Method for optimizing stability of photoelectric information conversion assembly in severe environment

Abstract

The invention belongs to the technical field of electronic information, and provides a method for optimizing the stability of a photoelectric information conversion assembly in a severe environment, which comprises the step of optimizing the stability of the photoelectric information conversion assembly in the severe environment. The method comprises the following steps of: synchronously acquiring environment parameters such as temperature, humidity and illumination and equipment current data in a high-temperature and high-humidity environment to construct a multi-dimensional time sequence group; analyzing the coupling degree of each environment parameter and the current sequence, and after locking the high coupling relationship between illumination and current, judging whether the current response has delay or not when the illumination suddenly changes; if the delay exists, further analyzing the current response sensitivity, if the sensitivity deviates from expectation, constructing an illumination-current prediction model, and calculating the current regulation quantity in advance by predicting the illumination abrupt change amplitude to realize pre-regulation; and finally, collecting the adjusted data iteration optimization model, and improving the dynamic response performance and stability of the assembly in a complex environment.

Description

Technical Field

[0001] This invention belongs to the field of electronic information technology, specifically a method for optimizing the stability of photoelectric information conversion components under harsh environments. Background Technology

[0002] As a key component for clean energy utilization and information acquisition, optoelectronic information conversion components are subjected to harsh environments with high temperature and high humidity for a long time. The ambient temperature often exceeds 40°C and the humidity is maintained above 80%. These conditions not only accelerate the aging of optoelectronic information conversion components and supporting circuit components, but also pose a severe challenge to the current response characteristics of the components.

[0003] Existing solutions to address the current response lag problem in optoelectronic information conversion components under sudden changes in illumination have significant limitations. Firstly, traditional current regulation strategies often rely on real-time feedback control, meaning regulation only begins after a sudden change in illumination causes a current deviation. High temperature and humidity environments further amplify the response delay of circuit components, resulting in a current response lagging behind actual requirements. Secondly, existing technologies lack sufficient analysis of the correlation between illumination and current, failing to quantify the degree of coupling between the two and making it difficult to predict the magnitude and timing of sudden changes in illumination. Therefore, it is impossible to achieve advance regulation to offset the lag effect. Thus, a technical solution is urgently needed that can accurately capture the illumination-current correlation characteristics and achieve advance prediction and dynamic optimization to solve the current response lag problem under sudden changes in illumination.

[0004] Therefore, the present invention provides a method for optimizing the stability of photoelectric information conversion components under harsh environments. Summary of the Invention

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

[0006] The technical solution adopted by this invention to solve its technical problem is: a method for optimizing the stability of a photoelectric information conversion component under harsh environments, comprising: Collect environmental parameters and current data of photoelectric information conversion components; construct multiple sets of one-dimensional sequences of environmental parameters and current value sequences of current data according to the collection time sequence, and integrate the multiple sets of one-dimensional sequences into a multi-dimensional sequence group; Analyze the coupling degree index between the single-dimensional sequence and the current value sequence in the multidimensional sequence group. If the coupling degree index shows that the light intensity sequence and the current value sequence of the current data contained in the single-dimensional sequence have a high coupling relationship, then analyze whether there is a delay in the current response when the light intensity changes abruptly. If there is a delay in the current response and the current response sensitivity deviates from the expectation, then an illumination-current prediction model is constructed, and the amplitude of the illumination change is predicted to calculate the current regulation amount and realize the pre-regulation of the current. The illumination-current prediction model was iteratively optimized using multiple sets of pre-adjusted and compliant light intensity and current data.

[0007] Furthermore, the process of obtaining the coupling degree index is as follows: Collect multiple sets of environmental parameters in the environment where the photoelectric information conversion component equipment is located, and construct a single-dimensional sequence corresponding to the multiple sets of environmental parameters; Obtain the correlation deviation between the one-dimensional sequence and the current value sequence, and construct a coupling degree calculation formula based on the correlation deviation. The coupling degree between the one-dimensional sequence and the current value sequence at each acquisition time point is obtained by using the coupling degree calculation formula. The coupling degree of each collection point is averaged to obtain the coupling degree index. If the coupling index is greater than the preset coupling threshold, it indicates that the one-dimensional sequence and the current value sequence have a preliminary strong coupling relationship. The obtained coupling indexes are sorted in descending order, and the single-dimensional sequence corresponding to the maximum value of the coupling index is extracted. If the one-dimensional sequence and the current value sequence have a preliminary strong coupling relationship and the one-dimensional sequence is the sequence with the maximum coupling index, then it indicates that the one-dimensional sequence and the current value sequence have a strong coupling relationship.

[0008] Furthermore, the method for obtaining the correlation deviation value is as follows: The average value of the one-dimensional sequence is obtained by averaging the one-dimensional sequence, and the average value of the current value sequence is obtained by averaging the current value sequence. Obtain the maximum and minimum values ​​of the one-dimensional sequence, and then compare the difference between the maximum and minimum values ​​with the average value of the one-dimensional sequence to obtain the sequence bias of the one-dimensional sequence. Obtain the maximum and minimum values ​​of the current value sequence, then take the difference between the maximum and minimum values ​​and compare it with the average value of the current value sequence to obtain the sequence deviation of the current value sequence. The correlation deviation value between the one-dimensional sequence and the current value sequence is obtained by subtracting the sequence deviation of the one-dimensional sequence from that of the current value sequence.

