An intelligent monitoring system for predicting the life of high-power LED lamp beads

Abstract

The invention discloses an intelligent monitoring system for predicting the life of high-power LED lamp beads, and relates to the field of intelligent monitoring technology. The system comprises a data acquisition module, which is used to collect real-time current density distribution data of high-power LED lamp beads in a working state, a calculation module, which is used to calculate the hot spot position and hot spot temperature of the lamp beads based on the current density distribution data, an analysis module, which is used to analyze the influence of the hot spot position and the hot spot temperature on the brightness attenuation of the lamp beads, and a drive control module, which is used to adjust the drive current of the lamp beads according to the influence degree, optimize the brightness and extend the life of the lamp beads; the intelligent monitoring system for predicting the life of high-power LED lamp beads solves the problem of brightness attenuation caused by inconsistent current density in the prior art under long-term high-power working conditions.

Description

Technical Field

[0001] The present invention relates to the field of intelligent monitoring technology, and in particular to an intelligent monitoring system for predicting the life of high-power LED lamp beads. Background Art

[0002] In modern lighting technology, high-power LED lamp beads are widely used in industrial lighting, automotive lighting, display equipment and other fields due to their high efficiency, long life and environmental protection characteristics. However, in practical applications, the long-term stability and reliability of high-power LED lamp beads have always been one of the focuses of technical research and application development.

[0003] Existing high-power LED lamp beads usually operate under high current density conditions. Although they have excellent light output performance in the initial stage, as the working time increases, the brightness of the lamp beads will gradually decay due to heat accumulation and material aging caused by uneven current density distribution. This brightness decay problem will significantly affect the service life and performance stability of LED lamp beads. Further analysis shows that the inconsistency of current density will not only aggravate local overheating of the chip, but also cause performance degradation of the packaging material and accelerate the degradation of the optical properties of the LED. In the prior art, some methods attempt to delay brightness decay by optimizing heat dissipation design or improving packaging process, but these improvement schemes are insufficient in dynamically monitoring the working state of the lamp beads and predicting their service life. For example, the more common life monitoring methods currently rely on manual regular detection or simple evaluation based on a single parameter, and lack the ability to monitor and comprehensively analyze multiple parameters in real time. In addition, these methods cannot provide reliable prediction information before the lamp beads experience serious brightness decay, and thus cannot effectively prevent or reduce the impact of brightness decay on practical applications. Therefore, there is a problem of brightness decay caused by inconsistent current density for high-power LED lamp beads under long-term high-power working conditions. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent monitoring system for predicting the life of high-power LED lamp beads, so as to solve the problem of brightness attenuation caused by inconsistent current density under long-term high-power working conditions in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solution: an intelligent monitoring system for predicting the life of high-power LED lamp beads, the system comprising:

[0006] Data acquisition module, used to collect real-time current density distribution data of high-power LED lamp beads in working state;

[0007] A calculation module connected to the data acquisition module is used to calculate the hot spot position and hot spot temperature of the lamp bead based on the current density distribution data;

[0008] The calculation module calculates the hot spot position and hot spot temperature of the lamp bead based on the current density distribution data, further comprising determining the maximum current density area of ​​the LED lamp bead based on the collected current density distribution data, calculating the temperature distribution in the maximum current density area, determining the position with the highest temperature as the hot spot position, and calculating the hot spot temperature based on the hot spot position;

[0009] The analysis module connected to the calculation module is used to analyze the influence of the hot spot position and hot spot temperature on the brightness attenuation of the lamp beads, including segmented fitting of the hot spot position and hot spot temperature data provided by the calculation module with the brightness attenuation degree, setting the critical point as the temperature threshold, analyzing whether the hot spot temperature reaches the influence range on the brightness attenuation, providing a quantitative analysis report, and outputting the brightness attenuation trend curve. The specific formula for segmented fitting is: ;

[0010] Where y represents the brightness drop of the high-power LED lamp bead under a certain temperature condition, x represents the temperature value of the hot spot area, c represents the threshold value of the hot spot temperature on the brightness attenuation, a1 and a2 represent the slope parameters of the piecewise linear fitting, and b1 and b2 represent the intercept parameters of the piecewise linear fitting;

[0011] The driving control module connected to the analysis module is used to adjust the driving current of the lamp beads according to the degree of influence, optimize the brightness and extend the life of the lamp beads, including defining the error variable between the target brightness and the actual brightness, and combining the hot spot temperature as a constraint condition to calculate the optimal driving current, adjust the driving current of the lamp beads in real time, optimize the working state of the lamp beads, and calculate the optimal driving current. The specific formula is:

[0012] ;

[0013] Among them, E represents the total energy consumed by adjusting the driving current when the high-power LED lamp is in working state, u represents the control variable, that is, the driving current, α represents the weight factor, z represents the difference between the target brightness and the actual brightness, T represents the time range for calculating the total energy consumption, and t represents time.

