LED vehicle lamp operation monitoring system and method based on data analysis

Abstract

The invention relates to the technical field of electrical performance testing, and particularly discloses an LED vehicle lamp operation monitoring system and method based on data analysis, and the system can accurately obtain the illumination parameters of the environment where an LED vehicle lamp is located, further scientifically analyzes and determines the reference illumination intensity of the LED vehicle lamp, and on this basis, comprehensively monitors and carefully collects the circuit information of the LED vehicle lamp, thereby improving the reliability of the LED vehicle lamp. Through a data analysis technology, each abnormal lamp bead existing in the LED vehicle lamp is accurately positioned, the abnormal lamp beads are specifically adjusted according to predetermined reference illumination intensity, after adjustment is completed, the running state parameters of the LED vehicle lamp are further monitored, the adjustment adaptation index of the LED vehicle lamp is evaluated accordingly, and the adjustment adaptation index of the LED vehicle lamp is evaluated according to the running state parameters of the LED vehicle lamp. Therefore, whether further performance adjustment needs to be carried out or not is intelligently judged, the adjustment effect is fed back in time, and therefore it is ensured that the made adjustment can fully meet set performance indexes.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical performance testing, and in particular to a system and method for monitoring the operation of an LED vehicle lamp based on data analysis. Background Art

[0002] With the rapid development of automobile technology, LED headlights have gradually become the mainstream choice of modern automobile lighting systems due to their advantages such as high efficiency, long life and low energy consumption. In recent years, LED headlight operation monitoring methods have emerged. By integrating various sensors and processors, the operating status of LED headlights can be monitored in real time and accurately analyzed.

[0003] For example, the invention patent with announcement number CN116540058B announces an LED headlight operation monitoring system based on data analysis, including a processor, which is communicatively connected to a headlight monitoring module, a fault analysis module, a frequency monitoring module and a storage module; the headlight monitoring module is used to monitor and analyze the operation status of the LED headlight: after the LED headlight is turned on, the LED headlight is marked as a monitoring object; the operation coefficient YX of the monitoring object is obtained by numerically calculating the light flux data GT and the color temperature data SW; the operation status of the LED headlight can be monitored and analyzed, and the actual operation status of the LED headlight can be fed back through the operation coefficient.

[0004] For example, the invention patent with publication number CN115561666A discloses a method and system for self-inspection of electric vehicle lamps, which includes collecting the detection voltage signal of the output circuit of the electric vehicle lamp based on a sampling circuit and outputting the sampled voltage; receiving the sampled voltage based on the self-inspection circuit to detect whether the output circuit of the electric vehicle lamp is in a normal working state; controlling the working state of the output circuit of the electric vehicle lamp based on the switch module, and realizing circuit self-inspection, thereby determining whether the output circuit of the electric vehicle lamp meets the requirements for safe operation.

[0005] However, in the process of implementing the embodiments of the present application, it was found that the above-mentioned technology has at least the following technical problems: in the framework of analyzing the abnormal operation of the headlights, the prior art may only confirm the existence of faults at the circuit level, but fail to fully reveal how these faults specifically interfere with the normal operation mechanism of the headlights, and may even ignore the complex situation that some circuits can still maintain basic functional operation despite the existence of abnormalities, and thus fail to take effective measures in time to adjust the operation of the headlights. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides an LED vehicle light operation monitoring system and method based on data analysis, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides an LED car light operation monitoring system based on data analysis, including: a reference analysis module, used to obtain the lighting parameters of the environment to which the LED car light belongs, and analyze the reference light intensity of the LED car light; an abnormal adjustment module, used to monitor and collect circuit information of the LED car light, locate the abnormal lamp beads belonging to the LED car light through data analysis, and adjust the abnormal lamp beads belonging to the LED car light according to the reference light intensity of the LED car light; an operation feedback module, used to monitor the operating status parameters of the LED car light after adjustment, evaluate the adjustment adaptability index of the LED car light, and determine whether to perform performance adjustment and feedback.

[0008] As a further solution, the abnormal lamp beads belonging to the LED car lights are located through data analysis, and the specific positioning process is: the circuit information of the LED car lights specifically refers to the circuit abnormality index of each lamp bead belonging to the LED car lights within the detection period, if the circuit abnormality index of a certain lamp bead belonging to the LED car lights within the detection period is greater than the maximum value of the first circuit abnormality threshold interval, then the lamp bead belonging to the LED car lights is marked as a first-category abnormal lamp bead; if the circuit abnormality index of a certain lamp bead belonging to the LED car lights within the detection period belongs to the first circuit abnormality threshold interval, then the lamp bead belonging to the LED car lights is marked as a normal lamp bead; if the circuit abnormality index of a certain lamp bead belonging to the LED car lights within the detection period is less than the maximum value of the first circuit abnormality threshold interval, then the normal lamp bead is marked as a normal lamp bead. If the circuit abnormality index of a certain lamp bead belonging to the LED car light within the detection period is less than the minimum value of the second circuit abnormality threshold interval or belongs to the second circuit abnormality threshold interval, and the circuit abnormality index of a certain lamp bead belonging to the LED car light within the detection period is greater than the maximum value of the third circuit abnormality threshold interval, then the lamp bead belonging to the LED car light is marked as a third category abnormal lamp bead; if the circuit abnormality index of a certain lamp bead belonging to the LED car light within the detection period is less than the minimum value of the third circuit abnormality threshold interval or belongs to the third circuit abnormality threshold interval, then the lamp bead belonging to the LED car light is marked as a fourth category abnormal lamp bead.

[0009] As a further solution, the abnormal lamp beads belonging to the LED car lights are adjusted, and the specific adjustment process is: obtaining the operating lighting data of the LED car lights during the detection period, and at the same time integrating the circuit abnormality index of each lamp bead belonging to the LED car lights during the detection period, analyzing the lighting compliance coefficient of the LED car lights during the detection period, and matching the adjustment rate of each abnormal lamp bead belonging to the LED car lights; counting the total number of first-category abnormal lamp beads, the total number of second-category abnormal lamp beads, the total number of third-category abnormal lamp beads, the total number of fourth-category abnormal lamp beads and the total number of lamp beads belonging to the LED car lights; obtaining a first compensation value for reference light intensity and a second compensation value for reference light intensity; updating the reference light intensity of the LED car lights during the demand period according to the reference light intensity of the LED car lights during the demand period, the first compensation value for reference light intensity and the second compensation value for reference light intensity, and adjusting the adjustment rate of each abnormal lamp bead belonging to the LED car lights according to the reference light intensity of the LED car lights during the demand period and the The adjustment rate of the abnormal lamp beads adjusts the first type of abnormal lamp beads and the second type of abnormal lamp beads once; the total number of the first type of abnormal lamp beads and the total number of the second type of abnormal lamp beads are added, and the accumulated result is marked as the total number of adjustable abnormal lamp beads; the first compensation value of the reference light intensity is updated according to the total number of adjustable abnormal lamp beads and the total number of the third type of abnormal lamp beads; the second compensation value of the reference light intensity is updated according to the total number of adjustable abnormal lamp beads and the total number of the fourth type of abnormal lamp beads; the first compensation value of the reference light intensity and the second compensation value of the reference light intensity are reinitialized; the reference light intensity of the LED car light in the demand cycle is updated according to the reference light intensity of the LED car light in the demand cycle, the first compensation value of the reference light intensity and the second compensation value of the reference light intensity, and the first type of abnormal lamp beads and the second type of abnormal lamp beads are adjusted for the second time according to the reference light intensity of the LED car light in the demand cycle and the adjustment rate of each abnormal lamp bead belonging to the LED car light.

[0010] As a further solution, the determination of whether to perform performance adjustment and feedback is specifically carried out as follows: extracting an adjustment adaptation threshold from a monitoring database; comparing an adjustment adaptation index of the LED headlight within an adjustment period with the adjustment adaptation threshold; if the adjustment adaptation index of the LED headlight within the adjustment period is greater than or equal to the adjustment adaptation threshold, determining not to perform performance adjustment and feedback; if the adjustment adaptation index of the LED headlight within the adjustment period is less than the adjustment adaptation threshold, determining to perform performance adjustment and feedback.

