Reliability acceleration test method and system for metasurface grating in high-temperature and high-humidity environment

Abstract

The invention discloses an accelerated reliability test method and system for a metasurface grating in a high-temperature and high-humidity environment, and belongs to the technical field of grating reliability test.The method specifically comprises the steps that initial performance characterization is conducted on a metasurface grating sample, and parameter data of the metasurface grating sample are obtained; placing the metasurface grating sample in a multi-stress coupling loading device, applying a high-temperature, high-humidity and periodic mechanical stress coupling load, carrying out an acceleration test, and determining the stress of the metasurface grating sample according to the optical performance parameter, the structure parameter, the interface stress parameter and the environmental stress parameter of the metasurface grating sample monitored in real time in the loading process. A multi-dimensional failure feature database is constructed, critical failure time and critical failure parameters are calculated through multi-model compensation according to a preset failure threshold value, and the reliability life of the metasurface grating in the current environment is predicted through the multi-dimensional failure feature database and a machine learning algorithm; and finally realizing accurate judgment on the critical failure time through a multi-model calculation compensation scheme.

Description

Technical Field

[0001] This invention belongs to the field of grating reliability testing technology, specifically a method and system for accelerating reliability testing of metasurface gratings under high temperature and high humidity conditions. Background Technology

[0002] Metasurface gratings, as a novel micro-nano optical device based on subwavelength structure design, have shown broad application prospects in fields such as optical communication, biosensing, and imaging systems through precise control of the light field. However, traditional reliability testing methods have certain limitations, including: applying only a single stress, which cannot simulate the coupling effect of temperature-humidity-mechanical stress in the actual environment; and difficulty in capturing the critical failure state.

[0003] Under extreme conditions, such as high temperature, high humidity, and periodic mechanical stress, the performance of metasurface grating samples degrades rapidly. Existing technologies have the following problems: they ignore the combined effect of multiple environmental parameters under extreme conditions; and there are gaps in the data acquisition interval under rapid degradation, making it difficult to accurately determine the critical failure time and capture the failure critical point in the rapid degradation stage. Therefore, there is an urgent need for a reliability acceleration testing method to solve the above problems. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention proposes a method and system for accelerated reliability testing of metasurface gratings under high temperature and high humidity environments. By constructing a multi-dimensional failure feature database through real-time monitoring and multi-dimensional data acquisition, and using algorithms such as data interpolation and prediction compensation, the failure time can be accurately determined, thereby achieving accelerated aging and reliability assessment of metasurface gratings under extreme environments.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] Accelerated reliability testing methods for metasurface gratings under high temperature and high humidity environments include:

[0007] Initial performance characterization of metasurface grating samples was performed to obtain their optical parameters, structural parameters, and interface performance parameters.

[0008] The metasurface grating sample was placed in a multi-stress coupling loading device, and coupled loads of preset temperature, humidity and periodic mechanical stress were applied to conduct accelerated testing.

[0009] Based on the optical performance parameters, structural parameters, interface stress parameters and environmental stress parameters of the metasurface grating sample monitored in real time during the loading process, a multi-dimensional failure feature database is constructed. Based on the preset failure threshold, the critical failure time and critical failure parameters are calculated using multi-model compensation.

[0010] Using the multi-dimensional failure feature database and machine learning algorithm, the reliability lifetime of metasurface gratings under the current environment is predicted.

[0011] Specifically, the step of placing the metasurface grating sample in a multi-stress coupling loading device and applying coupled loads of preset temperature, humidity, and periodic mechanical stress for accelerated testing includes:

[0012] A multi-stress coupling loading device was constructed to simultaneously control temperature, humidity, and mechanical stress, and the metasurface grating sample was mounted on a dedicated sample holder;

[0013] Pre-set the initial parameters for temperature, humidity, and mechanical stress, and then apply the load;

[0014] Preset temperature, humidity, and periodic mechanical stress are applied to the metasurface grating sample for accelerated testing. During the accelerated testing, various environmental parameters and the state of the metasurface grating sample are automatically recorded.