[0009] Furthermore, the process of analyzing whether there is a delay in the current response is as follows: Acquire the light intensity sequence and current value sequence, including the light intensity change value and current change value at each acquisition time point; The values ​​of light change and current change are integrated into light change sequence and current change sequence; The normal fluctuation values ​​of the illumination change sequence and the threshold for significant current changes were obtained respectively. The light change value is compared with the normal fluctuation value of the light change sequence to obtain the light change abruptness index. The current mutation index is obtained by comparing the current change value with the threshold of significant current change in the current change sequence. Based on the obtained light and current abrupt change indices, abrupt change analysis was performed, and the collection points were marked as light abrupt change points and current abrupt change points. The light and current abrupt change points were integrated into light abrupt change sequences and current abrupt change sequences according to the acquisition time. The time delay sequence is obtained based on the light illumination mutation sequence and the current mutation sequence, and the coefficient of variation of the time delay sequence is calculated. Determine whether there is a significant lag in the current response based on the time delay sequence and the coefficient of variation of the time delay sequence.

[0010] Furthermore, the process of obtaining the normal fluctuation value and the threshold for significant current change is as follows: The mean and standard deviation of the illumination variation sequence were calculated based on the illumination variation sequence. Normal fluctuation values ​​are defined based on the 3σ principle and the mean and standard deviation of the illumination variation sequence; The mean and standard deviation of the current change sequence are calculated based on the current change sequence. The threshold for significant current change is defined based on the 3σ principle, as well as the mean and standard deviation of the current change sequence.

[0011] Furthermore, the process of performing current response sensitivity analysis is as follows: The average delay time of the current response is obtained by averaging the time delay sequence. And the standard deviation of the delay time is calculated based on the average delay time; The light intensity changes at all abrupt light change points are averaged to obtain the average light intensity change between abrupt light change points. By integrating the current change values ​​at all current abrupt points, the average current change value between current abrupt points is obtained; The ratio of the average light intensity variable to the average current variable is used to obtain the light-current ratio. The ratio of the light-current ratio to the average current response delay time is used to obtain the current response rate. The current response sensitivity is obtained by comparing the current response rate with the standard deviation of the delay time.

[0012] Furthermore, the process of predicting the magnitude of sudden changes in illumination is as follows: Average delay time based on current response Divide the sliding window into ; Obtain the slope of change within the sliding window, the cumulative change before the abrupt change, and the fluctuation value; and construct an equation to predict the magnitude of the abrupt change in illumination. The slope of change within the sliding window, the cumulative change before the abrupt change, and the fluctuation value are input into the equation for predicting the magnitude of the light intensity abrupt change to obtain the predicted light intensity abrupt change value.

[0013] Furthermore, the method for obtaining the slope of change, the cumulative change before the abrupt change, and the fluctuation value within the sliding window is as follows: Slope of change: Calculate the slope within the sliding window. The slope of the linear fitting of the light intensity at each acquisition time point; Cumulative change before mutation: The sum of all values ​​within a sliding window whose change in illumination is greater than Q times the normal fluctuation value; Where Q is a preset multiple; Fluctuation value: Calculate the ratio of the standard deviation to the mean of the illumination mutation index at each collection time point within the sliding window, and average the ratio at each collection time point to obtain the fluctuation value.

[0014] Furthermore, the process of calculating the current adjustment amount and achieving pre-adjustment is as follows: Extract the mean values ​​of the illumination change sequence and the current change sequence; The basic adjustment coefficient is obtained by comparing the mean of the illumination change sequence with the mean of the current change sequence. A formula for predicting current regulation is constructed based on the predicted amplitude of sudden changes in light intensity and the basic regulation coefficient. The predicted light intensity abrupt change value and the basic regulation coefficient are input into the current regulation prediction formula to obtain the current regulation amount;

[0015] Develop targeted regulation strategies based on predicted light intensity spikes and current adjustments.

[0016] Furthermore, the iterative optimization process for the illumination-current prediction model is as follows: After the pre-adjustment is implemented, multiple sets of light intensity and current data are collected, and the current response sensitivity is calculated separately. If the current response sensitivity of each set of light intensity and current data meets the requirements, it means that the current sensitivity meets the standard. Based on multiple sets of light intensity and current data, the basic adjustment coefficients of the light-current prediction model were recalculated and calibrated using the mean light intensity variation and the mean current variation.