[0011] As a further solution, the performance adjustment and feedback are performed, and the specific adjustment feedback process is: performing difference processing on the adjustment adaptation threshold and the adjustment adaptation index of the LED headlight within the adjustment period, performing ratio processing on the processing result and the adjustment adaptation threshold, and finally obtaining the adjustment adaptation deviation rate of the LED headlight; adjusting the reference light intensity of the LED headlight within the demand period according to the adjustment adaptation deviation rate of the LED headlight, and generating an adjustment report for feedback.

[0012] The second aspect of the present invention provides an LED car light operation monitoring method based on data analysis, including: step one, obtaining the lighting parameters of the environment to which the LED car light belongs, and analyzing the reference light intensity of the LED car light; step two, monitoring and collecting the circuit information of the LED car light, locating the abnormal lamp beads belonging to the LED car light through data analysis, and adjusting the abnormal lamp beads belonging to the LED car light according to the reference light intensity of the LED car light; step three, monitoring the operating status parameters of the LED car light after adjustment, evaluating the adjustment adaptability index of the LED car light, and determining whether to perform performance adjustment and feedback.

[0013] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention provides an LED headlight operation monitoring system and method based on data analysis, which can accurately obtain the lighting parameters of the environment in which the LED headlight is located, and then scientifically analyze and determine the reference light intensity of the LED headlight. On this basis, the circuit information of the LED headlight is comprehensively monitored and carefully collected. Through data analysis technology, the abnormal lamp beads in the LED headlight are accurately located, and the abnormal lamp beads are targetedly adjusted according to the predetermined reference light intensity. After the adjustment is completed, the operating state parameters of the LED headlight are further monitored, and the adjustment adaptation index of the LED headlight is evaluated accordingly, so as to intelligently determine whether further performance adjustment is needed and timely feedback the adjustment effect, thereby greatly enhancing the efficiency, stability, ability to adapt to changing environments and performance matching of the LED headlight in operation, thereby ensuring that the adjustments made can fully meet the established performance indicators.

[0014] (2) The present invention not only simplifies the process of adjusting the light intensity and improves the adjustment efficiency by initializing the first compensation value of the reference light intensity and the second compensation value of the reference light intensity, but also enables the LED headlight to perform more accurate fine-tuning based on the existing compensation value when adjusting the light intensity next time, which is conducive to faster adaptation to changes in different lighting environments and ensuring the stability and accuracy of the light intensity, thereby improving the overall user experience and effect.

[0015] (3) The present invention avoids excessive or insufficient adjustment by analyzing the illumination compliance coefficient of the LED headlights within the detection period and matching the adjustment rate of each abnormal lamp bead belonging to the LED headlights, thereby effectively reducing the risk of damage to the lamp bead due to improper operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0017] Figure 1 It is a schematic diagram of system module connection of the present invention.

[0018] Figure 2 The figure is a schematic flow chart of the method steps of the present invention. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0020] Reference Figure 1 As shown, the first aspect of the present invention provides an LED vehicle light operation monitoring system based on data analysis, comprising: a reference analysis module, an abnormal adjustment module, an operation feedback module and a monitoring database.

[0021] The reference analysis module is connected to the abnormal adjustment module, the abnormal adjustment module is connected to the operation feedback module, and the reference analysis module, the abnormal adjustment module and the operation feedback module are all connected to the monitoring database.

[0022] The monitoring database is used to store the reference current of the lamp beads belonging to the LED headlights during the demand cycle, the reference power dissipation value of the lamp beads belonging to the LED headlights during the demand cycle, the reference color temperature of the lamp beads belonging to the LED headlights during the demand cycle, the circuit abnormality factor corresponding to the average working current, the circuit abnormality factor corresponding to the average power dissipation value, the circuit abnormality factor corresponding to the average color temperature, the light intensity uniformity definition value, the brightness fluctuation value, the electrical signal frequency fluctuation value, the light compliance factor corresponding to the light intensity uniformity, the light compliance factor corresponding to the brightness fluctuation value, the light compliance factor corresponding to the electrical signal frequency fluctuation value, the weight value corresponding to the circuit abnormality index, the thermal resistance abnormality rate, the flicker frequency, the adjustment adaptation factor corresponding to the thermal resistance abnormality rate, the adjustment adaptation factor corresponding to the flicker frequency, the adjustment adaptation factor corresponding to the lighting compliance improvement ratio, the adjustment adaptation factor corresponding to the circuit abnormality index, the adjustment adaptation threshold, the adjustment rate corresponding to each light compliance coefficient interval, the first circuit abnormality threshold interval, the second circuit abnormality threshold interval and the third circuit abnormality threshold interval.

[0023] The reference analysis module is used to obtain the lighting parameters of the environment to which the LED headlight belongs and analyze the reference lighting intensity of the LED headlight.

[0024] Specifically, the reference light intensity of the LED headlight is analyzed, and the specific analysis process is as follows: the light parameters of the environment to which the LED headlight belongs include the light intensity curve of the environment to which the LED headlight belongs within the detection period, and according to the light intensity curve of the environment to which the LED headlight belongs within the detection period, the average light intensity of the environment to which the LED headlight belongs within the demand period is predicted; the light intensity curve of the environment to which the LED headlight belongs within the detection period refers to a graphical representation of the relationship between the light intensity of the environment to which the LED headlight belongs and changes with time within the detection time period, which can be obtained by monitoring the built-in light sensor of the car; the average light intensity of the environment to which the LED headlight belongs within the demand period refers to the average light intensity of the environment to which the LED headlight belongs within the demand period, and the specific prediction process is as follows: the light intensity curve of the environment to which the LED headlight belongs within the detection period is input into the autoregressive integral moving average model, and the parameters in the autoregressive integral moving average model are determined by the correlation function (such as determining the autoregressive order by the autocorrelation function and determining the moving average order by the partial autocorrelation function, etc.), thereby obtaining the average light intensity prediction model, and predicting the average light intensity of the environment to which the LED headlight belongs within the demand period by the average light intensity prediction model.

[0025] The reference light intensity of the LED headlights during the demand cycle is matched according to the average light intensity of the environment to which the LED headlights belong during the demand cycle, indicating the light intensity level to which the LED headlights should be adjusted during the demand cycle to ensure that they meet the needs of actual application scenarios. The specific matching process is: the reference light intensity corresponding to each average light intensity interval is stored in the monitoring database, and the average light intensity interval to which the average light intensity of the environment to which the LED headlights belong during the demand cycle is queried. The reference light intensity corresponding to the average light intensity interval is the reference light intensity of the LED headlights during the demand cycle matched with the average light intensity of the environment to which the LED headlights belong during the demand cycle.

[0026] The above-mentioned detection cycle refers to the cycle for detecting the environment to which the LED headlights belong. The main purpose of this cycle is to predict the average light intensity of the environment to which the LED headlights belong during the demand cycle. The above-mentioned demand cycle refers to the future time period that the LED headlights are expected to face. This embodiment aims to ensure that the LED headlights can adapt to and meet the light intensity requirements of the demand cycle in advance. The specific duration is determined by the data analysis administrator.

[0027] The abnormal adjustment module is used to monitor and collect circuit information of the LED car lights, locate the abnormal lamp beads belonging to the LED car lights through data analysis, and adjust the abnormal lamp beads belonging to the LED car lights according to the reference light intensity of the LED car lights.