[0015] Specifically, based on the optical performance parameters, structural parameters, interface stress parameters, and environmental stress parameters of the metasurface grating sample monitored in real time during the loading process, a multi-dimensional failure feature database is constructed. According to a preset failure threshold, the critical failure time and critical failure parameters are calculated using multi-model compensation, including:

[0016] Using timestamps as indexes, abnormal data in the optical performance parameters, structural parameters, interface stress parameters, and environmental stress parameters of metasurface grating samples are cleaned and repaired, and then constructed into a multi-dimensional table.

[0017] Extract the features of parameters from the multi-dimensional table and construct a multi-dimensional failure feature database;

[0018] Based on the preset failure threshold, the critical failure time and critical failure parameters are calculated using multi-model compensation.

[0019] Specifically, the step of calculating the critical failure time and critical failure parameters using multi-model compensation based on a preset failure threshold includes:

[0020] Based on the initial performance parameters of the metasurface grating sample, and combined with the applied preset temperature and humidity environment, a multi-parameter coupling threshold is set.

[0021] Based on a multi-dimensional failure feature database, a weighted average method is used to calculate the comprehensive failure degree. The parameter weights are adjusted according to environmental stress to obtain the real-time failure degree of the metasurface grating sample.

[0022] Construct an array from any two consecutive real-time failure values, filter all arrays, and remove arrays whose values ​​are all greater than or equal to or less than or equal to the multi-parameter coupling threshold; retain arrays whose multi-parameter coupling threshold is within the array range, and set the number of retained arrays to n;

[0023] For the retained n arrays, the failure time is calculated using linear interpolation, exponential decay model, and polynomial regression model respectively, resulting in multiple sets of critical failure time values. The differences between any set of critical failure time values ​​are analyzed to obtain a set of difference values. A consistency threshold is set. If the maximum value in a set of difference values ​​is less than or equal to the consistency threshold, the median of any set of critical failure time values ​​is taken as the final critical failure time. If the maximum value in a set of difference values ​​is greater than the consistency threshold, the mean of any set of critical failure time values ​​is taken as the final critical failure time. The final critical failure value and the final critical failure parameter are determined based on the final critical failure time.

[0024] Specifically, the multi-dimensional failure feature database includes: derived parameter features, correlation features, and failure sensitivity features.

[0025] Specifically, the array is in the form of [real-time failure 1, real-time failure 2], and real-time failure 1 and real-time failure 2 are continuously detected data.

[0026] An accelerated reliability testing system for metasurface gratings under high temperature and high humidity conditions is used to implement the aforementioned accelerated reliability testing method for metasurface gratings under high temperature and high humidity conditions. The system includes: a parameter acquisition module, an accelerated testing module, a criticality judgment module, and a lifetime prediction module.

[0027] The parameter acquisition module is used to perform initial performance characterization on the metasurface grating sample and acquire the optical parameters, structural parameters and interface performance parameters of the metasurface grating sample.

[0028] The accelerated testing module is used to place the metasurface grating sample in a multi-stress coupling loading device and apply a coupling load of preset temperature, humidity and periodic mechanical stress to carry out accelerated testing.

[0029] The critical judgment module is used to construct a multi-dimensional failure feature database based on the optical performance parameters, structural parameters, interface stress parameters and environmental stress parameters of the metasurface grating sample monitored in real time during the loading process, and to calculate the critical failure time and critical failure parameters using multi-model compensation based on the preset failure threshold.

[0030] The lifetime prediction module is used to predict the reliability lifetime of metasurface gratings under the current environment by utilizing the multi-dimensional failure feature database and machine learning algorithm.

[0031] Specifically, the accelerated testing module includes: an installation unit and an accelerated testing unit;

[0032] The mounting unit is used to construct a multi-stress coupling loading device that simultaneously controls temperature, humidity and mechanical stress, and to mount the metasurface grating sample on a special sample holder and apply load.

[0033] The accelerated testing unit is used to perform accelerated testing on the metasurface grating sample and record various environmental parameters and the state of the metasurface grating sample.

