably, S1 includes S11;

[0013] S11. Multiple data collection points are set in the installation area of ​​the LED light strip, using a combination of evenly spaced layout and dense layout in key areas. The data collection points include temperature data collection points and luminous flux data collection points; and a sampling period is set to collect temperature data and luminous flux data in real time.

[0014] The spacing between the equally spaced installations is 0.5m-1.0m;

[0015] The key areas for dense deployment include corner locations, areas with weak heat dissipation, and power access points, with a sampling point spacing of less than 0.3m;

[0016] The controller periodically collects temperature data and light flux data from temperature acquisition points and light flux acquisition points according to a preset sampling period. The sampling period is automatically adjusted according to the rate of environmental change and the system response time, and the value range is 2s-10s.

[0017] Preferably, S1 further includes S12;

[0018] S12. A multi-channel A / D conversion circuit is used to transmit the collected temperature data and luminous flux data to the controller via the bus interface. In the controller, the temperature data and luminous flux data are numbered and stored in the form of a two-dimensional matrix to form a temperature dataset containing the spatial coordinates (x, y) and temperature values ​​of each point. The corresponding luminous flux data is stored in the same spatial distribution to form a luminous flux dataset.

[0019] The spatial coordinates (x, y) represent the horizontal axis coordinates and the vertical axis coordinates.

[0020] The temperature dataset and luminous flux dataset are preprocessed to obtain a standard feature set. The preprocessing is performed by using the maximum and minimum range method to perform dimensionless processing on all parameters in the temperature dataset and luminous flux dataset, thereby eliminating the dimensional influence between all parameters.

[0021] The standard feature set includes the temperature value T of the i-th sampling point. i And the luminous flux L at the i-th acquisition point i .

[0022] Preferably, S2 includes S21;

[0023] S21. Temperature values ​​T at multiple i-th acquisition points based on the standard feature set. i A weighted average is performed on all temperature data within the same sampling period to obtain the average temperature value Tavg for the current period; and the average temperature value Tavg for the current period is compared with the temperature value T at the i-th sampling point. i Perform difference calculation and output the deviation value △T of the i-th acquisition point. i ;

[0024] The controller calculates the deviation value △T at the i-th acquisition point. i Then, the deviation values ​​ΔT of all i-th sampling points are... i Stored according to spatial coordinates, forming a temperature deviation matrix ΔTmap(x,y).

[0025] When the deviation value ΔT of the i-th collection point i When the LED light strip exceeds the safe value, the corresponding spatial coordinate (x, y) area will be marked as a heat accumulation area.

[0026] Preferably, S2 further includes S22;

[0027] S22. When a region is marked as a heat accumulation area, the controller executes a first control strategy, which includes temperature rise control and PWM duty cycle control.

[0028] The temperature rise control is achieved by adjusting the deviation value ΔT of the i-th sampling point after marking the heat accumulation area. i The deviation value ΔT of the i-th acquisition point in the three consecutive sampling periods is calculated. i The temperature rise will be monitored and a relevant control mechanism will be implemented accordingly; the details are as follows:

[0029] When the deviation value ΔT of the i-th sampling point in the sampling period i When the temperature exceeds the LED light strip's safety value of +2℃, Level 1 control is activated; this Level 1 control reduces the power in the current heat-concentrated area of ​​the LED light strip to 90% of its rated power.

[0030] When the deviation value ΔT of the i-th sampling point in the sampling period i When the LED light strip is within a safe temperature range of +2℃ to -4℃, secondary control is implemented; the secondary control reduces the power in the current heat accumulation area of ​​the LED light strip to 80% of the rated power.

[0031] When the deviation value ΔT of the i-th sampling point in the sampling period i When the temperature exceeds the LED light strip's safety value of +4℃, a three-level control is implemented; this three-level control reduces the power in the current heat-concentrated area of ​​the LED light strip to 70% of its rated power.

[0032] The PWM duty cycle control adjusts the PWM duty cycle based on the generated relevant control mechanism. The specific adjustments are as follows: when the temperature rise control output is a level 1 control, the PWM duty cycle is reduced by 10%; when the temperature rise control output is a level 2 control, the PWM duty cycle is reduced by 20%; when the temperature rise control output is a level 3 control, the PWM duty cycle is reduced by 30%, and the active heat dissipation signal output is activated.

[0033] Preferably, S2 further includes S23;

[0034] S23. After the controller completes the execution of the first control strategy, it performs a thermal balance analysis on the heat distribution of the entire LED light strip area and outputs the thermal balance index N1.

[0035] The thermal equilibrium analysis calculates the standard deviation of the temperature values ​​T at all temperature collection points within the current sampling period and compares it with the benchmark standard deviation of the temperature values ​​T recorded under thermal temperature equilibrium conditions during historical operation phases to obtain the equilibrium index N1.

[0036] If the balance index N1 result is <0.9, the controller determines that the current LED strip heat distribution is uneven, and at this time the thermo-optical coupling correction mechanism is triggered;

[0037] If the balance index N1 is ≥0.9, the controller determines that the current LED strip has a uniform heat distribution and maintains the current output power.

[0038] Preferably, S3 includes S31;

[0039] S31. After triggering the thermo-optical coupling correction mechanism, the controller collects the actual luminous flux L of the i-th acquisition point at each luminous flux acquisition point in real time. i And combined with the deviation value △T of the i-th collection point i Perform thermo-optical coupling correction calculations and output the target luminous flux Lcorr at the i-th acquisition point. i ;

[0040] The target luminous flux Lcorr at the i-th acquisition point i The specific calculation formula is as follows:

[0041] In the formula, k2 represents the luminous efficacy correction coefficient, with a value range of 0.05-0.25, initially set at 0.05, and Tmax represents the upper limit of the allowable operating temperature of the LED light strip.

[0042] Preferably, S4 includes S41;

[0043] S41. After the thermo-optical coupling correction mechanism is completed, based on the target luminous flux Lcorr of the i-th acquisition point acquired in real time. i The actual light flux L at the current i-th acquisition point i Perform difference calculation to obtain the luminous flux error value ΔL at the i-th acquisition point. i Based on the light flux error value ΔL at the i-th acquisition point i The target light flux Lcorr at the i-th acquisition point i The relative ratio is used to perform graded adjustment control of the PWM duty cycle in the heat accumulation region; the specific graded content is as follows:

[0044] When the luminous flux error value of the i-th acquisition point is ΔL i |≤0.02·Target luminous flux Lcorr at the i-th acquisition point i When the controller determines that the current area's light output is in a stable range, it maintains the current PWM duty cycle unchanged.

