Constant current light source driver power control method and device

Abstract

The invention relates to a constant-current light source driver power control method and device, and the method comprises the steps: obtaining the light source type, driving parameters and working environment information of a constant-current light source driver, and carrying out the integration, and obtaining the corresponding basic control parameters of the driver; acquiring power data and temperature data of the constant-current light source driver, and performing association processing on the power data and the temperature data and light source characteristics to obtain corresponding real-time light source driving parameters; dynamically analyzing the basic control parameters of the driver according to the real-time light source driving parameters to obtain a corresponding power regulation trend; identifying the working state of the light source according to the basic control parameters of the driver to obtain corresponding working mode information, and predicting the working mode information based on the power regulation trend to obtain a corresponding protection strategy; and comprehensively analyzing the initial power control scheme and the protection strategy to obtain a corresponding global power regulation and control scheme. According to the invention, global power optimization regulation and control of the light source driver can be realized.

Description

Technical Field

[0001] The present invention relates to the technical field of constant current light source drivers, and in particular to a constant current light source driver power control method and device. Background Art

[0002] As a key component of modern optoelectronic systems, constant current light source drivers play an important role in lighting, display, sensing and other fields. With the rapid development of optoelectronic technology, higher and higher requirements are placed on the power control accuracy and stability of light source drivers. How to achieve accurate and efficient power regulation of light source drivers has become an important research direction for optoelectronic system optimization. However, existing light source driver power control methods have many limitations. Traditional control methods usually only consider single-dimensional parameters, such as light source type or basic driving parameters, while ignoring the comprehensive influence of multiple complex factors such as light source working environment, power supply characteristics, and temperature changes. This simplified control mode is difficult to fully capture the dynamic characteristics of the light source driver, which may lead to inaccurate power regulation and insufficient system adaptability, thereby affecting the overall performance and service life of optoelectronic equipment. Especially in different working environments and complex application scenarios, single-dimensional parameter control is more likely to cause problems such as power imbalance and improper thermal management, which restricts the stability and reliability of the light source driver. Summary of the invention

[0003] The main purpose of the present invention is to provide a constant current light source driver power control method and device, which can achieve global power optimization and regulation of the light source driver.

[0004] To achieve the above object, the present invention provides a constant current light source driver power control method, comprising: Obtain the light source type, driving parameters and working environment information of the constant current light source driver, and integrate them to obtain the corresponding basic control parameters of the driver; Acquire power supply data and temperature data of the constant current light source driver, associate them with light source characteristics, and obtain corresponding real-time light source driving parameters; Dynamically analyzing the basic control parameters of the driver according to the real-time light source driving parameters to obtain corresponding power regulation trends; Performing system control analysis on the power regulation trend to obtain a corresponding initial power control solution; Identify the working state of the light source according to the basic control parameters of the driver to obtain corresponding working mode information, predict the working mode information based on the power adjustment trend to obtain a corresponding protection strategy; The initial power control scheme and the protection strategy are comprehensively analyzed to obtain a corresponding global power regulation scheme.

[0005] Furthermore, the light source type, driving parameters and working environment information of the constant current light source driver are obtained and integrated to obtain the corresponding basic control parameters of the driver, including: Acquire light source emission spectrum data of the constant current light source driver, perform feature recognition analysis on the light source emission spectrum data, and obtain the light source type; Acquiring electrical parameters and optical parameters of the constant current light source driver, and performing feature analysis on the electrical parameters and the optical parameters based on the light source type to obtain the driving parameters; Acquiring physical environment parameters and mechanical environment parameters of the constant current light source driver, performing multi-dimensional mapping processing on the physical environment parameters and the mechanical environment parameters, and obtaining the working environment information; Perform constraint matching analysis on the driving parameters and the working environment information to obtain corresponding environmental adaptability evaluation results; Correcting the driving parameters according to the environmental adaptability evaluation results to obtain corresponding initial control parameters; Performing entropy value weight calculation on the initial control parameters to obtain a corresponding parameter weight configuration matrix; Performing cluster optimization on the initial control parameters based on the parameter weight configuration matrix to obtain a corresponding parameter optimization set; The initial control parameters are normalized according to the parameter optimization set to obtain the basic control parameters of the driver.

[0006] Furthermore, the acquiring of power supply data and temperature data of the constant current light source driver and the correlating processing with the light source characteristics to obtain corresponding real-time light source driving parameters include: Performing multi-point sampling on the voltage data of the constant current light source driver to obtain a corresponding power supply voltage signal; Performing high-frequency real-time monitoring and fluctuation feature extraction on the current data of the constant-current light source driver to obtain a current change characteristic curve; Constructing a power supply characteristic map according to the power supply voltage signal and the current change characteristic curve to obtain the power supply data; Performing temperature collection on the constant current light source driver to obtain the temperature data, and performing spatial distribution and time variation trend analysis to obtain temperature dynamic variation characteristics; By mapping and associating the power supply data with the temperature dynamic change characteristics, a temperature power supply coupling characteristic mapping table is obtained; Performing a multi-dimensional correlation evaluation on the temperature-power coupling characteristic mapping table to obtain a light source characteristic correlation evaluation result; A multi-dimensional parameter correlation calculation is performed based on the light source characteristic correlation evaluation result to obtain the real-time light source driving parameter.

[0007] Furthermore, the dynamic analysis of the basic control parameters of the driver according to the real-time light source driving parameters to obtain the corresponding power regulation trend includes: Performing correlation decomposition and matrix construction on the real-time light source driving parameters to obtain a parameter decoupling mapping relationship; Reconstructing the feature of the parameter decoupling mapping relationship and performing nonlinear encoding conversion to obtain a parameter feature space; Based on the parameter feature space, a dynamic logic network is constructed, and correlation analysis is performed on the basic control parameters of the driver to obtain a parameter correlation determination matrix; Discretizing and segmenting the parameter association determination matrix to obtain a power variation discrete sequence; Performing an inflection point sensitivity analysis on the power variation discrete sequence, identifying a critical switching point of power regulation, and obtaining a power regulation trend node; Feature matching and association verification are performed on the key nodes of the power regulation trend to obtain the power regulation trend.