[0014] Preferably, the data acquisition module collects the real-time current density distribution data of the high-power LED lamp beads in the working state, including using a current density sensor to collect dynamic current density data of the high-power LED lamp beads in the operating state, analyzing the sensor data, extracting key amplitude and frequency changes, and judging abnormal fluctuations. The specific formula is: ;

[0015] Among them, s(t) represents the real-time current density signal collected by the current density sensor at time t, A represents the maximum value of the current density signal, and f represents the change speed of the current density signal. represents the initial offset of the current density signal relative to the reference point, and t represents the time;

[0016] Provides real-time current density distribution data to ensure that the calculation module obtains high-precision input.

[0017] Preferably, the calculation module calculates the hot spot position and hot spot temperature of the lamp bead based on the current density distribution data, including using the collected current density data as a heat source input, combining the thermal conductivity parameters of the lamp bead material, calculating the temperature change rate at the hot spot of the lamp bead, and determining the temperature difference distribution. The specific formula is: ;

[0018] Among them, q represents the heat transfer rate, k represents the thermal conductivity parameter of the lamp bead material, ΔQ represents the heat difference between the two areas inside the lamp bead, and Δw represents the physical path length between the hot spot and the heat dissipation area during the heat transfer process.

[0019] Preferably, the method of determining the maximum current density area of ​​the LED lamp bead based on the collected current density distribution data includes collecting real-time current density distribution data, gridding the current density distribution data, setting an average current density threshold D1, dividing into multiple areas, and comparing the average current density of each area one by one. If the average current density of the divided area exceeds the preset threshold D1, the divided area is marked as the maximum current density area, wherein D1=I0×β, D1 is the average current density threshold, I0 is the rated current, and β is the overload factor.

[0020] Preferably, the calculation of the temperature distribution in the maximum current density region includes calculating the heat generation G based on the current density distribution data in the maximum current density region, distributing the heat generation G to various positions in the maximum current density region and calculating the temperature change dH at each position using a heat conduction model. If dH>ΔH max , then record the temperature change at that location, where ΔH max is the maximum allowable value of temperature change, and dH is the calculated temperature change.

[0021] Preferably, determining the position with the highest temperature as the hotspot position includes screening out a set of positions P1 with the largest temperature change based on the temperature change records of each position, performing temperature monitoring on the positions in P1, and recording the temperature H of the highest temperature point. max , based on H max And the preset safety temperature H safe , judge whether it exceeds the safety range, if H max >H safe , then mark the location as a hotspot.

[0022] Preferably, the hotspot temperature calculation based on the hotspot position includes calculating the initial temperature H0 of the hotspot position and the ambient temperature H e , calculate the hot spot temperature H hot , using the formula H hot =H0+(dH×λ), where λ is the temperature amplification factor, monitor the change of hot spot temperature, and record the hot spot temperature for n consecutive times;

[0023] If H hot(n) -H hot(n－1) >ΔH empTh , then the alarm mechanism is triggered, where ΔH empTh is the temperature difference warning value, n represents the number of times the hot spot temperature is recorded, H hot(n) Indicates the hot spot temperature value monitored for the nth time, H hot(n－1) Indicates the hot spot temperature value monitored last time.

[0024] Preferably, the calculation formula of the temperature amplification coefficient λ is: λ=R th ×V loss / B eff ;

[0025] Where λ is the temperature amplification factor, R th Represents thermal resistance, V loss represents the power loss in the hot spot area, B eff Indicates the effective heat dissipation area.

[0026] Preferably, the calculation formula for the difference z between the target brightness and the actual brightness is:

[0027] z=L target -L actual ;

[0028] Where z represents the difference between the target brightness and the actual brightness, L target Indicates the target brightness set by the user, L actual Indicates the actual brightness currently detected.