[0028] Specifically, the abnormal lamp beads belonging to the LED car lights are located through data analysis, and the specific positioning process is: the circuit information of the LED car lights specifically refers to the circuit abnormality index of each lamp bead belonging to the LED car lights within the detection period, if the circuit abnormality index of a certain lamp bead belonging to the LED car lights within the detection period is greater than the maximum value of the first circuit abnormality threshold interval, then the lamp bead belonging to the LED car lights is marked as a first-class abnormal lamp bead; if the circuit abnormality index of a certain lamp bead belonging to the LED car lights within the detection period belongs to the first circuit abnormality threshold interval, then the lamp bead belonging to the LED car lights is marked as a normal lamp bead; if the circuit abnormality index of a certain lamp bead belonging to the LED car lights within the detection period is less than the minimum value of the first circuit abnormality threshold interval. And it is greater than the maximum value of the second circuit abnormality threshold interval, the lamp bead belonging to the LED car light is marked as a second type of abnormal lamp bead; if the circuit abnormality index of a certain lamp bead belonging to the LED car light within the detection period is less than the minimum value of the second circuit abnormality threshold interval or belongs to the second circuit abnormality threshold interval, and at the same time, the circuit abnormality index of a certain lamp bead belonging to the LED car light within the detection period is greater than the maximum value of the third circuit abnormality threshold interval, the lamp bead belonging to the LED car light is marked as a third type of abnormal lamp bead; if the circuit abnormality index of a certain lamp bead belonging to the LED car light within the detection period is less than the minimum value of the third circuit abnormality threshold interval or belongs to the third circuit abnormality threshold interval, the lamp bead belonging to the LED car light is marked as a fourth type of abnormal lamp bead.

[0029] It needs to be explained that the first circuit abnormality threshold interval, the second circuit abnormality threshold interval and the third circuit abnormality threshold interval are used as distinguishing criteria to divide the lamp beads belonging to the LED headlights into different types, and are all extracted from the monitoring database; among them, the above-mentioned first circuit abnormality threshold interval is used to define the first type of abnormal lamp beads and the second type of abnormal lamp beads; the above-mentioned second circuit abnormality threshold interval is used to define the second type of abnormal lamp beads and the third type of abnormal lamp beads; the above-mentioned third circuit abnormality threshold interval is used to define the third type of abnormal lamp beads and the fourth type of abnormal lamp beads, wherein there is a numerical interval between the first circuit abnormality threshold interval and the second circuit abnormality threshold interval, and there is also a numerical interval between the second circuit abnormality threshold interval and the third circuit abnormality threshold interval, that is, the minimum value of the first circuit abnormality threshold interval is greater than the maximum value of the second circuit abnormality threshold interval, and the minimum value of the second circuit abnormality threshold interval is greater than the maximum value of the third circuit abnormality threshold interval.

[0030] The above-mentioned first type of abnormal lamp beads appear to be abnormally bright and can be adjusted; the above-mentioned second type of lamp beads appear to be slightly dim and can be adjusted, but can still work normally; the above-mentioned third type of abnormal lamp beads appear to be slightly bright and cannot be adjusted; the above-mentioned fourth type of abnormal lamp beads appear to be completely dark and cannot be adjusted.

[0031] It should be explained that the value in the first circuit abnormality threshold interval is greater than the value in the second circuit abnormality threshold interval, and the value in the second circuit abnormality threshold interval is greater than the value in the third circuit abnormality threshold interval.

[0032] In a specific embodiment, the present invention analyzes the lighting compliance coefficient of the LED headlights during the detection cycle and matches the adjustment rate of each abnormal lamp bead belonging to the LED headlights, thereby avoiding excessive or insufficient adjustment and effectively reducing the risk of lamp bead damage due to improper operation.

[0033] Specifically, the abnormal lamp beads of the LED lamp are adjusted, and the specific adjustment process is as follows: The operating lighting data of the LED headlights within a detection period is obtained, and at the same time, the circuit abnormality index of each lamp bead belonging to the LED headlights within the detection period is integrated to analyze the lighting compliance coefficient of the LED headlights within the detection period, and the adjustment rate of each abnormal lamp bead belonging to the LED headlights is matched; wherein, the adjustment rate of each abnormal lamp bead belonging to the above-mentioned LED headlights represents the rate at which the light intensity of each abnormal lamp bead belonging to the LED headlights is adjusted to the reference light intensity, and the specific matching process is: the adjustment rate corresponding to each lighting compliance coefficient interval stored in the monitoring database is stored, and the lighting compliance coefficient interval stored in the monitoring database to which the lighting compliance coefficient of the LED headlights within the detection period belongs is queried, and the adjustment rate corresponding to the lighting compliance coefficient interval is the adjustment rate of each abnormal lamp bead belonging to the LED headlights matched in this embodiment.

[0034] The total number of the first type of abnormal lamp beads, the total number of the second type of abnormal lamp beads, the total number of the third type of abnormal lamp beads, the total number of the fourth type of abnormal lamp beads and the total number of lamp beads belonging to LED headlights can be obtained by using data analysis software (such as statistical analysis software).

[0035] Obtain a first compensation value for reference light intensity and a second compensation value for reference light intensity, specifically referring to the most recently initialized first compensation value for reference light intensity and the second compensation value for reference light intensity, which can be extracted from the data update log; the above-mentioned first compensation value for reference light intensity is specifically used to compensate for and adjust the light intensity of the third category of abnormal lamp beads. Specifically, when the lamp beads are classified as the third category of abnormalities, the light intensity of the first category of abnormal lamp beads and the second category of abnormal lamp beads will be increased or decreased based on this compensation value to ensure the balance and stability of the overall lighting effect; the above-mentioned second compensation value for reference light intensity is specifically suitable for compensating for the light intensity of the fourth category of abnormal lamp beads. Similar to the first compensation value, when the lamp beads are judged to be the fourth category of abnormalities, the light intensity of the first category of abnormal lamp beads and the second category of abnormal lamp beads will be adjusted based on this value to achieve the expected lighting effect.

[0036] According to the reference light intensity of the LED headlight during the demand cycle, the first compensation value of the reference light intensity and the second compensation value of the reference light intensity, the reference light intensity of the LED headlight during the demand cycle is updated, and the first type of abnormal lamp beads and the second type of abnormal lamp beads are adjusted once according to the reference light intensity of the LED headlight during the demand cycle and the adjustment rate of each abnormal lamp bead belonging to the LED headlight; it should be explained that the above-mentioned updating of the reference light intensity of the LED headlight during the demand cycle specifically refers to accumulating the reference light intensity of the LED headlight during the demand cycle, the first compensation value of the reference light intensity and the second compensation value of the reference light intensity, and the accumulation result is the updated reference light intensity of the LED headlight during the demand cycle.

[0037] The total number of the first type of abnormal lamp beads and the total number of the second type of abnormal lamp beads are accumulated, and the accumulated result is marked as the total number of adjustable abnormal lamp beads; the first compensation value of the reference light intensity is updated according to the total number of adjustable abnormal lamp beads and the total number of the third type of abnormal lamp beads; the second compensation value of the reference light intensity is updated according to the total number of adjustable abnormal lamp beads and the total number of the fourth type of abnormal lamp beads; the following is a specific example of how to update the reference light intensity compensation value according to the total number of each type of abnormal lamp beads: first calculate the total number of adjustable abnormal lamp beads, that is, add the total number of the first type of abnormal lamp beads and the total number of the second type of abnormal lamp beads, and then update the first compensation value of the reference light intensity according to the total number of adjustable abnormal lamp beads and the total number of the third type of abnormal lamp beads, and set a new first compensation value of the reference light intensity, as follows: ; in, , ; Similarly, the second compensation value of the reference light intensity is updated according to the total number of adjustable abnormal lamp beads and the total number of the fourth type of abnormal lamp beads, as follows: ; in, , ; Among them, the total number of the third type of abnormal lamp beads detected in the historical adjacent detection period represents the total number of the third type of abnormal lamp beads detected in the historical adjacent detection period, the total number of adjustable abnormal lamp beads detected in the historical adjacent detection period and the total number of the fourth type of abnormal lamp beads detected in the historical adjacent detection period have the same meaning.

[0038] Reinitializing the first compensation value of reference light intensity and the second compensation value of reference light intensity specifically refers to updating these two compensation values ​​based on the latest first compensation value of reference light intensity and the second compensation value of reference light intensity. In the subsequent use process, more accurate analysis and judgment can be performed based on these updated compensation values.