[0017] The beneficial effects of this invention are as follows: 1. In harsh environments with high temperature and humidity, environmental parameters and current data of photoelectric information conversion components are collected simultaneously. Multiple sets of single-dimensional sequences of environmental parameters and current value sequences of current data are constructed according to the collection time sequence, and the environmental parameter sequences are integrated into multi-dimensional sequence groups. This facilitates the correlation between the dynamic relationship between high-temperature and high-humidity environmental parameters and the current of the photoelectric information conversion components, providing time-matched multi-dimensional basic data for analyzing the performance of the equipment in harsh environments. Based on the multi-dimensional sequence groups, the coupling degree index between the sequences and current value sequences in the multi-dimensional sequence groups is analyzed. If the light intensity sequence and the current value sequence have a high coupling relationship, it is determined whether there is a delay in the current response when the light intensity changes abruptly. This allows for the identification of light intensity as a key influencing factor, and by judging the current response delay when it changes abruptly, the dynamic response performance of the equipment under the influence of this factor can be effectively evaluated. 2. If there is a delay in the current response, a sensitivity response analysis is performed to obtain the current response sensitivity. If the current response sensitivity deviates from the expectation, a light-current prediction model is constructed. By predicting the magnitude of sudden changes in light intensity, the current adjustment amount is calculated in advance to achieve pre-adjustment of the current. This can specifically solve the problem of current response delay. When the sensitivity deviates from the expectation, the light-current prediction model calculates the adjustment amount in advance to achieve pre-adjustment, effectively ensuring the current stability and operating performance of the equipment. Multiple sets of data after adjustment are collected and analyzed. The light-current prediction model is iteratively optimized based on the analysis results. Through iterative optimization, the light-current prediction model is made to better fit the actual adjustment data, continuously improving the pre-adjustment accuracy and ensuring stable operation of the equipment. Attached Figure Description

[0018] The invention will now be further described with reference to the accompanying drawings.

[0019] Figure 1 This is a flowchart illustrating the steps of an optimization method for a photoelectric information conversion component under harsh conditions, as described in an embodiment of the present invention. Figure 2 This is a logic diagram of a stability optimization method for a photoelectric information conversion component under harsh environments, as described in an embodiment of the present invention. Figure 3 This is a block diagram of a stability optimization system for a photoelectric information conversion component under harsh environments, as described in an embodiment of the present invention. Detailed Implementation