[0029] It can be seen from the above technical solution that the present invention has the following beneficial effects:

[0030] The intelligent monitoring system for predicting the life of high-power LED lamp beads collects real-time current density distribution data of high-power LED lamp beads in working state through the data acquisition module. The calculation module calculates the hot spot position and hot spot temperature of the lamp beads based on the current density distribution data. The analysis module analyzes the influence of the hot spot position and hot spot temperature on the brightness attenuation of the lamp beads. The drive control module adjusts the driving current of the lamp beads according to the influence degree, optimizes the brightness and prolongs the life of the lamp beads, realizes comprehensive monitoring of the working state of the LED lamp beads, overcomes the limitation of relying on a single parameter evaluation in the prior art, can accurately predict the brightness attenuation of the LED lamp beads based on the hot spot temperature change trend, and realizes early detection of potential brightness attenuation problems. Early warning effectively reduces the impact of brightness degradation on actual applications, can adjust working parameters in real time according to the operating status, extend the service life of the lamp beads and improve their reliability, realize active hotspot monitoring and management, thereby effectively alleviating the problem of local overheating of the chip, and can automatically trigger early warning signals and generate fault diagnosis reports to provide users with real-time feedback, enhance the system's adaptability and fault handling capabilities, significantly reduce the impact of current density inconsistency on LED lamp beads, improve the retention rate of lamp beads' optical properties, effectively extend their service life and maintenance cycle, reduce operating costs, and solve the problem of brightness attenuation caused by inconsistent current density under long-term high-power working conditions in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a schematic diagram of module connection of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] like Figure 1 As shown, the present invention provides a technical solution: an intelligent monitoring system for predicting the life of high-power LED lamp beads, the system comprising:

[0034] Data acquisition module, used to collect real-time current density distribution data of high-power LED lamp beads in working state;

[0035] A calculation module connected to the data acquisition module is used to calculate the hot spot position and hot spot temperature of the lamp bead based on the current density distribution data;

[0036] The analysis module connected to the calculation module is used to analyze the influence of the hot spot position and hot spot temperature on the brightness attenuation of the lamp beads, including segmented fitting of the hot spot position and hot spot temperature data provided by the calculation module with the brightness attenuation degree, setting the critical point as the temperature threshold, analyzing whether the hot spot temperature reaches the influence range on the brightness attenuation, providing a quantitative analysis report, and outputting the brightness attenuation trend curve. The specific formula for segmented fitting is: ;

[0037] Where y represents the brightness drop of the high-power LED lamp bead under a certain temperature condition, x represents the temperature value of the hot spot area, c represents the threshold value of the hot spot temperature on the brightness attenuation, a1 and a2 represent the slope parameters of the piecewise linear fitting, and b1 and b2 represent the intercept parameters of the piecewise linear fitting;

[0038] The driving control module connected to the analysis module is used to adjust the driving current of the lamp beads according to the degree of influence, optimize the brightness and extend the life of the lamp beads, including defining the error variable between the target brightness and the actual brightness, and combining the hot spot temperature as a constraint condition to calculate the optimal driving current, adjust the driving current of the lamp beads in real time, optimize the working state of the lamp beads, and calculate the optimal driving current. The specific formula is:

[0039] ;

[0040] Among them, E represents the total energy consumed by adjusting the driving current when the high-power LED lamp is in working state, u represents the control variable, that is, the driving current, α represents the weight factor, z represents the difference between the target brightness and the actual brightness, T represents the time range for calculating the total energy consumption, and t represents time.

[0041] The system obtains the current density distribution data of high-power LED lamp beads under actual working conditions through the data acquisition module. Then, the calculation module calculates the hot spot position and corresponding hot spot temperature of the lamp beads based on the current density distribution data. This information is processed by the analysis module to evaluate the influence of the hot spot temperature on the brightness attenuation of the lamp beads, and combined with the segmented fitting formula The brightness attenuation trend is segmented and fitted, where y represents the brightness drop of the high-power LED lamp bead under a certain temperature condition, x represents the temperature value of the hot spot area, c is the critical temperature of brightness attenuation, a1 and a2 are the slope parameters of the segmented fitting, and b1 and b2 are the intercept parameters. Based on the above analysis results, the driver adjustment module calculates the error between the target brightness and the actual brightness, and combines the formula Optimize the driving current, where E is the total energy consumption, u is the driving current, α is the weight factor, and z is the deviation between the target brightness and the actual brightness. The adjusted driving current effectively extends the service life of the LED lamp beads by reducing unnecessary energy consumption and controlling the hot spot temperature. Real-time status monitoring of high-power LED lamp beads and quantitative analysis of brightness attenuation trends are achieved, which improves the prediction accuracy of the system. The segmented fitting curve method can accurately describe the brightness attenuation law under different temperature conditions, providing a more scientific basis for driving adjustment. The energy consumption model is combined with the driving current optimization, and energy waste is reduced through dynamic adjustment. At the same time, the service life of the LED lamp beads is effectively extended. Through intelligent analysis and adjustment, manual intervention is reduced and the degree of automation of the system is improved.