[0008] Further, the performing system control analysis on the power regulation trend to obtain a corresponding initial power control scheme includes: Calculating the change characteristic gradient of the power regulation trend to obtain a power change slope sequence; Based on the power change slope sequence, discrete point interpolation processing is performed on the power regulation trend to obtain a continuous power change curve; Performing differential extraction on the continuous power variation curve to obtain comprehensive derivative characteristics of the first-order derivative and the second-order derivative; According to a preset gradient descent method, a loss function is constructed and calculated for the comprehensive derivative feature gradient to obtain a sensitivity coefficient; Performing threshold layering processing on the sensitivity coefficients to obtain a multi-dimensional power regulation control mapping relationship; Performing constraint optimization on the power regulation trend according to the regulation control mapping relationship to obtain the initial power control scheme; Among them, the formulas in the loss function construction calculation process include: ; represents the actual value, f(xi) represents the predicted value, sign() is the sign function, θ is the model parameter, α is the learning rate, and t is the iteration round.

[0009] Further, the light source working state is identified according to the basic control parameters of the driver to obtain corresponding working mode information, and the working mode information is predicted based on the power regulation trend to obtain a corresponding protection strategy, including: Extracting multi-dimensional characteristic parameters of the basic control parameters of the driver to obtain a characteristic vector of the light source working state; Performing light source clustering analysis according to the light source working state feature vector to obtain the working mode information; Establishing a light source working mode conversion probability matrix according to the working mode information, and performing probability distribution calculation to obtain a working mode conversion rule; Probabilistically analyzing the power regulation trend according to the working mode conversion rule to obtain corresponding risk assessment indicators; Construct a multi-dimensional risk weight matrix based on the risk assessment indicators, and conduct graded warning to obtain corresponding strategy classification information; The policy classification information is comprehensively analyzed to obtain the protection policy.

[0010] Furthermore, the light source working mode conversion probability matrix is ​​established according to the working mode information, and probability distribution calculation is performed to obtain the working mode conversion rule, including: Segmentally sampling the working mode information to obtain a working mode time slice sequence; Performing phase decomposition operation according to the working mode time slice sequence to obtain a mode conversion phase spectrum; Reconstructing and transforming the mode conversion phase spectrum to obtain a working mode conversion vector field; A function is constructed according to the working mode conversion vector field and a preset Markov state transfer equation to obtain a state transfer probability function; Performing Fourier transform on the state transfer probability function to obtain a frequency domain characteristic spectrum; Extract extreme points according to the frequency domain characteristic spectrum to obtain a working mode conversion topology structure; A graph theory analysis is performed on the working mode conversion topology to obtain a working mode conversion rule.

[0011] Furthermore, the initial power control scheme and the protection strategy are comprehensively analyzed to obtain a corresponding global power control scheme, including: Extracting power characteristics of the initial power control scheme to obtain a power characteristic vector; Performing working data mapping on the protection strategy to obtain a working information mapping sequence; Performing a multi-dimensional correlation analysis based on the power source characteristic vector and the working information mapping sequence to obtain power control related parameters; Dynamically calculating the weight coefficients of the power control related parameters to obtain a comprehensive evaluation index of power control; The initial power control scheme is iteratively optimized according to the comprehensive evaluation index of power control to obtain the global power control scheme.

[0012] The present invention also provides a constant current light source driver power control device, which is applied to any one of the above constant current light source driver power control methods, comprising: An acquisition module, which is used to obtain the light source type, driving parameters and working environment information of the constant current light source driver, and integrate them to obtain the corresponding basic control parameters of the driver; An analysis module, the analysis module is used to obtain power supply data and temperature data of the constant current light source driver, and associate them with light source characteristics to obtain corresponding real-time light source driving parameters; An association module, the association module is used to dynamically analyze the basic control parameters of the driver according to the real-time light source driving parameters to obtain a corresponding power adjustment trend; A processing module, the processing module is used to perform system control analysis on the power regulation trend to obtain a corresponding initial power control solution; A control module, the control module is used to identify the working state of the light source according to the basic control parameters of the driver, obtain corresponding working mode information, predict the working mode information based on the power regulation trend, and obtain a corresponding protection strategy; An execution module is used to comprehensively analyze the initial power control scheme and the protection strategy to obtain a corresponding global power regulation scheme.

[0013] The present invention provides a constant current light source driver power control method and device, which has the following beneficial effects: By associating system data with light source characteristic data and performing in-depth correlation analysis based on real-time environmental data, the power demand of the light source driver under different working conditions can be more accurately evaluated, thereby significantly improving the accuracy of power regulation and providing a more reliable technical basis for the design and operation of optoelectronic systems. Through dynamic mapping and correlation processing of power data and temperature data, the working status of the light source driver is managed in a refined manner, which helps to adjust the driving power on demand and avoid excessive energy consumption. Based on the comprehensive analysis of real-time temperature and power characteristics, it can ensure that the driver can operate efficiently and stably under different ambient temperatures and power supply fluctuations, reduce unnecessary energy consumption, and improve the overall operating efficiency of the system. Through systematic analysis of the basic control parameters and real-time working status of the driver, a more reasonable power regulation strategy can be formulated. By identifying special working modes and predicting possible risks, a targeted protection strategy can be constructed to achieve global power optimization regulation of the light source driver. This can not only effectively improve the reliability and service life of the equipment, but also flexibly adjust the power control strategy according to the characteristics and demand changes of different application scenarios, making the system more intelligent and adaptable. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a flow chart of a constant current light source driver power control method provided by the present invention; Figure 2 It is a structural diagram of a constant current light source driver power control device provided by the present invention.

[0015] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0017] The present invention is further described below in conjunction with the accompanying drawings and specific implementation methods.

[0018] Reference Figure 1 As shown, the present invention provides 1. A constant current light source driver power control method, characterized by comprising: Step S1: obtaining the light source type, driving parameters and working environment information of the constant current light source driver, and integrating them to obtain the corresponding basic control parameters of the driver; Step S2: acquiring power supply data and temperature data of the constant current light source driver, and performing correlation processing with the light source characteristics to obtain corresponding real-time light source driving parameters; Step S3: dynamically analyzing the basic control parameters of the driver according to the real-time light source driving parameters to obtain the corresponding power adjustment trend; Step S4: performing system control analysis on the power regulation trend to obtain a corresponding initial power control scheme; Step S5: Identify the working state of the light source according to the basic control parameters of the driver to obtain corresponding working mode information, predict the working mode information based on the power adjustment trend, and obtain a corresponding protection strategy; Step S6: Comprehensively analyze the initial power control scheme and the protection strategy to obtain a corresponding global power regulation scheme.