[0039] According to the reference light intensity of the LED headlight during the demand cycle, the first compensation value of the reference light intensity and the second compensation value of the reference light intensity, the reference light intensity of the LED headlight during the demand cycle is updated, and the first type of abnormal lamp beads and the second type of abnormal lamp beads are secondary adjusted according to the reference light intensity of the LED headlight during the demand cycle and the adjustment rate of each abnormal lamp bead belonging to the LED headlight; in an example embodiment, assuming that the reference light intensity of the LED headlight during the demand cycle is I_ref, and the adjustment rate of each abnormal lamp bead belonging to the LED headlight is TY, the specific adjustment process is: reducing the light intensity of the first type of abnormal lamp beads to I_ref at a speed of TY, and increasing the light intensity of the second type of abnormal lamp beads to I_ref at a speed of TY.

[0040] It should be explained that, in the actual adjustment process, current control technology (such as switch constant current control technology) is used to adjust the current of the circuit to which each lamp bead belongs until it reaches the reference current value matched with the reference light intensity.

[0041] In a specific embodiment, the present invention not only simplifies the process of light intensity adjustment and improves the adjustment efficiency by initializing a first compensation value of reference light intensity and a second compensation value of reference light intensity, but also enables the LED headlights to perform more precise fine-tuning based on the existing compensation values ​​the next time the light intensity is adjusted, which is conducive to faster adaptation to changes in different lighting environments, ensuring the stability and accuracy of light intensity, and thus improving the overall user experience and effect.

[0042] Specifically, the circuit abnormality index of each lamp bead belonging to the LED car light within the detection cycle, the specific analysis process is: according to the reference light intensity of the LED car light within the demand cycle, the reference current of the lamp bead belonging to the LED car light within the demand cycle, the reference power dissipation value of the lamp bead belonging to the LED car light within the demand cycle and the reference color temperature of the lamp bead belonging to the LED car light within the demand cycle are matched from the monitoring database, and the specific matching process is: the reference current, reference power dissipation value and reference color temperature corresponding to each reference light intensity interval are stored in the monitoring database, and the reference light intensity interval stored in the monitoring database to which the reference light intensity of the LED car light within the demand cycle belongs is queried. The reference current, reference power dissipation value and reference color temperature corresponding to the reference light intensity interval are the reference current of the lamp bead belonging to the LED car light within the demand cycle, the reference power dissipation value of the lamp bead belonging to the LED car light within the demand cycle and the reference color temperature of the lamp bead belonging to the LED car light within the demand cycle matched in this embodiment.

[0043] The average working current of each lamp bead belonging to the LED car light during the detection period, the average power dissipation value of each lamp bead belonging to the LED car light during the detection period, and the average color temperature of each lamp bead belonging to the LED car light during the detection period are obtained and comprehensively analyzed to obtain the circuit abnormality index of each lamp bead belonging to the LED car light during the detection period. The circuit abnormality index represents quantitative data of the influence of the average working current, the average power dissipation value and the average color temperature on the circuit abnormality, and is used to quantify the degree of circuit abnormality; the average working current of each lamp bead belonging to the LED car light during the detection period represents the average working current of each lamp bead belonging to the LED car light during the detection period, which can be obtained by monitoring the current sensor installed on the power supply line of the LED car light; the average power dissipation value of each lamp bead belonging to the LED car light during the detection period represents the average power consumed by each lamp bead of the LED car light when working during the detection period, which can be obtained by measuring the LED car light The real-time voltage and real-time current during the working process, and the instantaneous power P is calculated using the power formula (P=UI), U is the real-time voltage, I is the real-time current, and then the instantaneous power is averaged to obtain, wherein the real-time voltage can be measured by a voltage sensor, and the real-time current can be measured by a current sensor; the average color temperature of each lamp bead belonging to the above-mentioned LED headlight within the detection period, represents the average value of the color temperature of the light emitted by each lamp bead of the LED headlight within the detection period, and the specific acquisition method is: according to the average power dissipation value of each lamp bead within the detection period, the average color temperature of each lamp bead within the detection period is matched, and the specific matching process is: the average color temperature corresponding to each average power dissipation value interval is stored in the monitoring database, and the average power dissipation value interval stored in the monitoring database to which the average power dissipation value of each lamp bead within the detection period belongs is queried, and the average color temperature corresponding to the average power dissipation value interval is the average color temperature of the corresponding lamp bead within the detection period.

[0044] The circuit abnormality index is specifically obtained by accumulating the average working current component, the average power dissipation value component and the average color temperature component, wherein the average working current component is used to quantify the influence of the average working current change on the circuit abnormality index, the average power dissipation value component is used to quantify the influence of the average power dissipation value change on the circuit abnormality index, and the average color temperature component is used to quantify the influence of the average color temperature change on the circuit abnormality index. The average working current component refers to the index analysis of the average working current, the reference current and the circuit abnormality factor corresponding to the average working current; the average power dissipation value component refers to the index analysis of the average power dissipation value, the reference power dissipation value and the circuit abnormality factor corresponding to the average power dissipation value; the average color temperature component refers to the index analysis of the average color temperature, the reference color temperature and the circuit abnormality factor corresponding to the average color temperature; the circuit abnormality index of each lamp bead belonging to the LED headlight within the detection period is specifically expressed as follows: ; In the formula, is the circuit abnormality index of the sth lamp bead of the LED car light during the detection cycle, s is the number of each lamp bead, , d is the total number of lamp beads, is the average working current of the sth lamp bead of the LED lamp during the detection cycle, It is the reference current of the LED lamp bead in the demand cycle. is the average power dissipation value of the sth lamp bead of the LED lamp during the detection cycle, It is the reference power dissipation value of the LED lamp beads in the demand cycle. is the average color temperature of the sth lamp bead of the LED lamp during the detection period, It is the reference color temperature of the LED lamp beads in the demand cycle. To monitor the circuit abnormality factor corresponding to the average working current preset in the database, To monitor the circuit abnormality factor corresponding to the average power dissipation value preset in the database, It is the circuit abnormality factor corresponding to the average color temperature preset in the monitoring database.

[0045] The reference current of the lamp beads belonging to the above-mentioned LED car lights during the demand cycle represents the reference value of the average operating current of the sth lamp beads belonging to the LED car lights during the detection cycle; the reference power dissipation value of the lamp beads belonging to the above-mentioned LED car lights during the demand cycle represents the reference value of the average power dissipation value of the sth lamp beads belonging to the LED car lights during the detection cycle; the reference color temperature of the lamp beads belonging to the above-mentioned LED car lights during the demand cycle represents the reference value of the average color temperature of the sth lamp beads belonging to the LED car lights during the detection cycle.

[0046] The circuit abnormality factor corresponding to the above-mentioned average working current is used to quantify the influence of the unit value of the average working current on the circuit abnormality index; the circuit abnormality factor corresponding to the above-mentioned average power dissipation value is used to quantify the influence of the unit value of the average power dissipation value on the circuit abnormality index; the circuit abnormality factor corresponding to the above-mentioned average color temperature is used to quantify the influence of the unit value of the average color temperature on the circuit abnormality index. The monitoring database stores the correspondence between the average working current, the average power dissipation value and the average color temperature and their corresponding circuit abnormality factors. For example, the average working current, the average power dissipation value and the average color temperature are input into the monitoring database, and the monitoring database can match the circuit abnormality factor corresponding to the average working current, the circuit abnormality factor corresponding to the average power dissipation value and the circuit abnormality factor corresponding to the average color temperature, and the value range is between 0 and 1.