[0042] The data acquisition module collects the real-time current density distribution data of the high-power LED lamp beads in the working state, including using the current density sensor to collect the dynamic current density data of the high-power LED lamp beads in the operating state, analyze the sensor data, extract the key amplitude and frequency changes, and judge the abnormal fluctuation. The specific formula is: ;

[0043] Among them, s(t) represents the real-time current density signal collected by the current density sensor at time t, A represents the maximum value of the current density signal, and f represents the change speed of the current density signal. represents the initial offset of the current density signal relative to the reference point, and t represents the time;

[0044] Provides real-time current density distribution data to ensure that the calculation module obtains high-precision input.

[0045] The data acquisition module uses a highly sensitive current density sensor to capture the real-time current density data of high-power LED lamp beads in operation. The collected data is in the form of a dynamic fluctuation signal, which contains key information such as amplitude, frequency and phase. By analyzing these parameters, it is possible to identify abnormal fluctuations in the current density signal, such as current overload, signal distortion or uneven current density distribution. Specifically, the current density signal output by the sensor can be expressed as:

[0046] Description, where A represents the maximum value of the current density, f represents the speed of change of the current density signal, and φ represents the offset of the signal from the reference point. By dynamically monitoring the changes in these parameters, it is possible to make a quick judgment on abnormal fluctuations and provide the analysis results to the calculation module for further life prediction and brightness attenuation analysis. By collecting dynamic current density data through the current density sensor, accurate data under the operating state of the lamp beads can be obtained in real time, ensuring the reliability of subsequent analysis. Based on the amplitude and frequency changes of the dynamic fluctuation signal, it is possible to quickly identify abnormal current density and provide an immediate early warning mechanism for the system. By formulating the change law of the current density signal, high-precision input is provided for the calculation module, further improving the analysis efficiency and life prediction accuracy of the entire system. The high-frequency sampling capability of the acquisition module ensures that the system can update and feedback data changes in real time, providing reliable data support for the subsequent drive adjustment module.

[0047] The calculation module calculates the hot spot position and hot spot temperature of the lamp bead based on the current density distribution data, including using the collected current density data as the heat source input, combining the thermal conductivity parameters of the lamp bead material, calculating the temperature change rate at the hot spot of the lamp bead, and determining the temperature difference distribution. The specific formula is: ;

[0048] Among them, q represents the heat transfer rate, k represents the thermal conductivity parameter of the lamp bead material, ΔQ represents the heat difference between the two areas inside the lamp bead, and Δw represents the physical path length between the hot spot and the heat dissipation area during the heat transfer process.

[0049] The calculation module in this system uses the collected current density distribution data to calculate the hot spot position and hot spot temperature of high-power LED lamp beads. During operation, high-power LED lamp beads will form local hot spots due to uneven current density distribution. The temperature of these areas is a key factor affecting the brightness decay and life of the lamp beads. By using the collected current density data as the heat source input and combining it with the thermal conductivity parameter k of the lamp bead material, the formula can be used Calculate the heat transfer rate, where: ΔQ is the heat difference between the hot spot area and the heat dissipation area, which is determined by the current density data and the material thermal characteristics model; Δw is the physical length of the heat transfer path, which is determined by the structural parameters and geometric distribution of the lamp bead. The calculation results are used to analyze the temperature change rate at the hot spot inside the lamp bead, so as to infer the temperature difference distribution between the hot spot and the heat dissipation area, and provide accurate thermodynamic data input for the subsequent analysis module. By calculating the correlation between the current density data and the heat distribution, the hot spot area inside the lamp bead can be accurately located, and high-precision temperature data can be provided. Using the thermal conductivity parameters of the lamp bead material and combining the physical path length, an accurate heat conduction model is established to provide the analysis module with efficient temperature change prediction capabilities. The hot spot temperature is a key factor affecting the life of LED lamp beads. The system provides a reliable data basis for life prediction and brightness attenuation evaluation by quantifying the temperature change rate. The formulated heat transfer calculation method can adapt to different LED lamp bead materials and structures, improving the scope of application and versatility of the system.

[0050] The calculation module calculates the hot spot position and hot spot temperature of the lamp bead based on the current density distribution data, and also includes determining the maximum current density area of ​​the LED lamp bead based on the collected current density distribution data, calculating the temperature distribution in the maximum current density area, determining the position with the highest temperature as the hot spot position, and calculating the hot spot temperature based on the hot spot position.