[0019] Based on the above steps, the detailed process is as follows: Step S1: Determine the light source type by matching the preset database, reading the built-in identification or analyzing the characteristic curve. Obtain the key parameters of the driver, including the rated output current, voltage range, dimming method, and performance indicators such as efficiency and power factor. Measure and record working environment information such as ambient temperature, humidity, installation location and power supply network characteristics. Comprehensively analyze and integrate this information, establish the association between the light source type and the driving parameters, and take the working environment information into consideration, and finally generate a comprehensive driver basic control parameter table and the corresponding driver basic control parameters; Step S2: Monitor and record the input voltage and current of the driver in real time, calculate the actual power consumption, and monitor the temperature of the driver housing and key components, as well as changes in ambient temperature. According to the acquired light source type, call the corresponding light source characteristic information, analyze the current-luminous flux relationship of the light source, and consider the impact of temperature on the performance of the light source. Establish the correlation between power data, temperature data and light source characteristics, calculate the actual output of the light source under the current working conditions, and evaluate the working efficiency and stability of the light source. Based on these analysis results, calculate the optimal driving current, determine the real-time power demand of the light source, and generate real-time driving parameters containing current, power, temperature and other information.

[0020] Step S3: Compare the real-time light source driving parameters with the basic control parameters in detail, calculate the deviation values ​​of each parameter, and evaluate the trend and amplitude of parameter changes. Identify and quantify the main factors affecting power changes, such as temperature and voltage fluctuations, and establish a multi-factor power impact model. Collect and analyze the driving parameter change data within a certain period of time, use statistical methods to analyze the parameter change rules, and establish a parameter change trend prediction model. Based on these analysis results, evaluate whether the current power needs to be adjusted, and determine the urgency and direction of the adjustment. Comprehensively consider the real-time parameters, historical data and adjustment requirements, use the prediction model to calculate the power change trend in the short term, and generate a power adjustment trend including the adjustment direction, amplitude and time.

[0021] Step S4: Determine the control objectives according to the light source type and application scenario, including light output stability requirements, power efficiency targets, and light source life and reliability requirements. Evaluate the power regulation capability and range of the driver, consider the constraints of the power supply network, and analyze the impact of environmental factors on the control, so as to determine the control constraints. Based on the power regulation trend, select an appropriate control strategy (such as PID, fuzzy control, etc.), determine the initial values ​​of the control parameters, and design the response characteristics of the control algorithm. Use the power regulation trend for simulation analysis to evaluate the effects of different control strategies. Based on the simulation results, select the optimal control strategy, determine the specific values ​​and timing of the power regulation, and generate an initial power control scheme that includes the control strategy, parameters, and expected effects.

[0022] Step S5: Using the basic control parameters as reference standards, analyze the current, voltage, power and other parameters of the current light source to determine whether the light source is in normal working condition. According to the working state identification results, determine the current working mode (such as normal, overload, undervoltage, etc.), record the deviation of each parameter from the standard value, and generate an information report containing the working mode and parameter deviation. Using the power regulation trend data, apply time series prediction algorithms (such as ARIMA, LSTM, etc.) to predict the changes in the working mode in the future and generate a working mode prediction report. Based on the prediction results, analyze the potential risks that may be brought about, assess the severity and probability of the risks, and determine the risk items that need to be handled first. Design corresponding protection measures for high-risk items, formulate response plans for different risk levels, and design the trigger conditions and execution process of the protection strategy.

[0023] Step S6: Compare the requirements of the initial power control scheme and protection strategy, identify possible conflict points, and evaluate the priority relationship between the two. Design solutions for the identified conflict points, adjust control parameters or protection thresholds to eliminate conflicts, and redesign some control strategies if necessary. Integrate the various requirements of power control and protection strategies, use multi-objective optimization algorithms to find the best balance point, and consider the overall performance and reliability of the system. Design a dynamic switching mechanism for power control and protection strategies, formulate adjustment strategies under different working conditions, and design emergency response procedures for abnormal situations. Integrate the optimized power control strategy and protection measures, formulate detailed execution steps and parameter settings, and generate a global solution document containing control logic, parameter configuration, and expected effects. .

[0024] A constant current light source driver power control method provided by the present invention can more accurately evaluate the power demand of the light source driver under different working conditions by associating system data with light source characteristic data and performing deep correlation analysis based on real-time environmental data, thereby significantly improving the accuracy of power regulation and providing a more reliable technical basis for the design and operation of optoelectronic systems. Through dynamic mapping and correlation processing of power data and temperature data, refined management of the working state of the light source driver is realized, which helps to adjust the driving power on demand and avoid excessive energy consumption. Based on the comprehensive analysis of real-time temperature and power supply characteristics, it can ensure that the driver can operate efficiently and stably under different ambient temperatures and power supply fluctuations, reduce unnecessary energy consumption, and improve the overall operating efficiency of the system. Through systematic analysis of the basic control parameters and real-time working state of the driver, a more reasonable power regulation strategy can be formulated. By identifying special working modes and predicting possible risks, a targeted protection strategy is constructed, thereby realizing global power optimization regulation of the light source driver. This can not only effectively improve the reliability and service life of the equipment, but also flexibly adjust the power control strategy according to the characteristics and demand changes of different application scenarios, making the system more intelligent and adaptable.

[0025] In one embodiment, the light source type, driving parameters and working environment information of the constant current light source driver are obtained and integrated to obtain the corresponding basic control parameters of the driver, including: Obtain the light source emission spectrum data of the constant current light source driver, perform feature recognition analysis on the light source emission spectrum data, and obtain the light source type. The spectrum data contains information such as the wavelength distribution and peak wavelength of the light source. Feature recognition analysis identifies the specific type of the current light source, such as LED, halogen lamp, etc., by comparing it with the preset light source spectrum feature library.

[0026] The electrical parameters and optical parameters of the constant current light source driver are obtained, and the characteristics of the electrical parameters and optical parameters are analyzed based on the light source type to obtain the driving parameters. The electrical parameters include the operating voltage, current, etc., and the optical parameters include the light intensity, color temperature, etc. During the characteristic analysis process, the key parameters are extracted according to the characteristics of different light source types, and normalized to form a standardized driving parameter set.

[0027] The physical environment parameters and mechanical environment parameters of the constant current light source driver are obtained, and multi-dimensional mapping processing is performed on the physical environment parameters and mechanical environment parameters to obtain working environment information. Physical environment parameters include temperature, humidity, etc., and mechanical environment parameters include vibration, shock, etc. Multi-dimensional mapping processing converts these parameters into unified evaluation indicators for subsequent analysis.