[0047] It needs to be explained that when the illumination intensity of the lamp bead exceeds the reference value, its electrical characteristics will also change accordingly. The average current and average power dissipation values ​​will both increase, exceeding their reference values. At the same time, the average color temperature will also increase. This series of changes can be quantitatively evaluated by exponentially analyzing the average current, average power dissipation value and average color temperature. If the abnormality index of the circuit breaks through the first circuit abnormality threshold interval at this time, it means that the circuit state has deviated from the normal range and is higher than the reference average current and other requirements. On the contrary, when the illumination intensity of the lamp bead is slightly lower than the reference value but still within the adjustable range, its average current, average power dissipation value and average color temperature will also decrease slightly accordingly, but will still remain within a certain range. At this time, although the abnormality index of the circuit is less than the first circuit abnormality threshold interval, it is still higher than the second circuit abnormality threshold interval, indicating that although the circuit state is slightly lower than the reference average current and other requirements, it is still within the adjustable range. Further, If the lamp bead is short-circuited, its luminous ability will be sharply weakened and only a faint light will be emitted. At this time, the average current, average power dissipation value and average color temperature will all drop significantly, far below their reference values, and the circuit abnormality index will also decrease accordingly, and may even touch or fall below the second circuit abnormality threshold interval, but still be higher than the third circuit abnormality threshold interval, which indicates that the circuit has obvious abnormalities. The most serious thing is that when the lamp bead is short-circuited, it will completely lose its luminous ability. At this time, the average current, average power dissipation value and average color temperature will all approach zero, far below their reference values, and the circuit abnormality index will also drop below the third circuit abnormality threshold interval, clearly indicating that the circuit is in a serious abnormal state. In summary, by monitoring the average current, average power dissipation value and average color temperature of the lamp bead and combining it with the analysis of the circuit abnormality index, the circuit status can be effectively evaluated, and potential circuit faults can be discovered and handled in a timely manner.

[0048] It should also be explained that in the performance evaluation of LED headlights, the stability of the average operating current directly affects the energy efficiency and luminous quality of the lamp beads. When the average operating current deviates from the reference current, it may cause the average power dissipation value to deviate from the corresponding reference value. At the same time, the current deviation may also cause color temperature fluctuations, causing the average color temperature to deviate from the reference color temperature, thereby affecting the luminous quality of the headlights.

[0049] Furthermore, the illumination compliance coefficient of the LED headlights during the detection period is specifically analyzed as follows: the operating illumination data of the LED headlights during the detection period includes the uniformity of illumination intensity of the illumination area to which the LED headlights belong during the detection period, the brightness fluctuation value of the illumination area to which the LED headlights belong during the detection period, and the electrical signal frequency fluctuation value of the LED headlights during the detection period; the above-mentioned illumination intensity uniformity is used to quantify the uniformity of illumination intensity of the illumination area to which the LED headlights belong during the detection period, specifically referring to the ratio of the maximum illumination intensity to the minimum illumination intensity of the illumination area to which the LED headlights belong during the detection period, and the real-time illumination intensity of multiple positions in the illumination area can be collected by the on-board light sensor, and all illumination intensity data are sorted in order from small to large, so as to extract the ratio of the illumination intensity ranked last to the illumination intensity ranked first, wherein the illumination area refers to a specific area that can be directly illuminated and covered by the LED headlights, and the area is defined by the light emitted by the LED headlights; the above-mentioned brightness fluctuation value is used to characterize the uniformity of illumination intensity of the LED headlights to which the illumination area belongs during the detection period. The degree of fluctuation of brightness change in the area can be measured by using a vehicle-mounted camera or a light sensor array to capture a real-time illumination distribution image of the illumination area, and using image processing software (such as Matrix Lab) to obtain the brightness variance in the real-time illumination distribution image, and the brightness variance of all real-time illumination distribution images within the detection period is averaged to obtain a brightness fluctuation value. The smaller the brightness fluctuation value, the more stable and uniform the illumination. The above-mentioned electrical signal frequency fluctuation value refers to the degree of fluctuation of the frequency of the electrical signal (such as current or voltage) of the LED headlight during operation. It is one of the important indicators for measuring the power supply stability and control accuracy of the LED headlight. The power supply signal of the LED headlight can be monitored by the vehicle-mounted diagnostic system, and the frequency value of the electrical signal within the detection period is recorded. The standard deviation of these frequency values ​​is calculated, which is the electrical signal frequency fluctuation value of the LED headlight within the detection period. The vehicle-mounted diagnostic system is mainly used to monitor the operating status of the vehicle in real time, including the working conditions of the engine, emission system, fuel system, etc. At the same time, the sensors and controllers in the vehicle-mounted diagnostic system can monitor the power supply signal of the vehicle, including the power supply signal of the LED headlight.

[0050] A comprehensive analysis is performed on the circuit abnormality index of each lamp bead belonging to the LED headlight during the detection period, the light intensity uniformity of the light area belonging to the LED headlight during the detection period, the brightness fluctuation value of the light area belonging to the LED headlight during the detection period, and the electrical signal frequency fluctuation value of the LED headlight during the detection period, to obtain the lighting compliance coefficient of the LED headlight during the detection period. The lighting compliance coefficient of the LED headlight during the detection period represents quantitative data on the influence of the circuit abnormality index, light intensity uniformity, brightness fluctuation value, and electrical signal frequency fluctuation value on the lighting compliance of the LED headlight during the detection period, and is used to quantify the degree of compliance of the lighting performance of the LED headlight during the detection period with the preset specified lighting performance.

[0051] The illumination compliance coefficient of the LED headlight during the detection period is specifically expressed as: ; In the formula, is the illumination compliance coefficient of the LED headlight during the test period, It is the uniformity of light intensity in the illumination area of ​​the LED headlight during the detection period. It is the preset light intensity uniformity limit value in the monitoring database. is the brightness fluctuation value of the illumination area of ​​the LED headlight within the detection period, To monitor the brightness fluctuation value preset in the database, is the frequency fluctuation value of the electrical signal of the LED lamp during the detection period, To monitor the frequency fluctuation value of the defined electrical signal preset in the database, To monitor the illumination compliance factor corresponding to the illumination uniformity preset in the database, To monitor the lighting compliance factor corresponding to the brightness fluctuation value preset in the database, To monitor the illumination compliance factor corresponding to the electrical signal frequency fluctuation value preset in the database, is the circuit abnormality index of the sth lamp bead of the LED lamp during the detection cycle, is the weight value corresponding to the circuit abnormality index preset in the monitoring database, s is the number of each lamp bead, , d is the total number of lamp beads.

[0052] The above-mentioned light intensity uniformity definition value indicates the minimum allowable value of light intensity uniformity; the above-mentioned brightness fluctuation value defines the maximum allowable value of brightness fluctuation value; the above-mentioned electrical signal frequency fluctuation value defines the maximum allowable value of electrical signal frequency fluctuation value.

[0053] The illumination compliance factor corresponding to the above-mentioned illumination intensity uniformity is used to quantify the influence of the unit value of illumination intensity uniformity on the illumination compliance coefficient; the illumination compliance factor corresponding to the above-mentioned brightness fluctuation value is used to quantify the influence of the unit value of brightness fluctuation value on the illumination compliance coefficient; the illumination compliance factor corresponding to the above-mentioned electrical signal frequency fluctuation value is used to quantify the influence of the unit value of electrical signal frequency fluctuation value on the illumination compliance coefficient; the weight value corresponding to the above-mentioned circuit abnormality index is used to de-unitize the circuit abnormality index and to quantify the influence of the unit value of the circuit abnormality index on the illumination compliance coefficient. The monitoring database stores the correspondence between illumination intensity uniformity, brightness fluctuation value and electrical signal frequency fluctuation value and their corresponding illumination compliance factors, and also stores the correspondence between the circuit abnormality index and its corresponding weight value. For example, the illumination intensity uniformity, brightness fluctuation value, electrical signal frequency fluctuation value and circuit abnormality index are input into the monitoring database, and the monitoring database can match the illumination compliance factor corresponding to the illumination intensity uniformity, the illumination compliance factor corresponding to the brightness fluctuation value, the illumination compliance factor corresponding to the electrical signal frequency fluctuation value and the weight value corresponding to the circuit abnormality index, and the value range is between 0 and 1.