[0051] The calculation module first performs spatial analysis on the current density distribution data collected by the data acquisition module to determine the current density distribution inside the LED lamp bead. According to the magnitude of the current density, the system identifies the maximum current density area. Since the current density is positively correlated with the temperature, the maximum current density area usually corresponds to the hot spot area with the highest temperature. Subsequently, the system performs detailed temperature distribution calculations on the maximum current density area, uses a model based on heat conduction and energy conservation to analyze the temperature change in the area, and determines the position with the highest temperature through interpolation or fitting algorithms. This position is defined as the hot spot position, and the hot spot temperature is calculated based on the heat transfer model or infrared thermal imaging data at this position, providing key data input for subsequent analysis modules. Through the correspondence between the maximum current density area and the hot spot area, the hot spot position inside the LED lamp bead is quickly locked, avoiding the complex calculation process of the traditional method. The temperature distribution analysis based on the hot spot position can directly calculate the hot spot temperature of the lamp bead, providing key thermodynamic parameters for life prediction, dynamically adjusting the hot spot position and temperature calculation according to the real-time current density data to adapt to the state changes of the lamp bead under different working conditions. The accurate calculation of the hot spot temperature significantly improves the accuracy and reliability of the lamp bead life prediction, providing a scientific basis for extending the working life of the LED lamp bead.

[0052] Determining the maximum current density area of ​​the LED lamp bead based on the collected current density distribution data includes collecting real-time current density distribution data, gridding the current density distribution data, setting the average current density threshold D1, dividing multiple areas, and comparing the average current density of each area one by one. If the average current density of the divided area exceeds the preset threshold D1, the divided area is marked as the maximum current density area, wherein D1=I0×β, D1 is the average current density threshold, I0 is the rated current, and β is the overload factor.

[0053] The core of this process is to grid the collected real-time current density data and divide it into regions. After obtaining the current density distribution data of the lamp bead through the data acquisition module, the calculation module first divides the surface or interior of the lamp bead into equally spaced gridded small areas. The average current density of each small area is calculated separately. In order to accurately identify the maximum current density area, the system sets an average current density threshold D1, and the calculation formula is: D1 = I0×β, where I0 is the rated current of the LED lamp bead, reflecting the standard current density under normal working conditions; β is the overload factor, which is used to adjust the current threshold to adapt to the identification requirements under different load conditions. By comparing the average current density of each small area with the threshold D1 one by one, the high current density area that exceeds the threshold can be accurately located. These areas are marked as maximum current density areas and passed to subsequent modules for calculation and analysis of hot spot temperatures. Through gridding processing and threshold determination, the maximum current density area can be determined quickly and accurately, improving the accuracy of hotspot identification. The current density threshold is dynamically adjusted using the overload factor β to adapt to different load conditions and working environments. The gridding method effectively reduces the complexity of data processing, enabling the system to analyze the current density distribution in real time and quickly locate key areas. By accurately identifying the maximum current density area, accurate basic data is provided for hotspot temperature calculation, thereby improving the reliability of the system's life prediction.

[0054] Calculating the temperature distribution in the maximum current density area includes calculating the heat generation G based on the current density distribution data in the maximum current density area, distributing the heat generation G to various locations in the maximum current density area, and calculating the temperature change dH at each location using a heat conduction model. If dH>ΔH max , then record the temperature change at that location, where ΔH max is the maximum allowable value of temperature change, and dH is the calculated temperature change.

[0055] The core of this method is to accurately calculate the temperature distribution in the maximum current density area through the relationship between current density distribution data and heat generation and conduction: based on the current density distribution data in the maximum current density area, the heat generation G at each position is calculated according to the law of converting electrical energy into thermal energy, and the heat generation G is distributed to each position in the maximum current density area according to the distribution characteristics of current density. A heat source model for each position is established, and the temperature change dH at each position is calculated based on the heat conduction equation in heat transfer, combined with the thermal conductivity and physical structure characteristics of the lamp bead material. The maximum allowable value ΔH of the temperature change is set. max , compare the temperature change dH at each position one by one. If dH>ΔH max , then record the abnormal temperature change at that location and mark it as a potential hot spot area to provide reference data for subsequent life prediction. Through current density data and heat conduction model, the temperature distribution in the maximum current density area is refined and calculated, providing more accurate thermodynamic analysis results, which can quickly identify the location where the temperature change exceeds the threshold, record potential hot spots in real time, and improve the monitoring efficiency of the system. Based on the threshold judgment mechanism, it can filter out meaningless temperature change data and focus on recording and analyzing abnormal hot spots. By adjusting ΔH max The value can be adapted to different usage environments or lamp designs, improving the flexibility of monitoring.

[0056] Determining the location with the highest temperature as the hotspot location includes screening out the location set P1 with the largest temperature change based on the temperature change records of each location, monitoring the temperature of the location in P1, and recording the temperature H of the highest temperature point. max , based on H max And the preset safety temperature H safe , judge whether it exceeds the safety range, if H max >H safe , then mark the location as a hotspot.