[0028] The drive parameters and working environment information are subjected to constraint matching analysis to obtain the corresponding environmental adaptability evaluation results. During the constraint matching analysis process, a correlation model between the drive parameters and environmental factors is established to evaluate the adaptability of the current drive parameters in a given environment and generate quantitative evaluation results.

[0029] According to the environmental adaptability assessment results, the driving parameters are corrected to obtain the corresponding initial control parameters. According to the assessment results, the correction process adjusts the sensitive items in the driving parameters to improve their adaptability and stability in the current environment.

[0030] The entropy weight calculation is performed on the initial control parameters to obtain the corresponding parameter weight configuration matrix. The entropy weight calculation method takes into account the information volume and importance of each parameter, assigns a reasonable weight to each parameter, and forms a weight configuration matrix.

[0031] Based on the parameter weight configuration matrix, the initial control parameters are clustered and optimized to obtain the corresponding parameter optimization set. In the cluster optimization process, similar parameters are grouped together to form several parameter clusters, and the optimal parameter combination is selected from each cluster to form a parameter optimization set.

[0032] This embodiment can accurately determine the type of light source by performing feature recognition analysis on the light source emission spectrum data, providing an accurate basis for subsequent parameter adjustment. Feature analysis of electrical and optical parameters, combined with the light source type, can obtain more accurate driving parameters and improve driving efficiency. Multi-dimensional mapping processes environmental parameters so that different types of environmental factors can be uniformly evaluated, enhancing environmental adaptability. Constraint matching analysis realizes dynamic adaptation of driving parameters to the environment, improving the stability and reliability of the system. Entropy weight calculation and clustering optimization ensure the scientificity and effectiveness of parameter adjustment and avoid the risks brought by blind adjustment. Normalization processing ensures the compatibility of the final basic control parameters of the driver with the control system, and improves control accuracy. The entire process realizes comprehensive consideration from light source characteristic analysis to environmental adaptability evaluation and then to parameter optimization, significantly improving the power control effect and adaptability of the constant current light source driver.

[0033] In one embodiment, power supply data and temperature data of a constant current light source driver are obtained, and are associated with light source characteristics to obtain corresponding real-time light source driving parameters, including: In the power data acquisition stage, multi-point sampling technology is used to accurately measure the voltage of the constant current light source driver. Specifically, at least 5 different time nodes are selected, each with an interval of 50 milliseconds, and the power supply voltage signal is obtained through a high-precision analog-to-digital converter, and the voltage change amplitude is recorded.

[0034] The current monitoring link uses high-frequency real-time monitoring technology, setting the monitoring frequency to 10kHz to capture small current fluctuations. Through the digital signal processing algorithm, the current change characteristic curve is extracted, focusing on the amplitude, frequency and periodic characteristics of the current fluctuation. When the current fluctuation amplitude exceeds the baseline value by 5%, the abnormal monitoring mechanism is triggered to record detailed current change data.

[0035] The power supply characteristic mapping is constructed based on the voltage signal and current change characteristic curve, and adopts a multi-dimensional mapping model. The model comprehensively considers factors such as voltage amplitude, current fluctuation characteristics, and time dimension to establish the power supply characteristic mapping relationship. The mapping model can identify the nonlinear characteristics of the power supply system and provide a data basis for subsequent analysis.

[0036] Temperature data acquisition uses a multi-point temperature sensor array to cover the key parts of the constant current light source driver. The spatial distribution of temperature sensors includes the driver chip, power module and cooling system, and the sampling frequency is 1Hz. Temperature data analysis uses a time series algorithm to extract temperature change trends and characteristics, focusing on temperature gradients and change rates. When the temperature exceeds the preset threshold or the change rate is abnormal, the temperature anomaly monitoring process is started.

[0037] The temperature-power coupling feature mapping is achieved by establishing a multi-dimensional correlation relationship. The power supply data and the temperature dynamic change characteristics are deeply correlated, and a feature fusion algorithm is used to construct a coupling feature mapping table containing indicators such as correlation coefficient and change trend matching degree. The mapping table can reveal the impact mechanism of temperature changes on the performance of the power supply system.

[0038] The light source characteristic correlation evaluation adopts a multi-dimensional correlation analysis method, including statistical correlation analysis and information entropy calculation. The evaluation process considers multiple dimensions such as power data, temperature characteristics, and light source performance indicators, and obtains the light source characteristic correlation evaluation results through a comprehensive scoring mechanism. The evaluation results quantify the degree of influence of each factor on the light source driving performance.

[0039] The real-time light source driving parameter calculation is based on the light source characteristic correlation evaluation results and adopts an adaptive parameter optimization algorithm. The algorithm dynamically adjusts the driving current, voltage and power parameters according to the correlation evaluation results to ensure that the light source maintains stability and efficiency under different working conditions. The parameter calculation process fully considers the system dynamic characteristics and real-time requirements.

[0040] This embodiment realizes the comprehensive and accurate capture of the power and temperature characteristics of the light source driving system through multi-point refined data collection and high-frequency real-time monitoring, significantly improving the accuracy and depth of system performance analysis. The innovative multi-dimensional correlation analysis technology can establish a deep mapping relationship between power data, temperature characteristics and light source performance, breaking through the limitations of traditional single-dimensional analysis. The adaptive parameter optimization algorithm enables the light source driver to adjust the driving parameters in real time and dynamically to ensure stable and efficient performance in a complex and changeable working environment. Compared with traditional methods, the present invention significantly improves the intelligence level of the constant current light source driver, realizes the precise regulation and adaptive optimization of system performance, and has important technical innovation value.

[0041] In one embodiment, the basic control parameters of the driver are dynamically analyzed according to the real-time light source driving parameters to obtain the corresponding power regulation trend, including: The multi-dimensional matrix construction technology is used to decouple and map the driving parameters from the dimensions of time, current, voltage, etc. On the basis of decoupling mapping, the feature reconstruction algorithm is used to perform nonlinear encoding conversion on the parameters to generate a multi-dimensional parameter feature space, which can accurately reflect the complex correlation between the parameters.

[0042] The dynamic logic network is constructed based on the parameter feature space. By establishing the parameter association judgment matrix, the basic control parameters of the drive are deeply analyzed for their association. The association judgment matrix introduces weight factors and correlation scoring mechanisms to quantify the degree of mutual influence between parameters. During the matrix construction process, strict threshold screening rules are set to ensure that only significantly related parameter association paths are retained, effectively reducing the complexity of the analysis.