[0054] It needs to be explained that in the performance evaluation of LED headlights, the circuit abnormality index of the sth lamp bead within the detection cycle is a key indicator to measure the health of its circuit. It directly affects the uniformity of the light intensity of the lighting area to which the LED headlight belongs. When the circuit abnormality index increases, it means that there may be problems such as poor circuit connection, component aging or unstable driving circuit. These problems will cause the uniformity of light intensity to decrease. At the same time, the brightness fluctuation value of the lighting area within the detection cycle will also be affected. Circuit abnormality may cause brightness instability, making the brightness fluctuation value much larger than the corresponding defined value. In addition, the electrical signal frequency fluctuation value of the LED headlight within the detection cycle is also affected by the circuit state. An abnormal circuit may cause the instability of the electrical signal frequency, thereby causing the electrical signal frequency fluctuation value to be much larger than the preset defined electrical signal frequency fluctuation value. The circuit abnormality index, light intensity uniformity, brightness fluctuation value and electrical signal frequency fluctuation value are interrelated and jointly reflect the health status and lighting performance of the LED headlight circuit. When any one or more of these parameters are abnormal, the lighting compliance coefficient of the LED headlight within the detection cycle will be reduced, which means that the lighting performance of the headlight fails to meet the predetermined compliance standard and needs to be adjusted accordingly.

[0055] The operation feedback module is used to monitor the operating status parameters of the LED headlight after adjustment, evaluate the adjustment adaptability index of the LED headlight, and determine whether to perform performance adjustment and feedback.

[0056] Specifically, the determination of whether to perform performance adjustment and feedback is carried out, and the specific determination process is: extracting an adjustment adaptation threshold from a monitoring database; comparing the adjustment adaptation index of the LED headlight within the adjustment period with the adjustment adaptation threshold; if the adjustment adaptation index of the LED headlight within the adjustment period is greater than or equal to the adjustment adaptation threshold, determining not to perform performance adjustment and feedback; if the adjustment adaptation index of the LED headlight within the adjustment period is less than the adjustment adaptation threshold, determining to perform performance adjustment and feedback; the above-mentioned adjustment adaptation threshold represents the minimum value of a reasonable range of the adjustment adaptation index.

[0057] Specifically, the performance adjustment and feedback are performed, and the specific adjustment feedback process is: performing difference processing on the adjustment adaptation threshold and the adjustment adaptation index of the LED headlight during the adjustment period, performing ratio processing on the processing result and the adjustment adaptation threshold, and finally obtaining the adjustment adaptation deviation rate of the LED headlight, which is used to quantify the degree of deviation of the adjustment adaptation index of the LED headlight during the adjustment period relative to the adjustment adaptation threshold.

[0058] The reference light intensity of the LED headlights during the demand cycle is adjusted according to the adjustment adaptation deviation rate of the LED headlights, and an adjustment report is generated for feedback. The specific adjustment process is: assuming that the reference light intensity of the LED headlights during the demand cycle is I_ref, and the adjustment adaptation deviation rate of the LED headlights is io, the reference light intensity of the LED headlights during the demand cycle is adjusted to I_ref* (1-io), and the first type of abnormal lamp beads and the second type of abnormal lamp beads are readjusted according to I_ref* (1-io), and an adjustment report is generated at the same time, and the vehicle ownership personnel are notified by a pop-up window or text message. The adjustment report includes the adjustment adaptation deviation rate of the LED headlights and the comparison of the light intensity before and after the adjustment (i.e., I_ref and I_ref* (1-io)).

[0059] It needs to be explained that the first adjustment, the second adjustment and the readjustment are all to adjust the light intensity of the first type of abnormal lamp beads and the second type of abnormal lamp beads to the reference light intensity level.

[0060] Furthermore, the adjustment adaptation index of the LED headlight is evaluated, and the specific evaluation process is as follows: the operating status parameters of the LED headlight after adjustment include the illumination compliance coefficient of the LED headlight during the adjustment period, the circuit abnormality index of each lamp bead of the LED headlight during the adjustment period, the thermal resistance change curve of the LED headlight during the adjustment period, and the flashing frequency of the LED headlight during the adjustment period; the above-mentioned adjustment period is a period between the detection period and the demand period. During the adjustment period, the main purpose is to examine whether the LED headlight can meet the performance requirements of the upcoming demand period after adjustment. The specific duration of the adjustment period is determined by the data analysis administrator. The establishment of this period ensures that the LED headlight can make necessary adjustments and optimizations in a timely manner during continuous operation to meet the standards set by the ever-changing demand period; the illumination compliance coefficient of the LED headlight during the adjustment period is consistent with the illumination compliance coefficient of the LED headlight during the detection period in terms of meaning and acquisition method. The difference is that the illumination compliance coefficient of the LED headlight during the adjustment period involves and parameters are collected during the adjustment period; the circuit anomaly index of each lamp bead belonging to the above-mentioned LED headlight during the adjustment period is consistent with the circuit anomaly index of each lamp bead belonging to the LED headlight during the detection period in terms of expression and acquisition method, the difference is that the parameters involved in the circuit anomaly index of each lamp bead belonging to the LED headlight during the adjustment period are collected during the adjustment period; the thermal resistance change curve of the above-mentioned LED headlight during the adjustment period is a graphical representation of the change of the thermal resistance value of the LED headlight over time during a specific time period (i.e., the adjustment period), which can be measured by the thermal resistance test system built into the car; the flickering frequency of the above-mentioned LED headlight during the adjustment period refers to the ratio of the number of times the LED headlight flickers during a specific time period (i.e., the adjustment period) to the duration corresponding to the adjustment period, and the light signal when the LED headlight flickers can be captured by a photoelectric sensor and converted into an electrical signal for recording, the electrical signal output by the photoelectric sensor is amplified, filtered, etc. to extract a valid flickering signal, and the flickering signal is counted by a counter or timer to obtain the number of flickers during the adjustment period.

[0061] The thermal resistance change curve of the LED headlight during the adjustment period is compared with the defined thermal resistance change curve to obtain the thermal resistance abnormality rate of the LED headlight during the adjustment period; the defined thermal resistance change curve is a preset thermal resistance change threshold curve used to define the reasonable range of thermal resistance change of the LED headlight under normal working conditions. It represents the maximum acceptable range of thermal resistance value change over time under expected working conditions of the LED headlight. When the actual thermal resistance change of the LED headlight exceeds this definition, it may mean that there are problems such as poor heat dissipation, design defects or aging; the thermal resistance abnormality rate is an indicator for quantitatively evaluating the degree of abnormality of thermal resistance change of the LED headlight. It is calculated by ratioing the part of the thermal resistance change curve that exceeds the defined thermal resistance change curve (i.e., the abnormal part) with the entire thermal resistance change curve. Specifically, the thermal resistance abnormality rate is equal to the ratio of the area (or length) of the abnormal part to the area (or length) of the entire thermal resistance change curve. The higher this ratio is, the more serious the abnormality of the thermal resistance change of the LED headlight is.

[0062] The light compliance coefficient of the LED headlight during the adjustment period is differenced with the light compliance coefficient of the LED headlight during the detection period, and the difference processing result is ratioed with the light compliance coefficient of the LED headlight during the detection period, finally obtaining the light compliance improvement ratio of the LED headlight during the adjustment period, which is used to quantify the improvement effect of the light compliance degree of the LED headlight during the adjustment period.

[0063] Comprehensively evaluate the thermal resistance abnormality rate of the LED headlight during the adjustment period, the flickering frequency of the LED headlight during the adjustment period, the illumination compliance improvement ratio of the LED headlight during the adjustment period, and the circuit abnormality index of each lamp bead of the LED headlight during the adjustment period, and obtain the adjustment adaptation index of the LED headlight during the adjustment period. The adjustment adaptation index of the LED headlight during the adjustment period represents quantitative data of the influence of the thermal resistance abnormality rate, the flickering frequency, the illumination compliance improvement ratio, and the circuit abnormality index on the adjustment adaptation degree of the LED headlight during the adjustment period, and is used to quantify the adjustment adaptation degree of the LED headlight during the adjustment period. The adjustment adaptation index of the LED headlight during the adjustment period is specifically expressed as: ; In the formula, It is the adjustment adaptation index of LED headlights during the adjustment cycle. is the abnormal rate of thermal resistance of LED lights during the adjustment period, is the flashing frequency of the LED lights in the adjustment cycle, Improve the lighting compliance ratio of LED headlights within the adjustment cycle. is the circuit abnormality index of the sth lamp bead of the LED lamp during the adjustment cycle, To monitor the thermal resistance abnormality rate preset in the database, To monitor the defined flicker frequencies preset in the database, It is the adjustment adaptation factor corresponding to the thermal resistance abnormality rate preset in the monitoring database. To monitor the adjustment adaptation factor corresponding to the flicker frequency preset in the database, It is the adjustment adaptation factor corresponding to the preset lighting compliance improvement ratio in the monitoring database. is the adjustment adaptation factor corresponding to the circuit abnormality index preset in the monitoring database, s is the number of each lamp bead, , d is the total number of lamp beads.