[0045] When the target luminous flux Lcorr at the i-th acquisition point is 0.02 i <|Luminous flux error value △L at the i-th acquisition point i |≤0.05·Target luminous flux Lcorr at the i-th acquisition point i When the controller determines that there is a deviation in the light output of the current area, it executes the PWM duty cycle adjustment formula and sets the adjustment coefficient γ to 0.5.

[0046] When the luminous flux error value of the i-th acquisition point is ΔL i |>0.05·Target luminous flux Lcorr at the i-th acquisition point i When the controller determines that there is a significant brightness deviation in the current area, it executes the PWM duty cycle adjustment formula, sets the adjustment coefficient γ to 1, and performs a fast correction operation. The PWM duty cycle adjustment range is ±4%.

[0047] Preferably, S41 further includes S411;

[0048] S441, The luminous flux error value ΔL based on the i-th acquisition point i Based on the PWM duty cycle adjustment formula, the adjusted PWM duty cycle Dnew at the i-th acquisition point is calculated and output. i The PWM duty cycle is dynamically adjusted.

[0049] The specific form of the PWM duty cycle adjustment formula is: Dnew i =Dold i +γ×Sign(△L i ) × △Dunit; where Doldi represents the current PWM output duty cycle, △Dunit represents the minimum adjustable unit duty cycle change step value, with a value range of 0.01-0.02, and γ represents the adjustment coefficient.

[0050] An LED strip light-emitting controller includes a thermal-optical acquisition module, a thermal equilibrium analysis module, a thermal-optical coupling correction module, and a PWM duty cycle adjustment module;

[0051] The thermal light acquisition module periodically collects temperature and luminous flux data by setting multiple acquisition points in the installation area of ​​the LED light strip, and transmits the temperature and luminous flux data to the controller for preprocessing to obtain a standard feature set.

[0052] The thermal equilibrium analysis module marks the heat accumulation area based on a standard feature set and executes the first control strategy. After the first control strategy is completed, thermal equilibrium analysis is performed. If the heat distribution is still abnormal, the thermal-optical coupling correction mechanism is triggered.

[0053] The thermo-optical coupling correction module, after triggering the thermo-optical coupling correction mechanism, performs thermo-optical coupling correction calculations by the controller, and adaptively corrects the power output of the LED light strip based on the calculation results.

[0054] The PWM duty cycle adjustment module performs differential calculation based on the thermal-optical coupling correction result after correction, and performs graded adjustment control on the PWM duty cycle of each region based on the differential calculation result.

[0055] This invention provides a method and controller for controlling the light emission of LED strip lights. It has the following advantages:

[0056] (1) This method sets up multiple temperature and luminous flux collection points in the installation area of ​​the LED strip, and combines equal spacing and dense layout in key areas to achieve comprehensive perception of the spatial thermal distribution and light output distribution of the LED strip. The high-precision acquisition and transmission of data is achieved through multi-channel A / D conversion circuit and bus interface. The controller stores the temperature data and luminous flux data in the form of a two-dimensional matrix and performs dimensionless processing through the maximum and minimum value range method to form a standard feature set. This standard feature set can accurately reflect the temperature change trend and luminous flux distribution characteristics of the LED strip in different areas, providing a highly reliable data foundation for subsequent heat accumulation identification and power correction.

[0057] Compared with traditional solutions that rely solely on single-point temperature sensing or average temperature control, this invention achieves multi-dimensional spatial thermo-optical joint monitoring, effectively improving the spatial resolution and response sensitivity of data acquisition, enabling the controller to accurately identify thermal anomalies in their early stages, thereby preventing the spread of local overheating.

[0058] (2) This method constructs a temperature deviation matrix ΔTmap(x,y) to monitor the temperature deviation value ΔTi at each sampling point in real time. Upon detecting a local heat accumulation area, it automatically triggers the first control strategy to achieve graded power regulation and PWM duty cycle limiting control. This control strategy forms a closed-loop response system through a three-level temperature rise control mechanism and the corresponding PWM duty cycle adjustment amplitude, which can effectively reduce the energy input of the heat accumulation area in a short time and suppress the continuous rise of junction temperature.

[0059] Furthermore, after executing the first control strategy, the controller quantifies and evaluates the overall thermal distribution state by calculating the thermal equilibrium index N1, thereby achieving dynamic equilibrium judgment of temperature distribution. Through this closed-loop temperature feedback mechanism, the present invention enables the LED light strip to maintain a stable thermal equilibrium state in high-temperature environments, thereby effectively extending the service life of LED chips and driving circuits and preventing early failures caused by thermal shock. Compared with the traditional constant power driving method, the present invention can reduce the peak temperature of the heat accumulation area by about 15% to 25% and improve the overall energy efficiency by about 10% to 18%.

[0060] (3) This method achieves adaptive coordination of luminous flux and temperature parameters by introducing a thermo-optical coupling correction calculation formula and a graded PWM adjustment algorithm in the thermo-optical coupling correction stage and the PWM dynamic adjustment stage.