[0043] The power change prediction adopts the discretization segmented prediction method to convert the continuous power change into a discrete sequence. The prediction model introduces the probability density function and the state transfer matrix, and constructs a probability prediction model for power change through statistical analysis of historical data. The generation of discrete sequences follows the minimum variance principle, which can minimize the prediction error and improve the prediction accuracy.

[0044] Inflection point sensitivity analysis is a key step in identifying power regulation trends. By performing differential and second-order derivative analysis on discrete sequences, the critical transition points of power changes can be accurately located. Sensitivity analysis introduces dynamic thresholds and change rate evaluation mechanisms, which can effectively distinguish between small fluctuations and significant changes. The identification of critical transition points is based on multi-dimensional indicators such as change rate, fluctuation amplitude, and duration.

[0045] The final determination of the power regulation trend is based on feature matching and association verification of key nodes. The verification process uses multimodal feature fusion technology, taking into account electrical characteristics, thermodynamic characteristics, and time dynamic characteristics. The feature matching algorithm evaluates the strength and consistency of associations between nodes by building a similarity measurement model. Association verification introduces a confidence scoring mechanism, and only when the association between nodes is significant and stable will it be included in the final power regulation trend.

[0046] This embodiment significantly improves the accuracy and depth of driver parameter analysis through multi-dimensional parameter decoupling and feature reconstruction technology, so that power regulation can be based on a more complex and comprehensive parameter association model. The dynamic logic network construction method breaks through the limitations of traditional single-dimensional parameter analysis and introduces a multi-dimensional correlation evaluation mechanism, which greatly enhances the system's sensitivity and response speed to parameter changes. Discrete segmented prediction and inflection point sensitivity analysis technology make power regulation trend prediction more accurate and reliable. By introducing probability density functions and state transfer matrices, the key transition points of power changes can be effectively identified to reduce prediction errors. The correlation verification method of multimodal feature fusion ensures the stability and consistency of the power regulation trend and improves the adaptability and robustness of the driver.

[0047] In one embodiment, a system control analysis is performed on the power regulation trend to obtain a corresponding initial power control scheme, including: The power regulation trend is systematically analyzed and controlled. By calculating the gradient of power change, the researchers selected time series data points, calculated the rate of change between adjacent data points, and constructed a power change slope sequence. In this process, the slope calculation uses the differential method, that is, the difference between the power values ​​of two adjacent points is divided by the time interval, so as to obtain the dynamic characteristics of power change.

[0048] For the discrete power change slope sequence, the spline interpolation method is used to fit the continuous curve. The interpolation algorithm selects cubic spline interpolation, which can ensure the smoothness and continuity of the curve and maintain the continuity of the first-order derivative at the interpolation point. Through this interpolation process, the originally discrete power change data is converted into a continuous change curve.

[0049] Perform differential operations on the continuous power change curve to extract the first-order and second-order derivatives. The first-order derivative reflects the rate of power change, while the second-order derivative reveals the trend of the power change rate. These two derivatives are combined in a weighted manner to construct a comprehensive derivative feature, and the weight coefficient is dynamically adjusted according to the actual application scenario and system characteristics.

[0050] Based on the gradient descent method, the loss function is constructed for the gradient of the comprehensive derivative feature. The loss function design takes into account the accuracy and stability of power control, including multi-dimensional indicators such as power deviation, regulation speed and energy consumption. Through iterative optimization, the sensitivity coefficient reflecting the system sensitivity is calculated, which quantifies the impact of power regulation on system performance.

[0051] The sensitivity coefficients are processed by threshold stratification to establish a multi-dimensional power regulation control mapping relationship. The threshold division is based on the system dynamic response characteristics and control accuracy requirements, and the sensitivity coefficients are divided into different levels, each corresponding to a different power regulation strategy. This hierarchical method makes power control more adaptable and can dynamically adjust the control strategy according to the real-time system status.

[0052] According to the constructed regulation control mapping relationship, the power regulation trend is constrained and optimized to generate the initial power control plan. The optimization process introduces constraints, such as power upper and lower limits, change rate constraints and energy efficiency requirements, and solves the optimal control plan through a multi-objective optimization algorithm.

[0053] Among them, the formulas in the loss function construction calculation process include: ; represents the actual value, f(xi) represents the predicted value, sign() is the sign function, θ is the model parameter, α is the learning rate, and t is the iteration round.

[0054] This embodiment achieves accurate description and continuous simulation of power change trends through gradient calculation and spline interpolation, significantly improving the dynamic response accuracy of power regulation. The use of comprehensive derivative feature extraction technology can fully capture the rate and acceleration characteristics of power change, providing more in-depth system insights for power control. By constructing the loss function and calculating the sensitivity coefficient through the gradient descent method, this method establishes a power regulation evaluation mechanism based on multi-dimensional indicators, which can accurately quantify system performance and regulation effects. The threshold layered processing technology makes the power control strategy more adaptive, and the control parameters can be dynamically adjusted according to the real-time system status, effectively improving the robustness and adaptability of the driver. The multi-objective optimization algorithm is introduced through the constrained optimization method to generate the optimal power control scheme while meeting the constraints such as power upper and lower limits, change rate and energy efficiency.

[0055] In one embodiment, the working state of the light source is identified according to the basic control parameters of the driver to obtain the corresponding working mode information, and the working mode information is predicted based on the power regulation trend to obtain the corresponding protection strategy, including: The characteristic vector of the working state of the light source is constructed by extracting multi-dimensional characteristic parameters of the basic control parameters of the driver. The feature extraction process includes data collection in dimensions such as current amplitude, voltage fluctuation, temperature change and time series, and these data are standardized to ensure that each characteristic parameter is compared and analyzed in the same dimension.

[0056] After the feature vector is constructed, the K-means clustering algorithm is used to classify the light source working status. Cluster analysis is based on the Euclidean distance metric, which clusters similar working states together to form different working mode clusters. Each cluster represents a typical light source working mode, such as stable working mode, overload mode, abnormal fluctuation mode, etc. The clustering results will serve as the basic working mode information for subsequent analysis.

[0057] In the working mode conversion analysis phase, a Markov transition probability matrix is ​​constructed. This matrix records the conversion probability between different working modes and is calculated by counting the frequency of mode conversion in historical data. For example, the probability of stable mode converting to overload mode, the probability of abnormal fluctuation mode converting to stable mode, etc. The probability matrix can reflect the dynamic change law of the working state of the light source.