[0020] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0021] Example 1: Please refer to Figure 1 As shown in the embodiment of the present invention, a method for optimizing the stability of a photoelectric information conversion component under harsh environments includes: S1: In harsh environments with high temperature and high humidity, environmental parameters and current data of photoelectric information conversion components are collected simultaneously; multiple single-dimensional sequences of environmental parameters and current value sequences of current data are constructed according to the collection time sequence, and the environmental parameter sequences are integrated into multi-dimensional sequence groups; The process of simultaneously collecting environmental parameters and current data of photoelectric information conversion components in harsh environments with high temperature and high humidity is as follows: Select temperature and humidity resistant industrial-grade sensors to collect temperature and humidity data of the photoelectric information conversion component equipment in harsh environments; the temperature range of the sensor needs to cover 0-120℃ with an accuracy of ±0.1℃, and the humidity sensor needs to support 5-100%RH measurement with an accuracy of ±3%RH; The light intensity in the harsh environment in which the equipment is located is collected using a spectral sensor; the spectral sensor has a measurement range of 0-65535 lux and supports visible light and infrared spectrum. The current value of the photoelectric information conversion component is collected by a current transformer, and the range is adjusted according to the rated current of the equipment. Temperature data, humidity data, and light intensity data are collectively referred to as environmental parameters, and current magnitude is marked as equipment operating data. All sensors are triggered by hardware or synchronized via NTP time protocol to ensure that the time error at each acquisition point is less than 10 milliseconds; After ensuring that the environmental parameters and equipment operation data are collected at the same time, sample the environmental parameters and equipment operation data once per second. The collected environmental parameters and equipment operation data are preprocessed. Understandably, the preprocessing process involves: first, removing outliers caused by sensor momentary drift, communication interruption, or electromagnetic interference; and then performing a moving average on environmental parameters and equipment operating data to suppress high-frequency noise and ensure the validity of the collected data. The process of constructing multiple sets of one-dimensional sequences of environmental parameters and current value sequences of current data according to the acquisition time sequence, and integrating the environmental parameter sequences into a multi-dimensional sequence group, is as follows: The preprocessed environmental parameters and equipment operation data are summarized in the order of the collection time points to obtain temperature sequence, humidity sequence, light intensity sequence, collectively referred to as single-dimensional sequence and current value sequence; Integrate single-dimensional sequences into multi-dimensional sequence groups; S2: Based on the multidimensional sequence set, analyze the coupling index between the sequence and the current value sequence in the multidimensional sequence set; if the light intensity sequence and the current value sequence are highly coupled, determine whether there is a delay in the current response when the light intensity changes abruptly; The process of analyzing the coupling degree index between the sequence and the current value sequence in the multidimensional sequence set is as follows: The coupling degree index is used to quantify the correlation between a one-dimensional sequence and a current value sequence. The calculation process is as follows: It is understandable that a one-dimensional sequence represents any one of the sequences in a multi-dimensional sequence group; The one-dimensional sequence is [x1, x2, ..., x i The current value sequence is [y1, y2, ... y]. i ]; Where i represents the data collection time point; The average value of the one-dimensional sequence is obtained by averaging the one-dimensional sequence, and the average value of the current value sequence is obtained by averaging the current value sequence simultaneously. Obtain the maximum and minimum values ​​of the one-dimensional sequence, and then compare the difference between the maximum and minimum values ​​with the average value of the one-dimensional sequence to obtain the sequence bias of the one-dimensional sequence. The maximum and minimum values ​​of the current value sequence are acquired synchronously. The difference between the maximum and minimum values ​​of the current value sequence is then compared with the average value of the current value sequence to obtain the sequence deviation of the current value sequence. The correlation deviation value between the one-dimensional sequence and the current value sequence is obtained by subtracting the sequence deviation of the one-dimensional sequence from that of the current value sequence. ; It should be noted that the physical meaning of the correlation deviation value is as follows: the correlation deviation value is calculated by comparing the sequence deviation of the one-dimensional sequence with that of the current value sequence; the sequence deviation of the one-dimensional sequence reflects the degree of dispersion of the one-dimensional sequence, while the sequence deviation of the current value sequence reflects the degree of fluctuation of the current value sequence; specifically, the correlation deviation value quantifies the synchronization consistency between the fluctuations of the one-dimensional sequence and the fluctuations of the current value sequence. The smaller the correlation deviation value, the closer the fluctuation amplitudes of the one-dimensional sequence and the current value sequence are, and the stronger the synchronicity of their changes; conversely, the larger the correlation deviation value, the more significant the difference in fluctuations between the two sequences, and the weaker the synchronicity. The coupling degree between the one-dimensional sequence and the current value sequence at each acquisition time point is calculated based on the obtained correlation deviation value; the coupling degree calculation formula is as follows: ; in, This represents the value of the one-dimensional sequence at acquisition time point i. The current value sequence at acquisition time point i; This indicates the coupling degree between the one-dimensional sequence and the current value sequence at acquisition time point i; The coupling degree between the one-dimensional sequence and the current value sequence at each acquisition time point is averaged to obtain the coupling degree index between the one-dimensional sequence and the current value sequence. Based on the above calculation process of coupling degree index, the coupling degree index of temperature sequence and current value sequence, the coupling degree index of humidity sequence and current value sequence, and the coupling degree index of light intensity sequence and current value sequence are obtained in sequence. The obtained coupling index is compared with the preset coupling threshold; If the coupling index is greater than the preset coupling threshold, it indicates that the one-dimensional sequence and the current value sequence have a preliminary strong coupling relationship. If the coupling index is less than or equal to the preset coupling threshold, it indicates that the one-dimensional sequence and the current value sequence are weakly coupled. Sort the obtained coupling indexes by size and take the maximum value; If the one-dimensional sequence and the current value sequence have a preliminary strong coupling relationship and the coupling degree index is at its maximum value, then it indicates that the one-dimensional sequence and the current value sequence have a strong coupling relationship. If the light intensity sequence and the current value sequence are highly coupled, then it is determined whether there is a delay in the current response when the light intensity changes abruptly. The light intensity sequence is [L1, L2, ... L i ]; where L i This represents the light intensity value at the i-th sampling time point, where i is the sampling time point; First, calculate the change in illumination between two adjacent acquisition time points in the illumination intensity sequence; then integrate the illumination change values ​​into an illumination change sequence ΔL according to the time sequence. ΔL=[ΔL1,ΔL2,...,ΔL i ]; Where, ΔL i This represents the absolute change in light intensity between the i-th acquisition time point and the (i-1)-th acquisition time point; It is understandable that taking absolute values ​​is to uniformly measure the magnitude of changes in light intensity, whether it increases or decreases. The mean μΔL and standard deviation σΔL of the light intensity variation sequence were calculated; where the mean μΔL reflects the average variation range of light intensity, and the standard deviation σΔL reflects the dispersion of light intensity variation. According to the 3σ principle, the normal fluctuation value is defined as T = μΔL + 3 × σΔL; It should be noted that the specific meaning of the 3σ principle is that most data will fall within the range of the mean ± 3 standard deviations; The illumination change value at each acquisition time point is compared with the normal fluctuation value to obtain the illumination mutation index (MI) at each acquisition time point. i ; If MI i When the value is greater than 1, it indicates that the change in illumination at the sampling time Δ point has exceeded the normal fluctuation range, and the sampling time point is determined to be a point of sudden change in illumination. If MI i When the value is less than or equal to 1, it indicates that the change in illumination at that time point is within the normal fluctuation range, and the time point is determined to be a non-abrupt point. Calculate the current mutation index MI at each acquisition time point of the current sequence. i Mark the points where the current value changes abruptly, and the calculation process is as follows: Calculate the current change value at adjacent acquisition time points, and integrate the current change value into a current change sequence ΔY according to the time sequence; ΔY=[ΔY1,ΔY2,...,ΔY i ]; The mean μΔY and standard deviation σΔY of the current change sequence ΔY were calculated based on the current change sequence. The threshold T for significant current change is defined based on the mean μΔY and standard deviation σΔY of the current change sequence ΔY. Y T Y =μΔY+3×σΔY;