[0061] After acquiring the thermal-optical coupling correction calculation results, the controller calculates the target luminous flux Lcorri at the i-th acquisition point and performs difference analysis with the actual luminous flux Li. Based on the relative ratio of the luminous flux error ΔLi to the target luminous flux Lcorri, the PWM duty cycle is controlled in stages. When the error is small (≤2%), the output remains stable. When the error is moderate (2%~5%), fine-tuning is performed with γ=0.5. When the error is large (>5%), rapid correction is performed with γ=1. The maximum PWM adjustment range is ±4%. At the same time, the controller performs an overshoot detection mechanism after each adjustment. If the luminous flux error direction is detected to be continuously reversed, the adjustment coefficient γ is automatically halved to ensure a smooth transition of light output. Through this staged control and overshoot prevention mechanism, this invention achieves self-learning dynamic stability control of light output without increasing hardware costs. This allows the LED light strip to maintain a light intensity uniformity error of less than ±3% under the influence of temperature changes, environmental disturbances, and aging, and effectively suppresses visual flicker, significantly improving the visual comfort and overall light quality of the lighting. Attached Figure Description

[0062] Figure 1 This is a schematic diagram of the steps of an LED strip light emission control method according to the present invention;

[0063] Figure 2 This is a schematic diagram of the process of an LED strip light-emitting controller according to the present invention;

[0064] Figure 3 A class diagram is created to illustrate the data distribution and collection point layout. Detailed Implementation

[0065] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0066] Example 1: Please refer to Figure 1 This invention provides a method for controlling the light emission of LED strip lights. To achieve the above objectives, this invention employs the following technical solution, comprising the following steps:

[0067] S1. Set up multiple acquisition points in the installation area of ​​the LED light strip, periodically collect temperature data and luminous flux data, and transmit the temperature data and luminous flux data to the controller, where they are preprocessed to obtain a standard feature set;

[0068] S2. Mark the heat accumulation area based on the standard feature set and execute the first control strategy. After the first control strategy is executed, perform heat balance analysis. If the heat distribution is still abnormal, trigger the thermo-optical coupling correction mechanism.

[0069] S3. After triggering the thermo-optical coupling correction mechanism, the controller performs thermo-optical coupling correction calculation and adaptively corrects the power output of the LED strip based on the calculation results.

[0070] S4. After correction, perform difference calculation based on the thermal-optical coupling correction result, and perform graded adjustment control on the PWM duty cycle of each region based on the difference calculation result.

[0071] In this embodiment, the method establishes a high-resolution spatial sensing network by deploying multiple temperature and luminous flux sampling points in the LED strip installation area. In this deployment, equally spaced sampling points ensure the continuity of the overall heat distribution, while denser sampling points are set at corners, areas with weak heat dissipation, and power input terminals to capture initial signs of heat accumulation. If only equally spaced sampling is used, local temperature rise response lag can easily occur, leading to the inability to identify abnormal heat areas in a timely manner. By periodically sampling and preprocessing data to form a standard feature set, it is possible to ensure that different parameters are uniformly evaluated under the same data dimension, thereby avoiding misjudgments caused by differences in dimensions. During the heat accumulation marking and first control strategy execution stage based on the standard feature set, the controller performs power limiting and PWM duty cycle linkage adjustment for local temperature rise areas. The physical significance of this design is that the junction temperature of the LED chip is non-linearly positively correlated with the driving power. When the local temperature rise exceeds the safety threshold, maintaining constant power output will lead to a sharp shortening of the chip's lifespan or even sudden light decay. Therefore, graded power reduction and PWM limiting control can achieve "active cooling" through energy reduction in the early stages of thermal anomalies, effectively preventing the spread of hot spots while maintaining stable brightness in the surrounding area and preventing visual unevenness. After executing the first control strategy, the system performs a distribution uniformity analysis by calculating the thermal equilibrium index to determine whether to enter the thermo-optical coupling correction stage. The core purpose of this step is to compensate for and correct the luminous efficiency by combining the coupling relationship between luminous flux and temperature. Because the luminous efficiency of LEDs decreases with increasing temperature (approximately 2% to 3% decrease for every 10°C increase), without thermo-optical correction, although the system temperature is controlled, the overall brightness will decrease, resulting in visually dark areas. By introducing the thermo-optical coupling correction calculation formula, the controller automatically increases the target luminous flux in the corresponding area while reducing the temperature rise, physically achieving thermal compensation balance and maintaining overall illuminance consistency. Finally, in the graded PWM dynamic adjustment stage, the controller performs multi-level duty cycle adjustments by calculating the difference between the actual luminous flux and the target luminous flux. The physical significance of this mechanism lies in achieving a smooth brightness transition through minimal step adjustments (1%–2%), avoiding flickering or visual fluctuations caused by large PWM changes. Without hierarchical control, rapid PWM correction during sudden changes in system temperature or luminous flux would cause "brightness oscillations," affecting not only the visual experience but also overloading the driver. By introducing hierarchical control with an error direction sign function and an adjustment coefficient γ, the adjustment process acquires "self-damping characteristics," enabling stable convergence of brightness and heat distribution over multiple cycles.

[0072] Example 2: Please refer to Figure 1 and Figure 3 Specifically: S1 includes S11;

[0073] S11. Set up multiple data collection points in the installation area of ​​the LED light strip, using a combination of evenly spaced layout and dense layout in key areas. The data collection points include temperature data collection points and luminous flux data collection points; and set a sampling period to collect temperature data and luminous flux data in real time.

[0074] The spacing between the equally spaced installations is 0.5m-1.0m;

[0075] The key areas are densely deployed, including corner locations, areas with weak heat dissipation, and power access points, with the distance between the collection points less than 0.3m, in order to improve the accuracy of response to local temperature changes;

[0076] Temperature acquisition points are set up on the mounting surface of the LED strip along its length, based on the power density distribution and heat dissipation structure characteristics of the LED strip, and temperature sensors are set up to periodically collect temperature data to form a uniform temperature monitoring network.

[0077] The luminous flux acquisition point uses a digital photosensor to periodically collect luminous flux data;

[0078] The controller periodically collects temperature and luminous flux data from the temperature and luminous flux collection points according to a preset sampling period. The sampling period is automatically adjusted based on the rate of environmental change and the system response time, with a range of 2s-10s.

[0079] S1 also includes S12;

[0080] S12. A multi-channel A / D conversion circuit is used to transmit the collected temperature data and luminous flux data to the controller via the bus interface. In the controller, the temperature data and luminous flux data are numbered and stored in the form of a two-dimensional matrix to form a temperature dataset containing the spatial coordinates (x, y) and temperature values ​​of each point. The corresponding luminous flux data is stored in the same spatial distribution to form a luminous flux dataset.

[0081] In the spatial coordinates (x, y), x represents the horizontal axis coordinate and y represents the vertical axis coordinate, where the horizontal axis coordinate x represents the distance between sampling points and the vertical axis coordinate y represents the distance between sampling points of which number.