[0034] Specifically, the critical judgment module includes: a multi-dimensional table construction unit, a feature extraction unit, and a critical failure calculation unit;

[0035] The multi-dimensional table construction unit is used to clean and repair abnormal data in the optical performance parameters, structural parameters, interface stress parameters and environmental stress parameters of the metasurface grating sample using timestamps as indexes, and construct a multi-dimensional table.

[0036] The feature extraction unit is used to extract features of parameters in a multi-dimensional table and construct a multi-dimensional failure feature database.

[0037] The critical failure calculation unit is used to calculate the critical failure time and critical failure parameters using multi-model compensation based on a preset failure threshold.

[0038] Compared with the prior art, the beneficial effects of the present invention are:

[0039] This invention proposes an accelerated reliability testing method for metasurface gratings under high temperature and high humidity environments. By real-time monitoring and acquisition of multidimensional response data, derived parameters, correlations, and failure-sensitive features are extracted to construct a multidimensional failure feature database. Multi-model compensation is introduced, and the prediction results are fused using multi-model compensation to accurately capture the failure critical point in the rapid decay stage, achieving dynamic prediction of critical failure time and reliability lifetime. This method overcomes the limitations of traditional single-stress, single-threshold testing methods, effectively revealing complex degradation paths under multi-stress coupling, and improving the reliability assessment accuracy, lifetime prediction accuracy, and failure identification response sensitivity of metasurface grating devices in complex environments. It possesses good adaptability and widespread application value. Attached Figure Description

[0040] Figure 1 Flowchart of the reliability acceleration testing method for metasurface gratings under high temperature and high humidity conditions provided by the present invention;

[0041] Figure 2 The flowchart for calculating the critical failure time provided by this invention;

[0042] Figure 3This is a schematic diagram of data compensation calculation provided by the present invention;

[0043] Figure 4 This invention provides an architecture diagram for an accelerated reliability testing system for metasurface gratings under high temperature and high humidity conditions. Detailed Implementation

[0044] The present application will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present application, but do not limit the present application in any way. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application. These all fall within the protection scope of the present application.

[0045] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0046] It should be noted that, unless there is a conflict, the various features in the embodiments of this application can be combined with each other, all of which are within the protection scope of this application. Furthermore, although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than the module division in the device or the order in the flowchart. In addition, the terms "first," "second," and "third" used in this application do not limit the data or execution order, but only distinguish identical or similar items with essentially the same function and effect.

[0047] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The term "and / or" as used in this specification includes any and all combinations of one or more of the associated listed items.

[0048] Example 1:

[0049] Please see Figures 1-3 The present invention provides an embodiment of an accelerated reliability testing method for metasurface gratings under high temperature and high humidity conditions, comprising:

[0050] Step S1: Perform initial performance characterization on the metasurface grating sample to obtain the optical parameters, structural parameters and interface performance parameters of the metasurface grating sample.

[0051] In this embodiment, before characterization, the metasurface grating sample is first thoroughly cleaned to remove dust, oil, and other impurities from the surface. Common cleaning methods include ultrasonic cleaning, solvent cleaning, and drying to ensure that the sample surface remains clean and uncontaminated, thereby guaranteeing the accuracy of the test data and avoiding errors caused by surface contamination.

[0052] Specifically, representative metasurface grating samples were selected, and the following characterization operations were performed sequentially: optical parameter measurement, using a variable-angle ellipsometry to measure the reflectance, transmittance, and extinction coefficient of the samples in the visible to near-infrared bands, and calculating their effective refractive index and dispersion characteristics; structural parameter extraction, using scanning electron microscopy or atomic force microscopy to image and reconstruct the periodic structure of the sample surface, obtaining key structural parameters such as its period, groove depth, groove width, fill factor, and surface roughness; and interface performance parameter evaluation, using nanoindentation and scratch testing techniques to quantitatively evaluate the adhesion between the metasurface and the substrate.