[0022] The current change value at each acquisition time point is compared with the current significant change threshold to obtain the current mutation index MI at each acquisition time point. i ; If MI i When the value is greater than 1, it indicates that the current change at the sampling time point has exceeded the normal fluctuation range, and the sampling time point is determined to be a current change point. If MI i When the value is less than or equal to 1, it indicates that the current change at that sampling time point is within the normal fluctuation range, and the sampling time point is determined to be a non-abrupt point. The collection time points of the light change points are arranged in chronological order to obtain the light change sequence; The current mutation points are collected in chronological order to obtain the current mutation sequence; The time delay sequence is obtained by performing a difference operation between the light illumination mutation sequence and the current mutation sequence; Calculate the coefficient of variation of the time-delay sequence; The coefficient of variation is obtained by calculating the ratio of the mean to the standard deviation of the time-delay sequence. If the coefficient of variation of the time delay sequence is below a preset threshold and all values ​​of the time delay sequence are negative; Preferably, the preset threshold is 5%; This indicates that after a sudden change in light intensity, the current value also changes suddenly, but the current response has a significant lag and the difference between each lag time is small, with no obvious fluctuation. The technical solution of this embodiment is as follows: In a harsh environment with high temperature and high humidity, environmental parameters and current data of the photoelectric information conversion component are collected simultaneously; multiple sets of single-dimensional sequences of environmental parameters and current value sequences of current data are constructed according to the collection time sequence, and the environmental parameter sequences are integrated into a multi-dimensional sequence group; this facilitates the correlation between the dynamic relationship between the high temperature and high humidity environmental parameters and the current of the photoelectric information conversion component, providing time-matched multi-dimensional basic data for analyzing the performance of the equipment in harsh environments; based on the multi-dimensional sequence group, the coupling degree index between the sequence and the current value sequence in the multi-dimensional sequence group is analyzed; if the light intensity sequence and the current value sequence have a high coupling relationship, it is determined whether there is a delay in the current response when the light intensity changes abruptly; this can lock in the key influencing factor of light intensity, and by judging the current response delay when it changes abruptly, the dynamic response performance of the equipment under the influence of this factor can be effectively evaluated.