[0082] The temperature and light flux datasets were preprocessed to obtain a standard feature set. The preprocessing method used the maximum and minimum range to perform dimensionless processing on all parameters in the temperature and light flux datasets, eliminating the dimensional influence between all parameters.

[0083] The standard feature set includes the temperature value T at the i-th acquisition point. i And the luminous flux L at the i-th acquisition point i .

[0084] In this embodiment, the method achieves full spatial coverage monitoring of the LED strip's operating status by setting multiple temperature and luminous flux sampling points in the LED strip installation area and combining evenly spaced and densely spaced sampling points in key areas. Evenly spaced sampling (0.5m–1.0m) ensures the overall continuity of temperature and luminous flux distribution, while denser sampling (less than 0.3m) at corners, areas with weak heat dissipation, and power inputs enables highly sensitive response in the early stages of local heat accumulation. This is because the bending points or power interfaces of LED strips typically have poor heat dissipation; if sampling points are too sparse, it will lead to delayed temperature rise monitoring, causing local junction temperatures to exceed safe values ​​without timely intervention. Dense sampling point placement effectively avoids overheating failures caused by undetected "hot spots." Temperature sampling points are set with temperature sensors based on the strip's power density distribution, ensuring the collected data accurately reflects the thermal characteristics of different power ranges. This setup aims to prevent distortion of overall temperature judgment due to uneven strip power density, thereby improving the accuracy of temperature field modeling. The luminous flux acquisition points employ digital photosensors for periodic detection, ensuring synchronized sensing of changes in light decay and temperature. Relying solely on temperature feedback without luminous flux information could lead to uneven brightness even as temperatures decrease. Joint acquisition of luminous flux and temperature allows for the synchronous reflection of dynamic changes in thermo-optical coupling behavior, enabling early identification and correction of luminous efficacy decay. The controller performs data acquisition according to a set sampling period (2s–10s), a period length chosen to balance the rate of environmental change and system response time. For example, in greenhouses or shopping malls, temperature fluctuations typically exhibit a gradual trend; a sampling period that is too short would cause frequent system responses and increased computational load, while a period that is too long would miss the critical temperature rise point. Adaptive sampling period adjustment ensures both real-time and stable data acquisition, avoiding the dual problems of delayed sampling and oversampling. During data processing, a multi-channel A / D conversion circuit enables synchronous sampling of multiple signal sources, avoiding signal phase misalignment caused by traditional single-channel polling. The controller stores temperature and luminous flux data in a two-dimensional coordinate (x, y) matrix, establishing a spatial correspondence. This allows subsequent algorithms to directly perform rapid thermal image calculations and zonal control based on the matrix index. For example, when a high-temperature gradient appears along the x-axis of the light strip's length, while the luminous flux decreases along the vertical y-axis, the system can immediately determine that there is a localized heat dissipation anomaly at that location, triggering regional power limiting adjustments. The physical significance of this matrix structure lies in transforming the originally discrete point-sampled data into spatially distributed features, forming the basis of "digital thermal imaging." During data preprocessing, the temperature and luminous flux parameters are dimensionless using the maximum and minimum range method, eliminating the unit influence between different physical quantities and enabling the two types of data to be compared and fused in the same feature space.Without dimensionless processing, the order-of-magnitude difference between temperature (unit: °C) and luminous flux (unit: lm) can lead to feature shifts, causing the control algorithm to misjudge the degree of regional anomalies. The purpose of this standardization step is to construct a unified standard feature set, providing a mathematical basis for comparability in subsequent thermal agglomeration determination and power correction algorithms.

[0085] Example 3: Please refer to Figure 1 Specifically: S2 includes S21;

[0086] S21. Temperature values ​​T at multiple i-th acquisition points based on the standard feature set. i A weighted average is performed on all temperature data within the same sampling period to obtain the average temperature value Tavg for the current period; and the average temperature value Tavg for the current period is compared with the temperature value T at the i-th sampling point. i Perform difference calculation and output the deviation value △T of the i-th acquisition point. i ;

[0087] The controller calculates the deviation value △T at the i-th acquisition point. i Then, the deviation values ​​ΔT of all i-th sampling points are... i Stored according to spatial coordinates, forming a temperature deviation matrix ΔTmap(x,y).

[0088] When the deviation value ΔT of the i-th collection point i When the LED light strip exceeds the safe value, the corresponding spatial coordinate (x, y) area will be marked as a heat accumulation area.

[0089] S2 also includes S22;

[0090] S22. When a region is marked as a heat accumulation area, the controller executes the first control strategy, which includes temperature rise control and PWM duty cycle control.

[0091] Temperature rise control is achieved by measuring the deviation value ΔT at the i-th sampling point after marking it as a heat accumulation area. i The deviation value ΔT of the i-th acquisition point in the three consecutive sampling periods is calculated. i The temperature rise will be monitored and a relevant control mechanism will be implemented accordingly; the details are as follows:

[0092] When the deviation value ΔT of the i-th sampling point in the sampling period i When the temperature exceeds the LED strip's safety value of +2℃, Level 1 control is activated; Level 1 control reduces the power in the current heat-concentrated area of ​​the LED strip to 90% of its rated power.

[0093] When the deviation value ΔT of the i-th sampling point in the sampling period iWhen the LED light strip's safety temperature is +2℃ to -4℃, secondary control is implemented; secondary control reduces the power in the current heat accumulation area of ​​the LED light strip to 80% of the rated power.

[0094] When the deviation value ΔT of the i-th sampling point in the sampling period i If the temperature exceeds the LED light strip's safety value of +4℃, a three-level control will be implemented. The three-level control reduces the power in the current heat accumulation area of ​​the LED light strip to 70% of the rated power.

[0095] PWM duty cycle control adjusts the PWM duty cycle based on the generated relevant control mechanism. The specific adjustments are as follows: when the temperature rise control output is a level 1 control, the PWM duty cycle is reduced by 10%; when the temperature rise control output is a level 2 control, the PWM duty cycle is reduced by 20%; when the temperature rise control output is a level 3 control, the PWM duty cycle is reduced by 30%, and the active cooling signal output is activated.

[0096] S2 also includes S23;

[0097] S23. After the controller completes the execution of the first control strategy, it performs a thermal balance analysis on the heat distribution of the entire LED light strip area and outputs the thermal balance index N1.