[0053] The optical, structural, and interface performance parameters obtained through the above methods constitute a zero-time-point state reference before high-temperature and high-humidity coupling loading. On the one hand, this data is used for parameter deviation calculation and trend modeling in subsequent failure identification; on the other hand, by comparing the parameter changes before and after loading, the influence path of coupling stress on the metasurface grating performance can be understood.

[0054] Step S2: Place the metasurface grating sample in a multi-stress coupling loading device and apply a coupling load of preset temperature, humidity and periodic mechanical stress to conduct accelerated testing; wherein, the preset temperature and humidity are the high temperature and high humidity environment required for testing, which shall be set by those skilled in the art according to the actual situation.

[0055] The specific steps of step S2 are as follows:

[0056] Step S201: Construct a multi-stress coupling loading device that simultaneously controls temperature, humidity and mechanical stress, and mount the metasurface grating sample on a dedicated sample holder.

[0057] In this embodiment, the multi-stress coupling loading device includes a temperature control module, a humidity control module, a vibration loading module, and a sample mounting structure. By constructing the above device and the sample mounting method, the coordinated loading of three types of environmental stresses can be achieved within a single platform, maintaining the spatial matching between the stress application area and the grating structure.

[0058] Step S202: Pre-set the initial parameters for high temperature, high humidity and mechanical stress, and then apply the load.

[0059] Step S203: Apply high temperature and high humidity environment and predetermined periodic mechanical stress to the metasurface grating sample for accelerated testing. During the accelerated testing process, automatically record various environmental parameters and the state of the metasurface grating sample.

[0060] In this embodiment, the following data are collected in real time during the test using a high-precision sensor array: environmental stress parameters such as temperature, humidity, applied stress, and stress frequency, as well as structural response parameters such as reflectivity, phase delay, diffraction efficiency, grating structure deformation, and interface resistance.

[0061] The benefits of this step are as follows: Through the above-mentioned accelerated testing method, not only can the degradation path of metasurface gratings in actual service environment be quickly induced, but also the key parameters can be tracked throughout the process through real-time data acquisition. Compared with traditional high temperature and high humidity aging tests, this scheme can locate failure trends earlier and more accurately, significantly improving the accuracy of reliability prediction.

[0062] Step S3: Based on the optical performance parameters, structural parameters, interface stress parameters and environmental stress parameters of the metasurface grating sample monitored in real time during the loading process, a multi-dimensional failure feature database is constructed. According to the preset failure threshold, the critical failure time and critical failure parameters are calculated using multi-model compensation.

[0063] The specific steps of step S3 are as follows:

[0064] Step S301: Using timestamps as indexes, clean and repair abnormal data in the optical performance parameters, structural parameters, interface stress parameters, and environmental stress parameters of the metasurface grating sample, and construct a multi-dimensional table.

[0065] In this embodiment, the abnormal data cleaning and repair includes: using digital filtering (such as moving average, Kalman filtering, etc.) to remove sensor noise, ensuring data smoothness and avoiding misjudgments caused by environmental noise; uniformly correcting the data of each channel, such as calibrating temperature and humidity sensors, to reduce the impact of instrument errors on the overall data consistency; and synchronizing the data from different modules (optical performance, structure, interface stress, environmental stress) in time, and merging the multidimensional data into a whole data record based on the timestamp.

[0066] The multidimensional table includes: timestamps, optical performance parameters (such as diffraction efficiency, transmittance, phase information), structural parameters (such as surface morphology images, nanoscale, roughness indicators), interfacial stress parameters (such as interfacial adhesion, strain values, chemical composition changes), and environmental stress parameters (temperature, humidity, vibration amplitude, frequency).

[0067] Step S302: Extract the features of the parameters in the multi-dimensional table, including: derived parameter features, correlation features and failure sensitivity features, and construct a multi-dimensional failure feature database.

[0068] In this embodiment, key features of degradation rate, cumulative damage and stress response are extracted by mathematical transformation of the raw parameters monitored in real time. The features also include time-series features and periodic features.