[0058] The power regulation trend probability analysis is based on the transition probability matrix, combined with the current working mode and historical conversion rules, to predict the possible power change trend in the future. By calculating the probability of various conversion paths, the risk level in different power regulation scenarios is quantified. The risk assessment indicators include multi-dimensional quantitative indicators such as conversion probability, mode stability index and extreme value deviation degree.

[0059] The risk weight matrix is ​​constructed using the analytic hierarchy process, which assigns different weights to each risk indicator according to its importance. The matrix divides the risk level into three levels: low, medium, and high, and each level corresponds to a different warning threshold and processing strategy. When a high risk level is detected, the system will trigger the corresponding protection mechanism, such as reducing power, adjusting operating parameters, or starting emergency mode.

[0060] The protection strategy comprehensively considers the risk level, working mode characteristics and historical conversion rules. The strategy formulation follows the principle of risk minimization, while ensuring the normal operation of the light source, minimizing the risk of potential failures. The strategy includes various forms such as parameter adaptive adjustment, dynamic power limitation, and preventive maintenance recommendations to ensure the safe and reliable operation of the constant current light source driver.

[0061] This embodiment realizes accurate identification of the working status of the light source through multi-dimensional feature parameter extraction and cluster analysis, and significantly improves the adaptability and intelligent perception ability of the driver to complex working environments. The construction of the Markov transition probability matrix enables the system to dynamically capture the rules of working mode conversion, effectively predict potential risks, and realize proactive risk management. Through hierarchical risk assessment and graded early warning mechanisms, it is possible to respond to abnormal working conditions in a timely manner, reduce the probability of equipment failure, and extend the service life of the light source. The innovative design of the multi-dimensional risk weight matrix makes the protection strategy more accurate and personalized, which not only ensures the safe operation of the equipment, but also realizes energy consumption optimization and performance adjustment, reflecting the advancement and practicality of intelligent control.

[0062] In one embodiment, a light source working mode conversion probability matrix is ​​established according to the working mode information, and probability distribution calculation is performed to obtain a working mode conversion rule, including: The working mode information is sampled accurately in segments. The sampling process follows the Nyquist sampling theorem to ensure that the sampling frequency is not less than twice the highest frequency of the signal. Through a high-precision analog-to-digital converter, the continuous working mode information is discretized to generate a time slice sequence. Each time slice represents the working mode state within a specific time window, and the slice length is dynamically adjusted according to the system dynamic response characteristics and the signal change frequency.

[0063] The phase decomposition operation is performed on the obtained working mode time slice sequence. The Hilbert-Huang transform method is used to decompose the complex signal into several intrinsic mode functions through empirical mode decomposition, and each mode function is Hilbert transformed to extract the instantaneous frequency and amplitude information. In the phase decomposition process, an adaptive threshold mechanism is introduced to effectively suppress noise interference and extract the key phase characteristics of mode conversion.

[0064] The mode conversion phase spectrum is reconstructed and transformed to construct the working mode conversion vector field. The vector field construction is based on differential geometry theory, mapping discrete mode conversion points to continuous manifold space. The topological structure and flow characteristics of mode conversion are captured through gradient descent and manifold learning algorithms. The vector field characterizes the directionality and energy transfer law of mode conversion, laying the foundation for subsequent analysis.

[0065] According to the working mode conversion vector field, combined with the preset Markov state transition equation, the state transition probability function is constructed. The Markov state transition equation describes the probability dependence of the system from one working mode to another. The probability function introduces entropy weight and information gain factor, uncertainty of mode conversion and information complexity.

[0066] Fourier transform is performed on the state transition probability function to obtain the frequency domain characteristic spectrum. Fourier transform converts the time domain signal into a frequency domain representation, revealing the frequency characteristics and periodicity of the mode conversion. Through power spectrum density analysis, the dominant frequency components and spectrum peaks are identified to reflect the dynamic characteristics of the system.

[0067] The extreme points are extracted from the frequency domain characteristic spectrum to construct the working mode conversion topology. The extreme point extraction uses wavelet transform and multi-scale analysis methods to identify the key turning points and characteristic nodes in the characteristic spectrum. The topological structure reflects the connectivity and correlation of the mode conversion and reveals the internal conversion mechanism of the system.

[0068] Finally, the working mode conversion topology is analyzed by graph theory to extract the working mode conversion rules. Graph theory analysis is based on complex network theory to calculate node centrality, connectivity and modularity. Through feature extraction and pattern recognition, the probability matrix of working mode conversion is established, providing a theoretical basis for the power control of the constant current light source driver.

[0069] This embodiment significantly improves the accuracy and dynamic response capability of the power control of the constant current light source driver through precise segmented sampling and phase decomposition of the working mode information. The Hilbert-Huang transform and adaptive threshold mechanism are used to effectively suppress the system noise interference and improve the accuracy of the mode conversion feature extraction. The working mode conversion vector field constructed based on differential geometry theory realizes the high-dimensional mapping and dynamic modeling of the complex conversion process of the system, and reveals the topological structure and energy transfer law of the mode conversion. The Markov state transition probability function and entropy weight factor are introduced to quantify the uncertainty and information complexity of the system conversion. Through frequency domain characteristic spectrum analysis and graph theory methods, the present invention establishes a probability matrix of working mode conversion, which provides a theoretical basis for the power control of the constant current light source driver. Compared with traditional methods, this method can more accurately capture the dynamic characteristics of the system, improve the intelligence and adaptability of power control, and significantly optimize the performance and energy efficiency of the light source driver.

[0070] In one embodiment, the initial power control scheme and the protection strategy are comprehensively analyzed to obtain a corresponding global power control scheme, including: In the power feature extraction stage, multi-dimensional signal decomposition technology is used to perform spectrum analysis and waveform feature extraction on the power input signal to construct a power feature vector containing indicators such as voltage fluctuation, current stability, and harmonic content. The construction of the feature vector follows the IEEE standard to ensure the accuracy and representativeness of the data.

[0071] In the working data mapping phase, by establishing the operating status mapping model of the light source driver, key working parameters such as temperature, current, and load are standardized and encoded to generate a unique and comparable working information mapping sequence. The mapping process introduces normalization processing to eliminate the dimensional differences of different parameters and ensure the fairness of subsequent correlation analysis. The mapping rules are based on the working characteristic curve of the light source driver, covering the data mapping strategies of the normal working area, transition area, and extreme area.

[0072] Multi-dimensional correlation analysis is based on the association algorithm in machine learning, which deeply explores the potential correlation between the power feature vector and the working information mapping sequence. The analysis method uses Pearson correlation coefficient, mutual information theory, principal component analysis and other technologies to build a multi-dimensional correlation evaluation model. By calculating the correlation strength and direction between different feature dimensions, the key parameters that have a significant impact on power regulation are extracted to form a set of power regulation correlation parameters.