[0098] Thermal equilibrium analysis calculates the standard deviation of the temperature values ​​T at all temperature acquisition points within the current sampling period and compares it with the benchmark standard deviation of the temperature values ​​T recorded under thermal temperature equilibrium conditions during historical operation phases to obtain the equilibrium index N1.

[0099] If the balance index N1 result is <0.9, the controller determines that the current LED strip heat distribution is uneven, and at this time the thermo-optical coupling correction mechanism is triggered;

[0100] If the balance index N1 is ≥0.9, the controller determines that the current LED strip has a uniform heat distribution and maintains the current output power.

[0101] In this embodiment, the controller of the method first bases the temperature values ​​T of multiple i-th acquisition points in a standard feature set. iThe system performs a weighted average of temperature data within the same sampling period to obtain the current period's average temperature, Tavg. The core purpose of this design is to smooth out instantaneous fluctuations and avoid misjudgments caused by local anomalies. For example, when external airflow briefly passes over a region, the temperature at that point may drop instantaneously. Without weighted averaging, the system might mistakenly believe that the region has cooled down completely, thus prematurely stopping temperature control. By taking the weighted average Tavg and then calculating the deviation ΔTi, the true thermal equilibrium state of the region can be more accurately reflected, providing noise reduction and disturbance resistance. After calculating the deviation value ΔTi for each sampling point, the controller stores these deviation values ​​in spatial coordinates, forming a temperature deviation matrix ΔTmap(x,y). This matrix structure clearly displays the heat distribution gradient, helping the system quickly identify local high-temperature accumulation points. When the deviation of any sampling point exceeds a safety threshold, the corresponding coordinate area is immediately marked as a "heat accumulation area." This spatialized heat distribution marking method avoids the "temperature averaging misjudgment" problem inherent in traditional single-point monitoring. For example, if the left side of an LED light strip experiences concentrated overheating while the right side remains at a normal temperature, traditional global average control would mask the anomaly on the left. This design, however, uses spatial matrix positioning to achieve millimeter-level local hotspot identification, thus preventing the spread of thermal imbalance at its source. Once the controller identifies the heat accumulation area, it immediately executes the first control strategy, which includes temperature rise control and PWM duty cycle control. Temperature rise control employs a three-level response mechanism, designed to reduce power output in stages to prevent sudden brightness drops. Specifically, when ΔTi exceeds the safe value of +2℃, the system executes level one control, reducing power to 90% of the rated power; when it exceeds +4℃, level three control is executed, reducing power to 70% of the rated power. This step-by-step limiting design reflects the linear temperature-power regression relationship. Its physical meaning lies in releasing the heat load in a controlled manner, rather than a "hard cutoff," avoiding sudden brightness changes and visual discomfort caused by excessive power reduction. Simultaneously, the controller synchronously adjusts the PWM duty cycle, causing the light output in the heat accumulation area to decrease proportionally (10%, 20%, and 30% respectively), and initiates active cooling signal output under three-level control, achieving rapid cooling through hardware and software collaboration. If only single temperature control is relied upon without PWM limiting, the LED chip will cool down, but the light output will exhibit significant jitter and poor stability. This design balances thermal stability and visual uniformity through dual regulation of power and duty cycle. After the first control strategy is completed, the thermal equilibrium analysis stage begins. This stage calculates the thermal equilibrium index N1 to determine whether the current heat distribution has returned to the normal range. The significance of this step is to form a "dynamic verification closed loop," preventing the system from continuously executing control actions under overcooled or overcompensated conditions. By calculating the ratio of the current temperature standard deviation σT to the baseline standard deviation σT,ref from the historical equilibrium stage, the uniformity of the heat distribution can be objectively reflected.When N1 < 0.9, it indicates that local overheating still exists, and the system will automatically trigger the thermo-optical coupling correction mechanism for the next step of luminous efficacy compensation; when N1 ≥ 0.9, the current output power will be maintained. This judgment method based on statistical standard deviation has a clear physical meaning—the smaller the standard deviation, the more uniform the temperature field and the more stable the overall thermal balance of the LED strip. This method is more adaptive than the traditional threshold triggering mode and can prevent false triggering caused by environmental disturbances.

[0102] Example 4: Please refer to Figure 1 Specifically: S3 includes S31;

[0103] S31. After triggering the thermo-optical coupling correction mechanism, the controller collects the actual luminous flux L of the i-th acquisition point at each luminous flux acquisition point in real time. i And combined with the deviation value △T of the i-th collection point i Perform thermo-optical coupling correction calculations and output the target luminous flux Lcorr at the i-th acquisition point. i ;

[0104] The target luminous flux Lcorr at the i-th acquisition point i The specific calculation formula is as follows:

[0105] In the formula, k2 represents the luminous efficacy correction coefficient, with a value range of 0.05-0.25, initially set at 0.05, and Tmax represents the upper limit of the allowable operating temperature of the LED light strip.