[0069] In constructing a multi-dimensional failure feature database, the parameters in the original data table are first statistically analyzed in chronological order. Derived parameter characteristics are calculated using indicators such as the mean, variance, and instantaneous rate of change of multiple sampled data. These secondary indicators reflect the inherent trend of parameter evolution under experimental conditions. Furthermore, the presence of abnormal deviations is determined by comparing historical data curves. Secondly, the correlations between parameters are cross-referenced, using statistical measures such as correlation coefficients and covariance to describe the strength and direction of the interaction between temperature, humidity, mechanical stress, and sample response in textual form. For failure-sensitive features, signals showing significant fluctuations or inflection points near the critical failure point are identified based on predefined thresholds and gradient changes. Through the above description, the derived parameters, correlated features, and failure-sensitive features together constitute a multi-dimensional failure feature database reflecting the entire lifecycle behavior of the sample.

[0070] Step S303: Calculate the critical failure time and critical failure parameters using multi-model compensation based on the preset failure threshold.

[0071] like Figure 2 As shown, the specific steps of step S303 include:

[0072] Step S3031: Based on the initial performance parameters of the metasurface grating sample and the high temperature and high humidity environment, set the multi-parameter coupling threshold.

[0073] In this embodiment, the setting of the multi-parameter coupling threshold is based on the variation trend of the performance parameters of the metasurface grating sample in the stress field and the empirical distribution of historical failure samples. Specifically, firstly, by statistically analyzing the degradation behavior of multiple metasurface grating samples under different environmental stresses, the variation range of each key performance index is quantified, and the critical mode before failure is identified. Then, the sample performance parameters in the initial state are used as a reference, and their sensitivity parameters are weighted under high temperature and high humidity environment. The weighting weight is determined according to the degree of influence of the parameter on functionality. For example, optical attenuation is given a higher weight, while small periodic changes are given a secondary weight.

[0074] It should be noted that the threshold is not set using a fixed value.

[0075] Step S3032: Based on the multi-dimensional failure feature database, the weighted average method is used to calculate the comprehensive failure degree. The parameter weights are adjusted according to the environmental stress to obtain the real-time failure degree of the metasurface grating sample.

[0076] Step S3033: Construct an array from any two consecutive real-time failure values, filter all arrays, remove arrays whose values ​​are all greater than or equal to or less than or equal to the multi-parameter coupling threshold; retain arrays whose multi-parameter coupling threshold is within the array range, and set the number of retained arrays to n.

[0077] In this embodiment, the real-time failure degree sequences sorted by time are paired up. For each array, it is determined whether two values ​​are on the same side of the multi-parameter coupling threshold, i.e., both are greater than or equal to, or both are less than or equal to. If so, it means that no critical transition has occurred in that time period and the array is removed. Only those arrays that cross the multi-parameter coupling threshold are retained, i.e., one value is above the threshold and the other value is below the threshold. This indicates that the real-time failure degree has transitioned from a non-failure state to a failure state in the time interval corresponding to the array. This type of array constitutes the input window for subsequent interpolation calculation of the critical failure time.

[0078] The array is in the form of [real-time failure degree 1, real-time failure degree 2], and real-time failure degree 1 and real-time failure degree 2 are continuously detected data. At the same time, the failure time corresponding to real-time failure degree 1 and real-time failure degree 2 is detected. The critical failure time is calculated by using the correlation between time and real-time failure degree.

[0079] like Figure 3 As shown, in step S3034: For the retained n arrays, the failure time is calculated using linear interpolation, exponential decay model and polynomial regression model respectively to obtain multiple sets of critical failure time values. The differences of any set of critical failure time values ​​are analyzed to obtain a set of difference values. A consistency threshold is set. If the maximum value in a set of difference values ​​is less than or equal to the consistency threshold, the median of any set of critical failure time values ​​is taken as the final critical failure time. If the maximum value in a set of difference values ​​is greater than the consistency threshold, the mean of any set of critical failure time values ​​is taken as the final critical failure time. The final critical failure value and the final critical failure parameter are determined based on the final critical failure time.