[0057] Through the temperature change data recorded in the early stage, several locations with the largest change amplitude are selected to form the location set P1. These locations represent areas where high temperature hot spots may exist, reducing the monitoring cost of non-critical areas. Real-time temperature monitoring is performed on each location in the set P1, and the temperature value is obtained through sensor acquisition or heat conduction model calculation, and the temperature H of the highest temperature point is recorded. max . Set the maximum temperature value H max The preset safety temperature threshold H safe For comparison. If H max >H safe , indicating that the temperature at this location is beyond the safe range and there is a potential life risk, so it is marked as a hot spot. max ≤H safe, indicating that the temperature at this location is within the normal range and no additional marking is required. The above method can efficiently and accurately locate the hotspot position of the LED lamp bead, providing key data for life prediction and brightness attenuation analysis. By screening the location set P1 with the largest temperature change and recording the highest temperature point based on real-time monitoring, the accuracy of hotspot positioning is effectively improved. Only key areas with large temperature changes are monitored in detail, reducing the consumption of monitoring resources for non-important areas and improving system efficiency. safe By comparing the temperature, it can quickly identify the location where the temperature exceeds the standard, issue risk warnings in a timely manner, ensure the safe operation of the system, adapt to real-time data changes, dynamically update hotspot locations, and ensure the accuracy and real-time nature of the monitoring results.

[0058] The hotspot temperature is calculated based on the hotspot position, including the initial temperature H0 based on the hotspot position and the ambient temperature H e , calculate the hot spot temperature H hot , using the formula H hot =H0+(dH×λ), where λ is the temperature amplification factor, monitor the change of hot spot temperature, and record the hot spot temperature for n consecutive times;

[0059] If H hot(n) -H hot(n－1) >ΔH empTh , then the alarm mechanism is triggered, where ΔH empTh is the temperature difference warning value, n represents the number of times the hot spot temperature is recorded, H hot(n) Indicates the hot spot temperature value monitored for the nth time, H hot(n－1) Indicates the hot spot temperature value monitored last time.

[0060] Using the initial temperature H0 at the hotspot and the ambient temperature H e As the basic data, the hot spot temperature H is calculated by superimposing the temperature change dH and the temperature amplification factor λ. hot The introduction of the temperature amplification coefficient λ is used to reflect the nonlinear increase in hot spot temperature due to heat accumulation in actual work. The temperature at the hot spot position is monitored n times continuously to form a time series of temperature changes. This process helps to capture the trend of hot spot temperature changes, especially in the early stages of abnormal temperature rise. By calculating the difference between two consecutive monitored temperatures H hot(n) , determine whether the value exceeds the preset temperature difference warning value ΔH empTh. If the warning value is exceeded, it means that there may be a risk of abnormal temperature rise in the hot spot area. At this time, the alarm mechanism is triggered to prompt the user to take cooling measures or perform equipment maintenance. By introducing the temperature amplification coefficient λ, the impact of heat accumulation on the hot spot temperature is fully considered, making the temperature calculation more in line with the actual situation. Based on continuous monitoring and temperature difference judgment, the system can trigger an alarm at the early stage of abnormal temperature rise, effectively reducing the risk of overheating and failure of LED lamp beads. Through continuous n-time monitoring and dynamic judgment, the system realizes real-time tracking of hot spot temperature changes, ensuring the timeliness and reliability of monitoring. The introduction of the alarm mechanism significantly enhances the system's active safety protection capabilities, helps to extend the service life of LED lamp beads and ensure operational stability.

[0061] The calculation formula of temperature amplification coefficient λ is: λ=R th ×V loss / B eff ;

[0062] Where λ is the temperature amplification factor, R th Represents thermal resistance, V loss represents the power loss in the hot spot area, B eff Indicates the effective heat dissipation area.