[0106] In this embodiment, when the thermal equilibrium index N1 output during the thermal equilibrium analysis stage is lower than a set threshold (e.g., 0.9), the controller automatically triggers a thermo-optical coupling correction mechanism. This mechanism aims to compensate for the luminous flux loss caused by the temperature control stage, ensuring the LED strip maintains thermal stability while preserving visual brightness uniformity. Because the luminous efficiency of LED chips has a significant negative correlation with junction temperature, luminous flux typically decreases by about 2% to 3% when the temperature increases by 10°C. If only thermal control is implemented without considering light compensation, although the system reduces the risk of overheating, local dark areas or brightness fluctuations may occur, leading to uneven illuminance distribution. By introducing thermo-optical coupling correction calculations, a dynamic balance between "cooling and brightening" can be achieved, thereby maintaining overall visual consistency. During this stage, the controller collects the actual luminous flux L at each luminous flux collection point in real time. i And combined with the corresponding temperature deviation value ΔT i Perform thermo-optical coupling correction calculations and output the corrected target luminous flux Lcorr. iThe physical meaning of the thermo-optical coupling correction formula is that when the temperature of the i-th acquisition point is closer to Tmax, the term in parentheses approaches 0, and the system automatically suppresses luminous flux compensation; conversely, when the temperature is lower, the system allows for a moderate increase in luminous flux output to achieve dynamic photothermal balance between regions. For example, when the temperature of a local area drops by 5℃, ΔTi is negative, then the correction coefficient term (1−Ti / Tmax) is positive, and the controller increases the target luminous flux Lcorr. i The compensation coefficient is approximately 1% to 2%; however, for high-temperature regions (e.g., Ti close to Tmax−2℃), the compensation coefficient approaches zero, and the system no longer increases brightness, thus avoiding thermal rebound. This differentiated correction method is equivalent to establishing a "thermal regulating valve" at the light output level, possessing self-suppression and self-balancing characteristics. After adopting this thermo-optical coupling correction algorithm, the system achieves secondary equilibrium of temperature distribution at the luminous flux level, enabling thermal management and brightness control to form a closed-loop linkage. Compared with traditional constant light or constant temperature control, this mechanism not only prevents the brightness decrease problem caused by cooling but also avoids the reheating effect caused by excessive light compensation. Its true physical significance lies in achieving "light-thermal complementary dynamic stability" of the LED strip by controlling the interaction between light output and junction temperature. The controller performs local power fine-tuning based on the Lcorri of each acquisition point, ensuring that different areas operate close to the optimal thermal efficiency point under the same visual brightness. Therefore, this embodiment achieves regional luminous uniformity compensation for LED light strips through thermo-optical coupling correction calculation. Without adding additional hardware, it improves the light output uniformity to within ±3%, and the system luminous efficacy is improved by about 10%. At the same time, it effectively avoids the problems of "brightness drift" and "dark area accumulation" that occur after long-term operation, thereby significantly improving lighting quality and energy efficiency.

[0107] Example 5: Please refer to Figure 1 Specifically: S4 includes S41;

[0108] S41. After the thermo-optical coupling correction mechanism is completed, based on the target luminous flux Lcorr of the i-th acquisition point acquired in real time. i The actual light flux L at the current i-th acquisition point i Perform difference calculation to obtain the luminous flux error value ΔL at the i-th acquisition point. i Based on the light flux error value ΔL at the i-th acquisition point i The target light flux Lcorr at the i-th acquisition point i The relative ratio is used to perform graded adjustment control of the PWM duty cycle in the heat accumulation region; the specific graded content is as follows:

[0109] When the luminous flux error value of the i-th acquisition point is ΔL i |≤0.02·Target luminous flux Lcorr at the i-th acquisition point iWhen the controller determines that the current area's light output is in a stable range, it maintains the current PWM duty cycle unchanged.

[0110] When the target luminous flux Lcorr at the i-th acquisition point is 0.02 i <|Luminous flux error value △L at the i-th acquisition point i |≤0.05·Target luminous flux Lcorr at the i-th acquisition point i When the controller determines that there is a deviation in the light output of the current area, it executes the PWM duty cycle adjustment formula and sets the adjustment coefficient γ to 0.5.

[0111] When the luminous flux error value of the i-th acquisition point is ΔL i |>0.05·Target luminous flux Lcorr at the i-th acquisition point i When the controller determines that there is a significant brightness deviation in the current area, it executes the PWM duty cycle adjustment formula, sets the adjustment coefficient γ to 1, and performs a fast correction operation. The PWM duty cycle adjustment range is ±4%.

[0112] S41 also includes S411;

[0113] S441, The luminous flux error value ΔL based on the i-th acquisition point i Based on the PWM duty cycle adjustment formula, the adjusted PWM duty cycle Dnew at the i-th acquisition point is calculated and output. i The PWM duty cycle is dynamically adjusted.

[0114] The specific form of the PWM duty cycle adjustment formula is: Dnew i =Dold i +γ×Sign(△L i ) × ΔDunit; where Doldi represents the current PWM output duty cycle, Sign represents the error sign function, when ΔLi>0, it indicates insufficient light output, taking +1, when ΔLi<0, it indicates excessive light output, taking −1, ΔDunit represents the minimum adjustable unit duty cycle change step value, with a value range of 0.01-0.02, and γ represents the adjustment coefficient;

[0115] The PWM duty cycle adjustment formula is derived from the classic proportional step control algorithm and the proportional element (P-Control) in the PID control principle. In the traditional PID algorithm, the change in control output Δu is proportional to the system error e(t). However, in the brightness control of LED strip lights, the change in luminous flux error value ΔLi at the i-th acquisition point is nonlinearly related to the visual brightness. If proportional control is used directly, it may lead to overshoot or non-convergence. Therefore, this formula improves it to "sign direction correction + graded step adjustment".

[0116] All values ​​in the formula are in units of luminous flux, and since luminous flux is processed to be dimensionless, the output results are in dimensionless units.

[0117] In this embodiment, after completing the thermo-optical coupling correction, the controller of this method measures the target light flux Lcorr at the i-th acquisition point. i With actual luminous flux L i The difference is calculated to obtain the luminous flux error ΔL. i The purpose of this design is to form a real-time correction closed loop at the light output level to further correct for potential brightness unevenness issues after thermal compensation. During LED strip operation, even when the temperature is balanced, light output in some areas may still deviate from the target value due to driving voltage fluctuations or chip aging. Without this differential correction mechanism, a "bistable light-temperature offset" phenomenon will occur, meaning the system operates in a state of thermal equilibrium but unstable light output, resulting in subtle differences in illuminance distribution. This is addressed by introducing a luminous flux error ΔL. i The system can directly and quantitatively compensate for light output deviations, achieving true visual consistency control. To ensure a smooth and flicker-free adjustment process, this implementation adopts a graded adjustment strategy, dynamically setting the adjustment intensity based on the error amplitude. When |ΔL i | Less than 0.02·Lcorr i When the error is within the middle range (0.02·Lcorr), the system considers the light output stable and does not make any adjustments to avoid frequent small corrections that could cause PWM signal jitter. i ~0.05·Lcorr i When |ΔL| is reached, the controller performs a slow correction, with the adjustment coefficient γ set to 0.5, to correct the brightness deviation slightly; when |ΔL| is reached... i |More than 0.05·Lcorr i When the output deviates significantly, it indicates that the local light output is significantly off-target. At this time, the controller performs a rapid correction, setting γ to 1 and adjusting the PWM duty cycle by ±4%. The design logic of this hierarchical strategy is to transform the nonlinear response of the light output into piecewise linear control. The physical meaning is to suppress the light flicker and electromagnetic interference caused by large PWM changes through small-step incremental correction.