[0073] The dynamic calculation of the weight coefficients of power control related parameters adopts an adaptive weight algorithm to dynamically adjust the importance weight of each parameter according to the real-time working environment and historical operation data. The weight calculation introduces the entropy weight method and fuzzy evaluation theory to comprehensively consider the discrete degree, sensitivity and stability of the parameters. By constructing a multi-criteria decision-making model, a comprehensive evaluation index of power control that can fully reflect the complexity of the system is generated.

[0074] Based on the comprehensive evaluation index, the initial power control scheme is iteratively optimized. The optimization algorithm selects a hybrid strategy of the improved particle swarm algorithm and the simulated annealing algorithm to achieve precise adjustment of the power control scheme while ensuring system stability. Multiple constraints are set in the iterative process, including maximum power deviation, energy conversion efficiency, temperature rise control, etc., to ensure that the optimization results meet the performance requirements of the constant current light source driver. The final global power control scheme has the characteristics of self-adaptation and intelligence, which can significantly improve the working reliability and energy utilization efficiency of the driver.

[0075] This embodiment establishes an accurate power control model through multi-dimensional power feature extraction and working data mapping, which can realize comprehensive perception and intelligent analysis of the operating status of the constant current light source driver. This method breaks through the static limitations of traditional power control, introduces a dynamic and adaptive control mechanism, and significantly improves the working adaptability and stability of the driver. The innovative multi-dimensional correlation analysis technology effectively explores the deep correlation between power supply characteristics and working parameters, and realizes accurate evaluation and intelligent optimization of the power control process through accurate dynamic calculation of weight coefficients. Compared with traditional methods, this method can more accurately predict and adjust the power output of the driver, reduce system energy consumption, and improve energy conversion efficiency. In addition, the global power control scheme based on iterative optimization not only ensures the stability of the system, but also has a high degree of intelligent characteristics. It can autonomously adjust the power control strategy according to the real-time working environment, effectively extending the service life of the constant current light source driver and improving the reliability and performance of the equipment.

[0076] Reference Figure 2 As shown, the present invention provides a constant current light source driver power control device, which is applied to any one of the above constant current light source driver power control methods, including: The acquisition module is used to obtain the light source type, driving parameters and working environment information of the constant current light source driver, and integrate them to obtain the corresponding basic control parameters of the driver; An analysis module is used to obtain power supply data and temperature data of a constant current light source driver, and associate the data with light source characteristics to obtain corresponding real-time light source driving parameters; The correlation module is used to dynamically analyze the basic control parameters of the driver according to the real-time light source driving parameters to obtain the corresponding power adjustment trend; A processing module, the processing module is used to perform system control analysis on the power regulation trend and obtain a corresponding initial power control plan; The control module is used to identify the working state of the light source according to the basic control parameters of the driver, obtain the corresponding working mode information, predict the working mode information based on the power regulation trend, and obtain the corresponding protection strategy; The execution module is used to comprehensively analyze the initial power control plan and the protection strategy to obtain the corresponding global power regulation plan.

[0077] A constant current light source driver power control device provided by the present invention can more accurately evaluate the power demand of the light source driver under different working conditions by associating system data with light source characteristic data and performing deep correlation analysis based on real-time environmental data, thereby significantly improving the accuracy of power regulation and providing a more reliable technical basis for the design and operation of optoelectronic systems. Through dynamic mapping and correlation processing of power data and temperature data, refined management of the working state of the light source driver is realized, which helps to adjust the driving power on demand and avoid excessive energy consumption. Based on the comprehensive analysis of real-time temperature and power supply characteristics, it can ensure that the driver can operate efficiently and stably under different ambient temperatures and power supply fluctuations, reduce unnecessary energy consumption, and improve the overall operating efficiency of the system. Through systematic analysis of the basic control parameters and real-time working state of the driver, a more reasonable power regulation strategy can be formulated. By identifying special working modes and predicting possible risks, a targeted protection strategy is constructed to achieve global power optimization regulation of the light source driver. This can not only effectively improve the reliability and service life of the equipment, but also flexibly adjust the power control strategy according to the characteristics and demand changes of different application scenarios, making the system more intelligent and adaptable.

[0078] It should be noted that technicians in the relevant technical field can clearly understand that for the convenience and conciseness of description, the specific working process of the system and each module described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0079] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A constant current light source driver power control method, characterized in that: include: Obtain the light source type, driving parameters and working environment information of the constant current light source driver, and integrate them to obtain the corresponding basic control parameters of the driver; Acquire power supply data and temperature data of the constant current light source driver, associate them with light source characteristics, and obtain corresponding real-time light source driving parameters; Dynamically analyzing the basic control parameters of the driver according to the real-time light source driving parameters to obtain corresponding power regulation trends; Performing system control analysis on the power regulation trend to obtain a corresponding initial power control solution; Identify the working state of the light source according to the basic control parameters of the driver to obtain corresponding working mode information, predict the working mode information based on the power adjustment trend to obtain a corresponding protection strategy; The initial power control scheme and the protection strategy are comprehensively analyzed to obtain a corresponding global power regulation scheme.

2. The constant current light source driver power control method according to claim 1, characterized in that: The light source type, driving parameters and working environment information of the constant current light source driver are obtained and integrated to obtain the corresponding basic control parameters of the driver, including: Acquire light source emission spectrum data of the constant current light source driver, perform feature recognition analysis on the light source emission spectrum data, and obtain the light source type; Acquiring electrical parameters and optical parameters of the constant current light source driver, and performing feature analysis on the electrical parameters and the optical parameters based on the light source type to obtain the driving parameters; Acquiring physical environment parameters and mechanical environment parameters of the constant current light source driver, performing multi-dimensional mapping processing on the physical environment parameters and the mechanical environment parameters, and obtaining the working environment information; Perform constraint matching analysis on the driving parameters and the working environment information to obtain corresponding environmental adaptability evaluation results; Correcting the driving parameters according to the environmental adaptability evaluation results to obtain corresponding initial control parameters; Performing entropy value weight calculation on the initial control parameters to obtain a corresponding parameter weight configuration matrix; Performing cluster optimization on the initial control parameters based on the parameter weight configuration matrix to obtain a corresponding parameter optimization set; The initial control parameters are normalized according to the parameter optimization set to obtain the basic control parameters of the driver.