[0063] The temperature amplification factor λ is a key parameter of the temperature accumulation effect in the hot spot area and is used to correct the calculation results of the hot spot temperature. Formula λ=R th ×V loss / B eff ; It shows that the temperature amplification factor is determined by three key parameters: R th , the higher the thermal resistance value, the greater the temperature loss during heat transfer; V loss , the higher the power loss in the hot spot area, the more heat is generated; B eff , the larger the effective heat dissipation area, the higher the heat dissipation efficiency and the smaller the temperature amplification effect. Thermal resistance R th It can be calculated through the thermal physical parameters of the LED lamp bead material or obtained through experimental measurement; power loss V loss It can be calculated from current density and resistance, for example: V loss =I 2 ×R, where I is the current density and R is the resistance of the hot spot area; the heat dissipation area is B eff It is determined by the geometric structure and heat dissipation design of the lamp bead, which can be obtained through geometric modeling or actual measurement. The calculated temperature amplification factor λ is applied to the hot spot temperature calculation formula: H hot=H0+(dH×λ), which is used to correct the influence of temperature change dH, so as to more accurately predict the temperature of the hot spot area. By incorporating thermal resistance, power loss and heat dissipation area into the formula, the key factors affecting temperature amplification are fully considered, making the calculation of temperature amplification coefficient more scientific and reasonable. The formula parameter R th 、V loss and B eff It can be flexibly adjusted according to different LED lamp materials and designs, and adapt to a variety of working environments and heat dissipation designs. The introduction of the temperature amplification coefficient significantly improves the accuracy of hot spot temperature calculation, providing more reliable data support for life prediction and abnormality detection. By analyzing the influence of each parameter in the formula, the heat dissipation structure design of the lamp bead can be optimized, such as reducing the thermal resistance R th Or increase the effective heat dissipation area B eff , thereby reducing the temperature amplification effect and improving the reliability and life of LED lamp beads.

[0064] The calculation formula for the difference z between the target brightness and the actual brightness is: z=L target -L actual ;

[0065] Where z represents the difference between the target brightness and the actual brightness, L target Indicates the target brightness set by the user, L actual Indicates the actual brightness currently detected.

[0066] Users can set the target brightness L through the system setting module according to application requirements target This value is usually determined by the ideal working conditions of the lamp bead or the lighting requirements of the application scenario, such as the lighting standard of a specific area or the optimal value of equipment performance. The actual brightness L of the current LED lamp bead is detected in real time through the brightness sensor actual The brightness sensor converts the detected light intensity value into a standard brightness value for comparison with the target brightness. target -L actual Calculate the target brightness L target The actual brightness L actual The difference z between the target brightness and the actual brightness, when z=0, it means that the target brightness is consistent with the actual brightness; when z>0, the actual brightness is lower than the target brightness; when z<0, the actual brightness is higher than the target brightness. The calculation result of the difference z will be passed to the drive adjustment module. The drive module dynamically adjusts the driving current of the LED lamp beads according to the difference, so that the actual brightness approaches the target brightness, thereby maintaining the brightness stability of the system. By calculating the difference z between the target brightness and the actual brightness, real-time monitoring and precise adjustment of the brightness are achieved. By dynamically adjusting the driving current, the system can respond quickly when the actual brightness fluctuates and recover to the target brightness, ensuring the consistency and stability of the brightness. Users can customize the target brightness L according to their needs.target , making the system adaptable to a variety of application scenarios, thereby improving the flexibility and user experience of the lamp bead system, and by avoiding excessively high or low brightness output, reducing the overload or inefficient operation of the lamp beads, thereby extending the working life of the LED lamp beads.

[0067] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent monitoring system for predicting the life of high-power LED lamp beads, characterized in that: The system comprises: Data acquisition module, used to collect real-time current density distribution data of high-power LED lamp beads in working state; A calculation module connected to the data acquisition module is used to calculate the hot spot position and hot spot temperature of the lamp bead based on the current density distribution data; The calculation module calculates the hot spot position and hot spot temperature of the lamp bead based on the current density distribution data, further comprising determining the maximum current density area of ​​the LED lamp bead based on the collected current density distribution data, calculating the temperature distribution in the maximum current density area, determining the position with the highest temperature as the hot spot position, and calculating the hot spot temperature based on the hot spot position; The analysis module connected to the calculation module is used to analyze the influence of the hot spot position and hot spot temperature on the brightness attenuation of the lamp beads, including segmented fitting of the hot spot position and hot spot temperature data provided by the calculation module with the brightness attenuation degree, setting the critical point as the temperature threshold, analyzing whether the hot spot temperature reaches the influence range on the brightness attenuation, providing a quantitative analysis report, and outputting the brightness attenuation trend curve. The specific formula for segmented fitting is: ; Where y represents the brightness drop of the high-power LED lamp bead under a certain temperature condition, x represents the temperature value of the hot spot area, c represents the threshold value of the hot spot temperature on the brightness attenuation, a1 and a2 represent the slope parameters of the piecewise linear fitting, and b1 and b2 represent the intercept parameters of the piecewise linear fitting; The driving control module connected to the analysis module is used to adjust the driving current of the lamp beads according to the degree of influence, optimize the brightness and extend the life of the lamp beads, including defining the error variable between the target brightness and the actual brightness, and combining the hot spot temperature as a constraint condition to calculate the optimal driving current, adjust the driving current of the lamp beads in real time, optimize the working state of the lamp beads, and calculate the optimal driving current. The specific formula is: ； Among them, E represents the total energy consumed by adjusting the driving current when the high-power LED lamp is in working state, u represents the control variable, that is, the driving current, α represents the weight factor, z represents the difference between the target brightness and the actual brightness, T represents the time range for calculating the total energy consumption, and t represents time.