[0023] Example 2: Please refer to Figure 1 As shown in the embodiment of the present invention, a method for optimizing the stability of a photoelectric information conversion component under harsh environments includes: S3: If there is a delay in the current response, perform sensitivity response analysis on the current response to obtain the current response sensitivity; if the current response sensitivity deviates from the expectation, construct a light-current prediction model, and calculate the current adjustment amount in advance by predicting the amplitude of sudden changes in light intensity to achieve pre-regulation of the current. If there is a delay in the current response, then sensitivity response analysis is performed on the current response to obtain the current response sensitivity. The process is as follows: The average delay time of the current response is obtained by averaging the time delay sequence. And the standard deviation of the delay time F is calculated based on the average delay time; Record the light change values ​​at the abrupt light change points, integrate all the light change values ​​and perform mean value processing to obtain the average light intensity between the abrupt light change points; Record the current change value at the current abrupt change point, integrate all current change values ​​and perform average processing to obtain the average current value between the current abrupt change points; The ratio of the average light intensity variable to the average current variable is used to obtain the light-current ratio. The ratio of the light-current ratio to the average delay time of the current response is used to obtain the current response rate R. Based on the current response rate, a sensitivity calculation equation is constructed; the standard deviation of the delay time and the current response rate are input into the sensitivity calculation equation to obtain the current response sensitivity LY; wherein, the sensitivity calculation equation is: ; Where R is the current response rate and F is the standard deviation of the delay time; The calculated current response sensitivity is compared with the preset sensitivity threshold. like Figure 2 As shown, if the current response sensitivity is greater than the preset sensitivity threshold, it means that the current response sensitivity is better under the condition of sudden change in light intensity. If the current response sensitivity is less than or equal to the preset sensitivity threshold, it means that the current response sensitivity is poor under sudden changes in light intensity. It should be noted that the physical meaning of current response sensitivity lies in comprehensively measuring the response performance of current to sudden changes in illumination. Current response sensitivity is calculated from the current response rate and the standard deviation of the delay time. The current response rate reflects how quickly the current changes relative to the change in illumination intensity responds when there is a sudden change in illumination intensity. The standard deviation of the delay time reflects the dispersion of the current response delay time relative to the average delay time when there are multiple sudden changes in illumination intensity, reflecting the magnitude and consistency of the lag in each response. Specifically, current response sensitivity integrates amplitude sensitivity, response speed, and stability, becoming the core physical quantity describing the comprehensive response capability of current to sudden changes in illumination. It should also be noted that the purpose of obtaining the current response sensitivity is to: provide a quantitative basis for performance evaluation and optimization; by comparing it with a preset threshold, it can be directly determined whether the current response meets the standard: exceeding the threshold indicates good overall performance, while below it indicates problems such as slow response, insufficient sensitivity, or large fluctuations; at the same time, it can guide equipment optimization, such as improving circuit speed for excessively long delay times, and reducing interference for large standard deviations. In scenarios such as rapid light control and photovoltaic regulation, it can also assess equipment adaptability and ensure its reliable operation in complex lighting environments; If the current response sensitivity deviates from the expectation, a light-current prediction model is constructed. By predicting the magnitude of sudden changes in light intensity, the current adjustment amount is calculated in advance, and the process of pre-regulating the current is as follows: The process of constructing the illumination-current prediction model is as follows: The module for predicting the magnitude of sudden changes in illumination in the illumination-current prediction model is shown below: Based on the average delay time of the obtained current response The prediction period is set as Each data collection time point; For example, it is necessary to prepare in advance It can predict the trend of light change in seconds and ensure that the current regulation action can take effect synchronously when the light change occurs, thus offsetting the lag effect; Extract the preprocessed light intensity sequence [L1, L2, ... L i According to the forecast period Divide the window into sliding sections, with a window length of [value missing]. , including the past Light intensity data at a given time and the future The interval to be predicted at each time point; For each sliding window, calculate the following three types of feature values: The slope of change W: within the sliding window The slope of the linear fitting of the light intensity at each acquisition time point; Cumulative change ΔL before mutation sum : Sliding window inside front Among these points, the sum of all values ​​where the change in illumination is greater than Q times the normal fluctuation value; Preferably, Q=0.5; Fluctuation value DX: Calculated within the sliding window. At each data collection time point, the illumination mutation index (MI) is... i The ratio of the standard deviation to the mean is used to average the ratio at each collection time point to obtain the fluctuation value DX. If the cumulative change before a certain sliding window abruptly exceeds 0.8T and the fluctuation value is less than 0.3, then the future is determined to be... At each data collection time point, a sudden change in illumination will occur, denoted as "predicted change," and the magnitude of the predicted illumination change ΔL is calculated. pred ; Where ΔL is calculated pred The formula is: ; Where W is the slope of change, ΔL sum为 Cumulative change before the mutation; It is understandable that 0.5 is an adjustment coefficient, which was obtained by those skilled in the art through historical data analysis; Input the slope of change and the cumulative change before the abrupt change into the formula for predicting the magnitude of the light intensity abrupt change to obtain the predicted light intensity abrupt change value. The current regulation module of the illumination-current prediction model is shown below: Based on the predicted abrupt change in light intensity, a formula for predicting current regulation is constructed; the formula for predicting current regulation is as follows: ; Where k is the basic adjustment coefficient, ΔY theo This refers to the current adjustment amount; For example, the mean value μΔL of the illumination change sequence ΔL and the mean value μΔY of the current change sequence ΔY are extracted; the ratio of the mean value μΔL of the illumination change sequence ΔL and the mean value μΔY of the current change sequence ΔY is used to obtain the basic adjustment coefficient k. It should be noted that the physical meaning of the basic adjustment coefficient k is: the average current change caused by a unit change in light intensity, used to quantify the baseline correlation ratio between light intensity and current change; The predicted light intensity abrupt value and the basic regulation coefficient k are input into the current regulation prediction formula, and the current regulation is obtained after calculation. If the module predicts the magnitude of sudden changes in illumination determines the future... If a sudden change in light intensity occurs at a certain data collection time point, the current regulation module will be triggered to predict the current regulation amount and make targeted adjustments to the current. Among them, if the predicted increase in light intensity (ΔL) pred >0), then according to ΔY theo Increase the current; If the predicted decrease in light intensity (ΔL) pred <0), then according to ΔY theo Reduce current; S4: Analyze the current response sensitivity by using light intensity and current data that have been pre-adjusted and meet the standards multiple times, and iteratively optimize the light-current prediction model. Multiple sets of adjusted data were collected and analyzed, and the light-current prediction model was iteratively optimized based on the analysis results. After the pre-adjustment strategy was implemented, multiple sets of light intensity and current data were collected. The collected data on light intensity and current were preprocessed. Based on the preprocessed multiple sets of light intensity and current data, the current response sensitivity was calculated using a unified sensitivity calculation equation. If the current response sensitivity of each set of light intensity and current data is greater than the preset sensitivity threshold, and the standard deviation of the current response sensitivity of multiple sets of light intensity and current data is less than 5%, then the current sensitivity is deemed to meet the standard after the adjustment strategy is implemented; otherwise, the current sensitivity is deemed not to meet the standard after the adjustment strategy is implemented. If the current sensitivity is determined to be up to standard, iterative optimization is performed by accumulating multiple sets of light intensity and current data to continuously improve stability and accuracy. Specifically: Based on multiple sets of light intensity and current data, the average light intensity change and the average current change are used to recalculate and calibrate the basic adjustment coefficient k, so that k is closer to the actual correlation law of long-term operation. The feature values ​​(including the slope W and the cumulative change ΔL before the mutation) in the module for predicting the magnitude of sudden changes in illumination are continuously updated using multiple sets of light intensity and current data. sum The statistical distribution of the fluctuation value (DX) makes the predicted light intensity change amplitude more consistent with the actual environmental changes. If the current sensitivity is determined to be substandard, the solution improvement process will be initiated. Check the data acquisition environment: verify the sensor accuracy, determine whether the time synchronization accuracy is still less than 10 milliseconds, and whether the sampling rate is still 1 time / second. If the above problems occur, calibrate the sensor. Illumination prediction optimization: The module for predicting the magnitude of sudden changes in illumination is optimized by changing the sliding window length from a fixed value to a dynamic value, adjusting it according to the standard deviation of the delay time F, calculating the Euclidean distance between the sliding window length and the standard deviation of the delay time, and making dynamic adjustments based on the Euclidean distance; Long-term degradation compensation: Based on equipment operating time data, establish a model for the degradation of current response sensitivity as the equipment ages, preset the compensation amount in advance, and delay performance degradation; Regularly (e.g., weekly) assess equipment performance and plot current response sensitivity trends; If the sensitivity continuously decreases or fluctuates abnormally, the solution improvement process will be automatically triggered for iterative optimization. Regularly review iteration logs, summarize parameter optimization trends, predict performance degradation risks in advance, and achieve proactive optimization; The technical solution of this embodiment is as follows: If there is a delay in the current response, sensitivity response analysis is performed on the current response to obtain the current response sensitivity; if the current response sensitivity deviates from the expectation, an illumination-current prediction model is constructed, and the current adjustment amount is calculated in advance by predicting the amplitude of sudden changes in illumination, thereby achieving pre-adjustment of the current; this can specifically solve the problem of current response delay, and when the sensitivity deviates from the expectation, the adjustment amount is calculated in advance by the illumination-current prediction model to achieve pre-adjustment, effectively ensuring the current stability and operating performance of the equipment; multiple sets of data after adjustment are collected and analyzed, and the illumination-current prediction model is iteratively optimized based on the analysis results; through iterative optimization, the illumination-current prediction model is made to better fit the actual adjustment data, continuously improving the pre-adjustment accuracy and ensuring stable operation of the equipment.