[0064] The above definition of thermal resistance abnormality rate indicates the maximum allowable value of the thermal resistance abnormality rate; the above definition of flicker frequency indicates the maximum allowable value of the flicker frequency.

[0065] The adjustment adaptation factor corresponding to the above-mentioned thermal resistance abnormality rate is used to quantify the influence of the unit value of the thermal resistance abnormality rate on the adjustment adaptation index; the adjustment adaptation factor corresponding to the above-mentioned flicker frequency is used to quantify the influence of the unit value of the flicker frequency on the adjustment adaptation index; the adjustment adaptation factor corresponding to the above-mentioned illumination compliance improvement ratio is used to de-unitize the illumination compliance improvement ratio, and at the same time to quantify the influence of the unit value of the illumination compliance improvement ratio on the adjustment adaptation index; the adjustment adaptation factor corresponding to the above-mentioned circuit abnormality index is used to de-unitize the circuit abnormality index, and at the same time to quantify the influence of the unit value of the circuit abnormality index on the adjustment adaptation index. The monitoring database stores the correspondence between the thermal resistance abnormality rate, flicker frequency, illumination compliance improvement ratio and circuit abnormality index and their corresponding adjustment adaptation factors. For example, the thermal resistance abnormality rate, flicker frequency, illumination compliance improvement ratio and circuit abnormality index are input into the monitoring database, and the monitoring database can match the adjustment adaptation factor corresponding to the thermal resistance abnormality rate, the adjustment adaptation factor corresponding to the flicker frequency, the adjustment adaptation factor corresponding to the illumination compliance improvement ratio and the adjustment adaptation factor corresponding to the circuit abnormality index, and the value range is between 0 and 1.

[0066] What needs to be explained is that when the LED headlights fail to fully adapt to the adjustment requirements after adjustment, they will show a series of changes in operating status parameters. Specifically, the LED headlights may flicker, resulting in a significant increase in the flickering frequency during the adjustment period, indicating that there may be unstable factors in the LED headlight circuit or the car power supply. At the same time, since the adjustment fails to effectively improve the lighting performance of the headlights, the lighting compliance improvement ratio will be at a low level, which means that the headlights have not yet met the expected standards in terms of light intensity, uniformity and stability. At the same time, the circuit abnormality index of the lamp beads is still at a high level, indicating that the health of the lamp bead circuit is not good and there may be In the case of component aging, poor connection or drive circuit failure, these problems will further lead to an increase in the thermal resistance abnormality rate of the headlights, which means that the heat dissipation performance of the headlights is affected, which may cause the temperature of the headlights to rise, accelerate their aging and performance degradation. In summary, when the flashing frequency of the LED headlights during the adjustment cycle is at a high level, the lighting compliance improvement ratio is at a low level, the circuit abnormality index is high, and the thermal resistance abnormality rate is at a high level, these parameters interact with each other, and together manifest as a low adjustment adaptability of the LED headlights, indicating that the adjustment has failed to achieve the expected effect and needs to be readjusted to improve the performance and adaptability of the headlights.

[0067] In a specific embodiment, the present invention provides an LED car light operation monitoring system based on data analysis, which can accurately obtain the lighting parameters of the environment in which the LED car light is located, and then scientifically analyze and determine the reference light intensity of the LED car light. On this basis, the circuit information of the LED car light is comprehensively monitored and carefully collected. Through data analysis technology, the abnormal lamp beads in the LED car light are accurately located, and the abnormal lamp beads are targetedly adjusted according to the predetermined reference light intensity. After the adjustment is completed, the operating status parameters of the LED car light are further monitored, and the adjustment adaptation index of the LED car light is evaluated accordingly, so as to intelligently determine whether further performance adjustment is needed, and timely feedback the adjustment effect, thereby greatly enhancing the efficiency, stability, ability to adapt to changing environments and performance matching of the LED car light in operation, thereby ensuring that the adjustments made can fully meet the established performance indicators.

[0068] Reference Figure 2 As shown, the second aspect of the present invention provides an LED car light operation monitoring method based on data analysis, including: step one, obtaining the lighting parameters of the environment to which the LED car light belongs, and analyzing the reference light intensity of the LED car light; step two, monitoring and collecting the circuit information of the LED car light, locating the abnormal lamp beads belonging to the LED car light through data analysis, and adjusting the abnormal lamp beads belonging to the LED car light according to the reference light intensity of the LED car light; step three, monitoring the operating status parameters of the LED car light after adjustment, evaluating the adjustment adaptation index of the LED car light, and determining whether to perform performance adjustment and feedback.

[0069] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. The LED headlight operation monitoring system based on data analysis is characterized by: include: A reference analysis module is used to obtain the illumination parameters of the environment in which the LED headlights are located and analyze the reference illumination intensity of the LED headlights; The abnormal adjustment module is used to monitor and collect circuit information of LED lights, locate abnormal lamp beads of LED lights through data analysis, and adjust the abnormal lamp beads of LED lights according to the reference light intensity of LED lights; The operation feedback module is used to monitor the operating status parameters of the LED headlights after adjustment, evaluate the adjustment adaptability index of the LED headlights, and determine whether to perform performance adjustment and feedback.

2. The LED vehicle light operation monitoring system based on data analysis according to claim 1 is characterized in that: The reference light intensity of the LED headlight is analyzed, and the specific analysis process is as follows: The illumination parameters of the environment to which the LED headlight belongs include an illumination intensity curve of the environment to which the LED headlight belongs within a detection period, and according to the illumination intensity curve of the environment to which the LED headlight belongs within the detection period, predicting the average illumination intensity of the environment to which the LED headlight belongs within a demand period; The reference light intensity of the LED headlight during the demand period is matched according to the average light intensity of the environment to which the LED headlight belongs during the demand period.

3. The LED vehicle light operation monitoring system based on data analysis according to claim 1 is characterized in that: The abnormal lamp beads belonging to the LED lights are located through data analysis. The specific location process is as follows: The circuit information of the LED headlight specifically refers to the circuit abnormality index of each lamp bead belonging to the LED headlight within the detection cycle. If the circuit abnormality index of a certain lamp bead belonging to the LED headlight within the detection cycle is greater than the maximum value of the first circuit abnormality threshold interval, the lamp bead belonging to the LED headlight is marked as a first-class abnormal lamp bead; If the circuit abnormality index of a certain lamp bead belonging to the LED car light during the detection cycle belongs to the first circuit abnormality threshold interval, the lamp bead belonging to the LED car light is marked as a normal lamp bead; If the circuit abnormality index of a certain lamp bead belonging to the LED headlight within the detection period is less than the minimum value of the first circuit abnormality threshold interval and greater than the maximum value of the second circuit abnormality threshold interval, the lamp bead belonging to the LED headlight is marked as a second type of abnormal lamp bead; If the circuit abnormality index of a certain lamp bead belonging to the LED headlight within the detection cycle is less than the minimum value of the second circuit abnormality threshold interval or belongs to the second circuit abnormality threshold interval, and at the same time, the circuit abnormality index of a certain lamp bead belonging to the LED headlight within the detection cycle is greater than the maximum value of the third circuit abnormality threshold interval, then the lamp bead belonging to the LED headlight is marked as a third type abnormal lamp bead; If the circuit abnormality index of a certain lamp bead belonging to the LED car light within the detection period is less than the minimum value of the third circuit abnormality threshold interval or belongs to the third circuit abnormality threshold interval, the lamp bead belonging to the LED car light is marked as a fourth type of abnormal lamp bead.