2. The intelligent monitoring system for predicting the life of high-power LED lamp beads according to claim 1 is characterized in that: The data acquisition module collects the real-time current density distribution data of the high-power LED lamp beads in the working state, including using the current density sensor to collect the dynamic current density data of the high-power LED lamp beads in the operating state, analyze the sensor data, extract the key amplitude and frequency changes, and judge the abnormal fluctuation. The specific formula is: ; Among them, s(t) represents the real-time current density signal collected by the current density sensor at time t, A represents the maximum value of the current density signal, and f represents the change speed of the current density signal. represents the initial offset of the current density signal relative to the reference point, and t represents the time; Provides real-time current density distribution data to ensure that the calculation module obtains high-precision input.

3. The intelligent monitoring system for predicting the life of high-power LED lamp beads according to claim 1 is characterized in that: The calculation module calculates the hot spot position and hot spot temperature of the lamp bead based on the current density distribution data, including using the collected current density data as a heat source input, combining the thermal conductivity parameters of the lamp bead material, calculating the temperature change rate at the hot spot of the lamp bead, and determining the temperature difference distribution. The specific formula is: ; Among them, q represents the temperature change rate at the hot spot of the lamp bead, k represents the thermal conductivity parameter of the lamp bead material, ΔQ represents the heat difference between the two areas inside the lamp bead, and Δw represents the physical path length between the hot spot and the heat dissipation area during the heat transfer process.

4. The intelligent monitoring system for predicting the life of high-power LED lamp beads according to claim 1 is characterized in that: The method of determining the maximum current density area of ​​the LED lamp bead based on the collected current density distribution data includes collecting real-time current density distribution data, gridding the current density distribution data, setting an average current density threshold D1, dividing multiple areas, and comparing the average current density of each area one by one. If the average current density of the divided area exceeds the preset threshold D1, the divided area is marked as the maximum current density area, wherein D1=I0×β, D1 is the average current density threshold, I0 is the rated current, and β is the overload factor.

5. The intelligent monitoring system for predicting the life of high-power LED lamp beads according to claim 1 is characterized in that: The calculation of the temperature distribution in the maximum current density region includes calculating the heat generation G based on the current density distribution data in the maximum current density region, distributing the heat generation G to various positions in the maximum current density region and calculating the temperature change dH at each position using a heat conduction model. If dH>ΔH max , then record the temperature change at that location, where ΔH max is the maximum allowable value of temperature change, and dH is the calculated temperature change.

6. The intelligent monitoring system for predicting the life of high-power LED lamp beads according to claim 5, characterized in that: The method of determining the location with the highest temperature as the hotspot location includes screening out a location set P1 with the largest temperature change based on the temperature change record of each location, performing temperature monitoring on the locations in P1, and recording the temperature H of the highest temperature point. max , based on H max And the preset safety temperature H safe , to determine whether it exceeds the safety range. If H max >H safe , then mark the location as a hotspot.

7. The intelligent monitoring system for predicting the life of high-power LED lamp beads according to claim 5, characterized in that: The hot spot temperature calculation based on the hot spot position includes calculating the hot spot temperature based on the initial temperature H0 of the hot spot position and the ambient temperature H e , calculate the hot spot temperature H hot , using the formula H hot =H0+(dH×λ), where λ is the temperature amplification factor, monitor the change of hot spot temperature, and record the hot spot temperature for n consecutive times; If H hot(n) -H hot(n－1) >ΔH empTh , then the alarm mechanism is triggered, where ΔH empTh is the temperature difference warning value, n represents the number of times the hot spot temperature is recorded, H hot(n) Indicates the hot spot temperature value monitored for the nth time, H hot(n－1) Indicates the hot spot temperature value monitored last time.

8. The intelligent monitoring system for predicting the life of high-power LED lamp beads according to claim 7, characterized in that: The calculation formula of the temperature amplification coefficient λ is: λ=R th ×V loss / B eff ; Where λ is the temperature amplification factor, R th Represents thermal resistance, V loss represents the power loss in the hot spot area, B eff Indicates the effective heat dissipation area.

9. The intelligent monitoring system for predicting the life of high-power LED lamp beads according to claim 1, characterized in that: The calculation formula of the difference z between the target brightness and the actual brightness is: z=L target -L actual ; Where z represents the difference between the target brightness and the actual brightness, L target Indicates the target brightness set by the user, L actual Indicates the actual brightness currently detected.

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