[0118] For example, if the brightness of a certain area is still about 4% lower than the target value after temperature compensation, the controller only needs to increase the PWM duty cycle by about 2% to restore the illuminance balance without causing a visual jump. The controller is based on the luminous flux error ΔL. i Further calculate the new PWM duty cycle Dnew iThe physical meaning of this formula lies in enabling the system to achieve self-convergent adjustment along the error gradient by directly linking the PWM duty cycle change to the error direction. This control method is based on an improved structure of the proportional step control algorithm and the proportional element (P-Control) in PID control, abandoning the traditional PID integral element to avoid the cumulative offset problem of LED brightness, resulting in faster system response and more stable control results. Through this hierarchical and directional step control mechanism, PWM correction can be completed in milliseconds without causing brightness flicker or power fluctuations. Its true physical meaning lies in adjusting the average drive power within the linear range through a limited amplitude pulse width change, thereby achieving a high degree of matching between light intensity output and energy input. Compared with traditional constant light control, this implementation can quickly fine-tune according to real-time deviations, keeping the overall light output error of the LED strip within ±2%.

[0119] Example 6: Please refer to Figure 1 and Figure 2 An LED strip light-emitting controller includes a thermal light acquisition module, a thermal balance analysis module, a thermal light coupling correction module, and a PWM duty cycle adjustment module.

[0120] The thermal light acquisition module periodically collects temperature and luminous flux data by setting multiple acquisition points in the installation area of ​​the LED light strip, and transmits the temperature and luminous flux data to the controller for preprocessing to obtain a standard feature set.

[0121] The thermal equilibrium analysis module marks the heat accumulation area based on the standard feature set and executes the first control strategy. After the first control strategy is completed, thermal equilibrium analysis is performed. If the heat distribution is still abnormal, the thermal-optical coupling correction mechanism is triggered.

[0122] The thermo-optical coupling correction module, after triggering the thermo-optical coupling correction mechanism, performs thermo-optical coupling correction calculations by the controller, and adaptively corrects the power output of the LED light strip based on the calculation results;

[0123] The PWM duty cycle adjustment module performs differential calculation based on the thermal-optical coupling correction result after correction, and performs graded adjustment control on the PWM duty cycle of each region based on the differential calculation result.

[0124] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A method for controlling the light emission of an LED strip, characterized in that: Includes the following steps: S1. Set up multiple acquisition points in the installation area of ​​the LED light strip, periodically collect temperature data and luminous flux data, and transmit the temperature data and luminous flux data to the controller, where they are preprocessed to obtain a standard feature set; S2. Mark the heat accumulation area based on the standard feature set and execute the first control strategy. After the first control strategy is executed, perform heat balance analysis. If the heat distribution is still abnormal, trigger the thermo-optical coupling correction mechanism. S3. After triggering the thermo-optical coupling correction mechanism, the controller performs thermo-optical coupling correction calculation and adaptively corrects the power output of the LED strip based on the calculation results. S3 includes S31; S31. After triggering the thermo-optical coupling correction mechanism, the controller collects the actual luminous flux L of the i-th acquisition point at each luminous flux acquisition point in real time. i And combined with the deviation value △T of the i-th collection point i Perform thermo-optical coupling correction calculations and output the target luminous flux Lcorr at the i-th acquisition point. i ; The target luminous flux Lcorr at the i-th acquisition point i The specific calculation formula is as follows: In the formula, k2 represents the luminous efficacy correction coefficient, with a value range of 0.05-0.25, initially set at 0.05, and Tmax represents the upper limit of the allowable operating temperature of the LED light strip; S4. After correction, perform difference calculation based on the thermal-optical coupling correction result, and perform graded adjustment control on the PWM duty cycle of each region based on the difference calculation result.

2. The LED strip light emission control method according to claim 1, characterized in that: S1 includes S11; S11. Multiple data collection points are set in the installation area of ​​the LED light strip, using a combination of evenly spaced layout and dense layout in key areas. The data collection points include temperature data collection points and luminous flux data collection points; and a sampling period is set to collect temperature data and luminous flux data in real time. The spacing between the equally spaced installations is 0.5m-1.0m; The key areas for dense deployment include corner locations, areas with weak heat dissipation, and power access points, with a sampling point spacing of less than 0.3m; The controller periodically collects temperature data and light flux data from temperature acquisition points and light flux acquisition points according to a preset sampling period. The sampling period is automatically adjusted according to the rate of environmental change and the system response time, and the value range is 2s-10s.

3. The LED strip light emission control method according to claim 2, characterized in that: S1 further includes S12; S12. A multi-channel A / D conversion circuit is used to transmit the collected temperature data and luminous flux data to the controller via the bus interface. In the controller, the temperature data and luminous flux data are numbered and stored in the form of a two-dimensional matrix to form a temperature dataset containing the spatial coordinates (x, y) and temperature values ​​of each point. The corresponding luminous flux data is stored in the same spatial distribution to form a luminous flux dataset. The spatial coordinates (x, y) represent the horizontal axis coordinates and the vertical axis coordinates. The temperature dataset and luminous flux dataset are preprocessed to obtain a standard feature set. The preprocessing is performed by using the maximum and minimum range method to perform dimensionless processing on all parameters in the temperature dataset and luminous flux dataset, thereby eliminating the dimensional influence between all parameters. The standard feature set includes the temperature value T of the i-th sampling point. i And the luminous flux L at the i-th acquisition point i .

4. The LED strip light emission control method according to claim 3, characterized in that: S2 includes S21; S21. Temperature values ​​T at multiple i-th acquisition points based on the standard feature set. i The average temperature value Tavg for the current period is obtained by performing a weighted average of all temperature data within the same sampling period. The average temperature value Tavg of the current period is compared with the temperature value T of the i-th sampling point. i Perform difference calculation and output the deviation value △T of the i-th acquisition point. i ; The controller calculates the deviation value △T at the i-th acquisition point. i Then, the deviation values ​​ΔT of all i-th sampling points are... i Stored according to spatial coordinates, forming a temperature deviation matrix ΔTmap(x,y). When the deviation value ΔT of the i-th collection point i When the LED light strip exceeds the safe value, the corresponding spatial coordinate (x, y) area will be marked as a heat accumulation area.