[0024] Example 3: Please refer to Figure 3 As shown in the embodiment of the present invention, a stability optimization system for a photoelectric information conversion component under harsh environments includes the following modules: Data acquisition module: Collects environmental parameters and current data of photoelectric information conversion components; constructs multiple sets of one-dimensional sequences of environmental parameters and current value sequences of current data according to the acquisition time sequence, and integrates multiple sets of one-dimensional sequences into a multi-dimensional sequence group; Change Analysis Module: Analyzes the coupling degree index between the single-dimensional sequence and the current value sequence in the multi-dimensional sequence group. If the coupling degree index shows that the light intensity sequence and the current value sequence of the current data contained in the single-dimensional sequence have a high coupling relationship, then analyzes whether there is a delay in the current response when the light intensity changes abruptly. Current regulation module: If there is a delay in current response and the current response sensitivity deviates from the expectation, a light-current prediction model is constructed, the magnitude of sudden changes in light intensity is predicted, the current regulation amount is calculated, and the current is pre-regulated. Verification and optimization module: Iterative optimization of the light-current prediction model is performed using multiple sets of pre-adjusted and qualified light intensity and current data.

[0025] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for optimizing the stability of a photoelectric information conversion component under harsh environments, characterized in that: include: Collect environmental parameters and current data of photoelectric information conversion components; Multiple sets of one-dimensional sequences of environmental parameters and current value sequences of current data are constructed according to the acquisition time sequence, and the multiple sets of one-dimensional sequences are integrated into a multi-dimensional sequence group. Analyze the coupling degree index between the single-dimensional sequence and the current value sequence in the multidimensional sequence group. If the coupling degree index shows that the light intensity sequence and the current value sequence of the current data contained in the single-dimensional sequence have a high coupling relationship, then analyze whether there is a delay in the current response when the light intensity changes abruptly. If there is a delay in the current response and the current response sensitivity deviates from the expectation, then an illumination-current prediction model is constructed, and the amplitude of the illumination change is predicted to calculate the current regulation amount and realize the pre-regulation of the current. The illumination-current prediction model was iteratively optimized using multiple sets of pre-adjusted and compliant light intensity and current data.

2. The method for optimizing the stability of a photoelectric information conversion component under harsh environments according to claim 1, characterized in that: The process of obtaining the coupling degree index is as follows: Collect multiple sets of environmental parameters in the environment where the photoelectric information conversion component equipment is located, and construct a single-dimensional sequence corresponding to the multiple sets of environmental parameters; Obtain the correlation deviation between the one-dimensional sequence and the current value sequence, and construct a coupling degree calculation formula based on the correlation deviation. The coupling degree between the one-dimensional sequence and the current value sequence at each acquisition time point is obtained by using the coupling degree calculation formula. The coupling degree of each collection point is averaged to obtain the coupling degree index. If the coupling index is greater than the preset coupling threshold, it indicates that the one-dimensional sequence and the current value sequence have a preliminary strong coupling relationship. The obtained coupling indexes are sorted in descending order, and the single-dimensional sequence corresponding to the maximum value of the coupling index is extracted. If the one-dimensional sequence and the current value sequence have a preliminary strong coupling relationship and the one-dimensional sequence is the sequence with the maximum coupling index, then it indicates that the one-dimensional sequence and the current value sequence have a strong coupling relationship.

3. The method for optimizing the stability of a photoelectric information conversion component under harsh environments according to claim 2, characterized in that: The method for obtaining the correlation deviation value is as follows: The average value of the one-dimensional sequence is obtained by averaging the one-dimensional sequence, and the average value of the current value sequence is obtained by averaging the current value sequence. Obtain the maximum and minimum values ​​of the one-dimensional sequence, and then compare the difference between the maximum and minimum values ​​with the average value of the one-dimensional sequence to obtain the sequence bias of the one-dimensional sequence. Obtain the maximum and minimum values ​​of the current value sequence, then take the difference between the maximum and minimum values ​​and compare it with the average value of the current value sequence to obtain the sequence deviation of the current value sequence. The correlation deviation value between the one-dimensional sequence and the current value sequence is obtained by subtracting the sequence deviation of the one-dimensional sequence from that of the current value sequence.