3. The constant current light source driver power control method according to claim 1, characterized in that: The acquiring of the power supply data and the temperature data of the constant current light source driver and the correlating processing with the light source characteristics to obtain the corresponding real-time light source driving parameters includes: Performing multi-point sampling on the voltage data of the constant current light source driver to obtain a corresponding power supply voltage signal; Performing high-frequency real-time monitoring and fluctuation feature extraction on the current data of the constant-current light source driver to obtain a current change characteristic curve; Constructing a power supply characteristic map according to the power supply voltage signal and the current change characteristic curve to obtain the power supply data; Performing temperature collection on the constant current light source driver to obtain the temperature data, and performing spatial distribution and time variation trend analysis to obtain temperature dynamic variation characteristics; By mapping and associating the power supply data with the temperature dynamic change characteristics, a temperature power supply coupling characteristic mapping table is obtained; Performing a multi-dimensional correlation evaluation on the temperature-power coupling characteristic mapping table to obtain a light source characteristic correlation evaluation result; A multi-dimensional parameter correlation calculation is performed based on the light source characteristic correlation evaluation result to obtain the real-time light source driving parameter.

4. The constant current light source driver power control method according to claim 1, characterized in that: The dynamically analyzing the basic control parameters of the driver according to the real-time light source driving parameters to obtain the corresponding power regulation trend includes: Performing correlation decomposition and matrix construction on the real-time light source driving parameters to obtain a parameter decoupling mapping relationship; Reconstructing the feature of the parameter decoupling mapping relationship and performing nonlinear encoding conversion to obtain a parameter feature space; Based on the parameter feature space, a dynamic logic network is constructed, and correlation analysis is performed on the basic control parameters of the driver to obtain a parameter correlation determination matrix; Discretizing and segmenting the parameter association determination matrix to obtain a power variation discrete sequence; Performing an inflection point sensitivity analysis on the power variation discrete sequence, identifying a critical switching point of power regulation, and obtaining a power regulation trend node; Feature matching and association verification are performed on the key nodes of the power regulation trend to obtain the power regulation trend.

5. The constant current light source driver power control method according to claim 1, characterized in that: The performing system control analysis on the power regulation trend to obtain a corresponding initial power control scheme includes: Calculating the change characteristic gradient of the power regulation trend to obtain a power change slope sequence; Based on the power change slope sequence, discrete point interpolation processing is performed on the power regulation trend to obtain a continuous power change curve; Performing differential extraction on the continuous power variation curve to obtain comprehensive derivative characteristics of the first-order derivative and the second-order derivative; According to a preset gradient descent method, a loss function is constructed and calculated for the comprehensive derivative feature gradient to obtain a sensitivity coefficient; Performing threshold layering processing on the sensitivity coefficients to obtain a multi-dimensional power regulation control mapping relationship; Performing constraint optimization on the power regulation trend according to the regulation control mapping relationship to obtain the initial power control scheme; Among them, the formulas in the loss function construction calculation process include: ； represents the actual value, f(xi) represents the predicted value, sign() is the sign function, θ is the model parameter, α is the learning rate, and t is the iteration round.

6. The constant current light source driver power control method according to claim 1, characterized in that: The step of identifying the working state of the light source according to the basic control parameters of the driver to obtain corresponding working mode information, and predicting the working mode information based on the power regulation trend to obtain a corresponding protection strategy includes: Extracting multi-dimensional characteristic parameters of the basic control parameters of the driver to obtain a characteristic vector of the light source working state; Performing light source clustering analysis according to the light source working state feature vector to obtain the working mode information; Establishing a light source working mode conversion probability matrix according to the working mode information, and performing probability distribution calculation to obtain a working mode conversion rule; Probabilistically analyzing the power regulation trend according to the working mode conversion rule to obtain corresponding risk assessment indicators; Construct a multi-dimensional risk weight matrix based on the risk assessment indicators, and conduct graded warning to obtain corresponding strategy classification information; The policy classification information is comprehensively analyzed to obtain the protection policy.

7. The constant current light source driver power control method according to claim 1, characterized in that: The step of establishing a light source working mode conversion probability matrix according to the working mode information and performing probability distribution calculation to obtain a working mode conversion rule includes: Segmentally sampling the working mode information to obtain a working mode time slice sequence; Performing phase decomposition operation according to the working mode time slice sequence to obtain a mode conversion phase spectrum; Reconstructing and transforming the mode conversion phase spectrum to obtain a working mode conversion vector field; A function is constructed according to the working mode conversion vector field and a preset Markov state transfer equation to obtain a state transfer probability function; Performing Fourier transform on the state transfer probability function to obtain a frequency domain characteristic spectrum; Extract extreme points according to the frequency domain characteristic spectrum to obtain a working mode conversion topology structure; A graph theory analysis is performed on the working mode conversion topology to obtain a working mode conversion rule.

8. The constant current light source driver power control method according to claim 1, characterized in that: The comprehensive analysis of the initial power control scheme and the protection strategy to obtain a corresponding global power regulation scheme includes: Extracting power characteristics of the initial power control scheme to obtain a power characteristic vector; Performing working data mapping on the protection strategy to obtain a working information mapping sequence; Performing a multi-dimensional correlation analysis based on the power source characteristic vector and the working information mapping sequence to obtain power control related parameters; Dynamically calculating the weight coefficients of the power control related parameters to obtain a comprehensive evaluation index of power control; The initial power control scheme is iteratively optimized according to the comprehensive evaluation index of power control to obtain the global power control scheme.

9. A constant current light source driver power control device, characterized in that: The constant current light source driver power control method applied to any one of claims 1 to 8 above comprises: An acquisition module, which is used to obtain the light source type, driving parameters and working environment information of the constant current light source driver, and integrate them to obtain the corresponding basic control parameters of the driver; An analysis module, the analysis module is used to obtain power supply data and temperature data of the constant current light source driver, and associate them with light source characteristics to obtain corresponding real-time light source driving parameters; An association module, the association module is used to dynamically analyze the basic control parameters of the driver according to the real-time light source driving parameters to obtain a corresponding power adjustment trend; A processing module, the processing module is used to perform system control analysis on the power regulation trend to obtain a corresponding initial power control solution; A control module, the control module is used to identify the working state of the light source according to the basic control parameters of the driver, obtain corresponding working mode information, predict the working mode information based on the power regulation trend, and obtain a corresponding protection strategy; An execution module is used to comprehensively analyze the initial power control scheme and the protection strategy to obtain a corresponding global power regulation scheme.

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