5. The LED strip light emission control method according to claim 4, characterized in that: S2 further includes S22; S22. When a region is marked as a heat accumulation area, the controller executes a first control strategy, which includes temperature rise control and PWM duty cycle control. The temperature rise control is achieved by adjusting the deviation value ΔT of the i-th sampling point after marking the heat accumulation area. i The deviation value ΔT of the i-th acquisition point in the three consecutive sampling periods is calculated. i The temperature rise will be monitored and a relevant control mechanism will be implemented accordingly; the details are as follows: When the deviation value ΔT of the i-th sampling point in the sampling period i When the temperature is within the range of the safe value to the safe value +2℃, Level 1 control is executed; the Level 1 control reduces the power in the current heat accumulation area of ​​the LED strip to 90% of the rated power. When the deviation value ΔT of the i-th sampling point in the sampling period i When the LED light strip is within a safe temperature range of +2℃ to -4℃, secondary control is implemented; the secondary control reduces the power in the current heat accumulation area of ​​the LED light strip to 80% of the rated power. When the deviation value ΔT of the i-th sampling point in the sampling period i When the temperature exceeds the LED light strip's safety value of +4℃, a three-level control is implemented; this three-level control reduces the power in the current heat-concentrated area of ​​the LED light strip to 70% of its rated power. The PWM duty cycle control adjusts the PWM duty cycle based on the generated relevant control mechanism. The specific adjustments are as follows: when the temperature rise control output is a level 1 control, the PWM duty cycle is reduced by 10%; when the temperature rise control output is a level 2 control, the PWM duty cycle is reduced by 20%; when the temperature rise control output is a level 3 control, the PWM duty cycle is reduced by 30%, and the active heat dissipation signal output is activated.

6. The LED strip light emission control method according to claim 5, characterized in that: S2 also includes S23; S23. After the controller completes the execution of the first control strategy, it performs a thermal balance analysis on the heat distribution of the entire LED light strip area and outputs the thermal balance index N1. The thermal equilibrium analysis calculates the standard deviation of the temperature values ​​T at all temperature collection points within the current sampling period and compares it with the benchmark standard deviation of the temperature values ​​T recorded under thermal temperature equilibrium conditions during historical operation phases to obtain the thermal equilibrium index N1. If the thermal balance index N1 result is <0.9, the controller determines that the current LED strip has uneven heat distribution, and triggers the thermal-optical coupling correction mechanism. If the thermal balance index N1 is ≥0.9, the controller determines that the current LED strip has a uniform heat distribution and maintains the current output power.

7. The LED strip light emission control method according to claim 6, characterized in that: S4 includes S41; S41. After the thermo-optical coupling correction mechanism is completed, based on the target luminous flux Lcorr of the i-th acquisition point acquired in real time. i The actual light flux L at the current i-th acquisition point i Perform difference calculation to obtain the luminous flux error value ΔL at the i-th acquisition point. i Based on the light flux error value ΔL at the i-th acquisition point i The target light flux Lcorr at the i-th acquisition point i The relative ratio is used to perform graded adjustment control of the PWM duty cycle in the heat accumulation region; the specific graded content is as follows: When the luminous flux error value of the i-th acquisition point is ΔL i |≤0.02·Target luminous flux Lcorr at the i-th acquisition point i When the controller determines that the current area's light output is in a stable range, it maintains the current PWM duty cycle unchanged. When the target luminous flux Lcorr at the i-th acquisition point is 0.02 i <|Luminous flux error value △L at the i-th acquisition point i |≤0.05·Target luminous flux Lcorr at the i-th acquisition point i When the controller determines that there is a deviation in the light output of the current area, it executes the PWM duty cycle adjustment formula and sets the adjustment coefficient γ to 0.

5. When the luminous flux error value of the i-th acquisition point is ΔL i |>0.05·Target luminous flux Lcorr at the i-th acquisition point i When the controller determines that there is a significant brightness deviation in the current area, it executes the PWM duty cycle adjustment formula, sets the adjustment coefficient γ to 1, and performs a fast correction operation. The PWM duty cycle adjustment range is ±4%.

8. The LED strip light emission control method according to claim 7, characterized in that: S41 further includes S411; S411, the luminous flux error value ΔL based on the i-th acquisition point i Based on the PWM duty cycle adjustment formula, the adjusted PWM duty cycle Dnew at the i-th acquisition point is calculated and output. i The PWM duty cycle is dynamically adjusted. The specific form of the PWM duty cycle adjustment formula is: Dnew i =Dold i +γ×Sign(△L i ) × △Dunit; where Doldi represents the current PWM output duty cycle, △Dunit represents the minimum adjustable unit duty cycle change step value, with a value range of 0.01-0.02, γ represents the adjustment coefficient, and Sign represents the error sign function.

9. An LED strip light-emitting controller, applied to the LED strip light-emitting control method according to any one of claims 1-8, characterized in that: It includes a thermo-optical acquisition module, a thermal equilibrium analysis module, a thermo-optical coupling correction module, and a PWM duty cycle adjustment module; The thermal light acquisition module periodically collects temperature and luminous flux data by setting multiple acquisition points in the installation area of ​​the LED light strip, and transmits the temperature and luminous flux data to the controller for preprocessing to obtain a standard feature set. The thermal equilibrium analysis module marks the heat accumulation area based on a standard feature set and executes the first control strategy. After the first control strategy is completed, thermal equilibrium analysis is performed. If the heat distribution is still abnormal, the thermal-optical coupling correction mechanism is triggered. The thermo-optical coupling correction module, after triggering the thermo-optical coupling correction mechanism, performs thermo-optical coupling correction calculations by the controller, and adaptively corrects the power output of the LED light strip based on the calculation results. The PWM duty cycle adjustment module performs differential calculation based on the thermal-optical coupling correction result after correction, and performs graded adjustment control on the PWM duty cycle of each region based on the differential calculation result.

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