4. The stability optimization method for a photoelectric information conversion component under harsh environments according to claim 1, characterized in that: The process of analyzing whether there is a delay in the current response is as follows: Acquire the light intensity sequence and current value sequence, including the light intensity change value and current change value at each acquisition time point; The values ​​of light change and current change are integrated into light change sequence and current change sequence; The normal fluctuation values ​​of the illumination change sequence and the threshold for significant current changes were obtained respectively. The light change value is compared with the normal fluctuation value of the light change sequence to obtain the light change abruptness index. The current mutation index is obtained by comparing the current change value with the threshold of significant current change in the current change sequence. Based on the obtained light and current abrupt change indices, abrupt change analysis was performed, and the collection points were marked as light abrupt change points and current abrupt change points. The light and current abrupt change points were integrated into light abrupt change sequences and current abrupt change sequences according to the acquisition time. The time delay sequence is obtained based on the light illumination mutation sequence and the current mutation sequence, and the coefficient of variation of the time delay sequence is calculated. Determine whether there is a significant lag in the current response based on the time delay sequence and the coefficient of variation of the time delay sequence.

5. The stability optimization method for a photoelectric information conversion component under harsh environments according to claim 4, characterized in that: The process of obtaining the normal fluctuation value and the threshold for significant current change is as follows: The mean and standard deviation of the illumination variation sequence were calculated based on the illumination variation sequence. Normal fluctuation values ​​are defined based on the 3σ principle and the mean and standard deviation of the illumination variation sequence; The mean and standard deviation of the current change sequence are calculated based on the current change sequence. The threshold for significant current change is defined based on the 3σ principle, as well as the mean and standard deviation of the current change sequence.

6. The method for optimizing the stability of a photoelectric information conversion component under harsh environments according to claim 1, characterized in that: The process of performing current response sensitivity analysis is as follows: The average delay time of the current response is obtained by averaging the time delay sequence. And the standard deviation of the delay time is calculated based on the average delay time; The light intensity changes at all abrupt light change points are averaged to obtain the average light intensity change between abrupt light change points. By integrating the current change values ​​at all current abrupt points, the average current change value between current abrupt points is obtained; The ratio of the average light intensity variable to the average current variable is used to obtain the light-current ratio. The ratio of the light-current ratio to the average current response delay time is used to obtain the current response rate. The current response sensitivity is obtained by comparing the current response rate with the standard deviation of the delay time.

7. The method for optimizing the stability of a photoelectric information conversion component under harsh environments according to claim 1, characterized in that: The process of predicting the magnitude of sudden changes in illumination is as follows: Average delay time based on current response Divide the sliding window into ; Obtain the slope of change within the sliding window, the cumulative change before the abrupt change, and the fluctuation value; and construct an equation to predict the magnitude of the abrupt change in illumination. The slope of change within the sliding window, the cumulative change before the abrupt change, and the fluctuation value are input into the equation for predicting the magnitude of the light intensity abrupt change to obtain the predicted light intensity abrupt change value.

8. The stability optimization method for a photoelectric information conversion component under harsh environments according to claim 7, characterized in that: The method for obtaining the slope of change, the cumulative change before the abrupt change, and the fluctuation value within the sliding window is as follows: Slope of change: Calculate the slope within the sliding window. The slope of the linear fitting of the light intensity at each acquisition time point; Cumulative change before mutation: The sum of all values ​​within a sliding window whose change in illumination is greater than Q times the normal fluctuation value; Where Q is a preset multiple; Fluctuation value: Calculate the ratio of the standard deviation to the mean of the illumination mutation index at each collection time point within the sliding window, and average the ratio at each collection time point to obtain the fluctuation value.

9. The stability optimization method for a photoelectric information conversion component under harsh environments according to claim 1, characterized in that: The process of calculating the current adjustment amount and realizing the pre-adjustment is as follows: Extract the mean values ​​of the illumination change sequence and the current change sequence; The basic adjustment coefficient is obtained by comparing the mean of the illumination change sequence with the mean of the current change sequence. A formula for predicting current regulation is constructed based on the predicted amplitude of sudden changes in light intensity and the basic regulation coefficient. The predicted light intensity abrupt change value and the basic regulation coefficient are input into the current regulation prediction formula to obtain the current regulation amount; Develop targeted regulation strategies based on predicted light intensity spikes and current adjustments.

10. The method for optimizing the stability of a photoelectric information conversion component under harsh environments according to claim 1, characterized in that: The iterative optimization process for the illumination-current prediction model is as follows: After the pre-adjustment is implemented, multiple sets of light intensity and current data are collected, and the current response sensitivity is calculated separately. If the current response sensitivity of each set of light intensity and current data meets the requirements, it means that the current sensitivity meets the standard. Based on multiple sets of light intensity and current data, the basic adjustment coefficients of the light-current prediction model were recalculated and calibrated using the mean light intensity variation and the mean current variation.

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