4. The LED vehicle light operation monitoring system based on data analysis according to claim 3 is characterized in that: The circuit abnormality index of each lamp bead of the LED lamp within the detection cycle, the specific analysis process is as follows: According to the reference light intensity of the LED headlights in the demand cycle, the reference current of the LED headlights in the demand cycle, the reference power dissipation value of the LED headlights in the demand cycle, and the reference color temperature of the LED headlights in the demand cycle are matched from the monitoring database; The average working current of each lamp bead belonging to the LED car light during the detection period, the average power dissipation value of each lamp bead belonging to the LED car light during the detection period, and the average color temperature of each lamp bead belonging to the LED car light during the detection period are obtained and comprehensively analyzed to obtain the circuit abnormality index of each lamp bead belonging to the LED car light during the detection period. The circuit abnormality index represents quantitative data of the influence of the average working current, the average power dissipation value and the average color temperature on the circuit abnormality, and is used to quantify the degree of circuit abnormality.

5. The LED vehicle light operation monitoring system based on data analysis according to claim 1 is characterized in that: The specific adjustment process of adjusting the abnormal lamp beads of the LED lamp is as follows: Obtain the operating illumination data of the LED headlights during the detection period, and analyze the illumination compliance coefficient of the LED headlights during the detection period by integrating the circuit abnormality index of each lamp bead belonging to the LED headlights during the detection period, and match the adjustment rate of each abnormal lamp bead belonging to the LED headlights; Count the total number of abnormal lamp beads of the first category, the total number of abnormal lamp beads of the second category, the total number of abnormal lamp beads of the third category, the total number of abnormal lamp beads of the fourth category, and the total number of lamp beads belonging to LED lights; Obtaining a first compensation value of reference light intensity and a second compensation value of reference light intensity; According to the reference light intensity of the LED headlight in the demand cycle, the first compensation value of the reference light intensity and the second compensation value of the reference light intensity, the reference light intensity of the LED headlight in the demand cycle is updated, and the first type of abnormal lamp beads and the second type of abnormal lamp beads are adjusted once according to the reference light intensity of the LED headlight in the demand cycle and the adjustment rate of each abnormal lamp bead belonging to the LED headlight; The total number of the first type of abnormal lamp beads and the total number of the second type of abnormal lamp beads are accumulated, and the accumulated result is marked as the total number of adjustable abnormal lamp beads; Update the first compensation value of the reference light intensity according to the total number of adjustable abnormal lamp beads and the total number of the third type of abnormal lamp beads; Update the second compensation value of the reference light intensity according to the total number of adjustable abnormal lamp beads and the total number of fourth-category abnormal lamp beads; Reinitialize the first compensation value of the reference light intensity and the second compensation value of the reference light intensity; According to the reference light intensity of the LED headlight during the demand cycle, the first compensation value of the reference light intensity and the second compensation value of the reference light intensity, the reference light intensity of the LED headlight during the demand cycle is updated, and the first type of abnormal lamp beads and the second type of abnormal lamp beads are secondarily adjusted according to the reference light intensity of the LED headlight during the demand cycle and the adjustment rate of each abnormal lamp bead belonging to the LED headlight.

6. The LED vehicle light operation monitoring system based on data analysis according to claim 5 is characterized in that: The specific analysis process of the illumination compliance coefficient of the LED headlights during the detection period is as follows: The operating illumination data of the LED headlights during the detection period includes the uniformity of illumination intensity of the illumination area to which the LED headlights belong during the detection period, the brightness fluctuation value of the illumination area to which the LED headlights belong during the detection period, and the electrical signal frequency fluctuation value of the LED headlights during the detection period; A comprehensive analysis is performed on the circuit abnormality index of each lamp bead belonging to the LED headlight during the detection period, the light intensity uniformity of the light area belonging to the LED headlight during the detection period, the brightness fluctuation value of the light area belonging to the LED headlight during the detection period, and the electrical signal frequency fluctuation value of the LED headlight during the detection period, to obtain the lighting compliance coefficient of the LED headlight during the detection period. The lighting compliance coefficient of the LED headlight during the detection period represents quantitative data on the influence of the circuit abnormality index, light intensity uniformity, brightness fluctuation value, and electrical signal frequency fluctuation value on the lighting compliance of the LED headlight during the detection period, and is used to quantify the degree of compliance of the lighting performance of the LED headlight during the detection period with the preset specified lighting performance.

7. The LED vehicle light operation monitoring system based on data analysis according to claim 1 is characterized in that: The adjustment adaptation index of the LED headlight is evaluated, and the specific evaluation process is as follows: The operating state parameters of the LED headlight after adjustment include the illumination compliance coefficient of the LED headlight during the adjustment period, the circuit abnormality index of each lamp bead of the LED headlight during the adjustment period, the thermal resistance change curve of the LED headlight during the adjustment period, and the flashing frequency of the LED headlight during the adjustment period; Compare the thermal resistance change curve of the LED headlight during the adjustment period with the defined thermal resistance change curve to obtain the thermal resistance abnormality rate of the LED headlight during the adjustment period; Perform difference processing on the illumination compliance coefficient of the LED headlights in the adjustment period and the illumination compliance coefficient of the LED headlights in the detection period, perform ratio processing on the difference processing result and the illumination compliance coefficient of the LED headlights in the detection period, and finally obtain the illumination compliance improvement ratio of the LED headlights in the adjustment period; The thermal resistance abnormality rate of the LED headlight during the adjustment period, the flickering frequency of the LED headlight during the adjustment period, the illumination compliance improvement ratio of the LED headlight during the adjustment period, and the circuit abnormality index of each lamp bead belonging to the LED headlight during the adjustment period are comprehensively evaluated to obtain the adjustment adaptation index of the LED headlight during the adjustment period. The adjustment adaptation index of the LED headlight during the adjustment period represents quantitative data of the influence of the thermal resistance abnormality rate, the flickering frequency, the illumination compliance improvement ratio, and the circuit abnormality index on the adjustment adaptation degree of the LED headlight during the adjustment period, and is used to quantify the adjustment adaptation degree of the LED headlight during the adjustment period.

8. The LED vehicle light operation monitoring system based on data analysis according to claim 1 is characterized in that: The specific process of determining whether to perform performance adjustment and feedback is as follows: Extracting the adjusted adaptation threshold from the monitoring database; Comparing the adjustment adaptation index of the LED headlight within the adjustment period with the adjustment adaptation threshold, if the adjustment adaptation index of the LED headlight within the adjustment period is greater than or equal to the adjustment adaptation threshold, determining not to perform performance adjustment and feedback; If the adjustment adaptation index of the LED headlights within the adjustment period is less than the adjustment adaptation threshold, it is determined that performance adjustment and feedback are to be performed.

9. The LED vehicle light operation monitoring system based on data analysis according to claim 8, characterized in that: The performance adjustment and feedback are performed, and the specific adjustment and feedback process is as follows: Performing difference processing on the adjustment adaptation threshold and the adjustment adaptation index of the LED headlight within the adjustment period, performing ratio processing on the processing result and the adjustment adaptation threshold, and finally obtaining the adjustment adaptation deviation rate of the LED headlight; The reference light intensity of the LED headlight within the demand cycle is adjusted according to the adjustment adaptation deviation rate of the LED headlight, and an adjustment report is generated for feedback.

10. A method for the LED vehicle light operation monitoring system based on data analysis as claimed in any one of claims 1 to 9, characterized in that: include: Step 1: Obtain the illumination parameters of the environment in which the LED headlights are located, and analyze the reference illumination intensity of the LED headlights; Step 2: monitor and collect circuit information of the LED headlights, locate the abnormal lamp beads of the LED headlights through data analysis, and adjust the abnormal lamp beads of the LED headlights according to the reference light intensity of the LED headlights; Step 3: monitor the operating status parameters of the LED headlights after adjustment, evaluate the adjustment adaptability index of the LED headlights, and determine whether to perform performance adjustment and feedback.

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