[0080] Specifically, any set of critical failure time values ​​is set as [s1, s2, s3], and a set of difference values ​​is set as [|s1-s2|,|s2-s3|,|s3-s1|]. |·| represents the absolute value. s1, s2, and s3 are the critical failure time values ​​calculated using linear interpolation, exponential decay model, and polynomial regression model, respectively. The consistency threshold is set to 10% × the current test duration, which is the maximum test time in the corresponding array.

[0081] Figure 3 The array in the model is the retained array. Multiple arrays are used to calculate the critical failure value through different single-model methods. Multiple critical failure values ​​are weighted and coupled to obtain the final critical failure value. It should be noted that the final critical failure value is not equal to the multi-parameter coupling threshold, but only infinitely close to the multi-parameter coupling threshold.

[0082] By using multi-model weighted calculation, the impact of single-model errors can be reduced, and the stability and accuracy of predicting the failure time in the rapid decay stage can be improved.

[0083] The benefits of this step are as follows: By integrating initial performance parameters, environmental stress levels, and multi-dimensional monitoring data, a multi-parameter coupled threshold model is constructed. Based on failure degree weighted calculation and interval screening, the critical failure transition segment is accurately identified. Multi-model weighted parallel prediction is introduced, and the prediction results are compensated and fused using difference analysis and consistency judgment mechanisms. This effectively avoids the sensitivity of a single model to local anomalies or nonlinear degradation responses. While ensuring prediction accuracy, the applicability is expanded, making it particularly suitable for scenarios with multiple stress superpositions, complex degradation paths, and a lack of clear single-parameter thresholds. It helps to stably determine the critical failure time and corresponding parameters of metasurface gratings under high temperature and high humidity environments, achieving accurate reliability prediction.

[0084] Step S4: Using the multi-dimensional failure feature database and machine learning algorithm, predict the reliability lifetime of the metasurface grating under the current environment.

[0085] In this embodiment, the multi-dimensional failure feature database is first divided into sample sets. The entire degradation process of historical metasurface grating samples is constructed into multiple sets of labeled time-series input samples. Each set of samples contains feature evolution trajectories and corresponding real failure times as supervision labels. Then, a suitable machine learning model, such as a tree-based GBDT model or an ensemble method (such as XGBoost), is selected to train the features of the samples. During the training process, the model will automatically identify the nonlinear mapping relationship between each feature and the lifetime, and extract the parameter combination that dominates failure under a specific stress path.

[0086] During the actual inference phase, the model is input with the monitoring characteristic trajectory of the current metasurface grating sample over a period of time, such as reflectivity, interface stress decay, and structural parameter change rate in the last 12 hours. Based on the parameter-lifetime mapping relationship learned from its history, the model will output the predicted remaining lifetime or estimated failure time of the current metasurface grating sample.

[0087] Example 2:

[0088] Please see Figure 4Another embodiment of the present invention provides a reliability acceleration testing system for metasurface gratings under high temperature and high humidity conditions, comprising: a parameter acquisition module, an acceleration testing module, a criticality judgment module, and a lifetime prediction module;

[0089] The parameter acquisition module is used to perform initial performance characterization on the metasurface grating sample and acquire the optical parameters, structural parameters and interface performance parameters of the metasurface grating sample.

[0090] The accelerated testing module is used to place the metasurface grating sample in a multi-stress coupling loading device and apply coupled loads of high temperature, high humidity and periodic mechanical stress to carry out accelerated testing.

[0091] The critical judgment module is used to construct a multi-dimensional failure feature database based on the optical performance parameters, structural parameters, interface stress parameters and environmental stress parameters of the metasurface grating sample monitored in real time during the loading process, and to calculate the critical failure time and critical failure parameters using multi-model compensation based on the preset failure threshold.

[0092] The lifetime prediction module is used to predict the reliability lifetime of metasurface gratings under the current environment by utilizing the multi-dimensional failure feature database and machine learning algorithm.

[0093] The accelerated testing module includes: an installation unit and an accelerated testing unit;

[0094] The mounting unit is used to construct a multi-stress coupling loading device that simultaneously controls temperature, humidity and mechanical stress, and to mount the metasurface grating sample on a special sample holder and apply load.

[0095] The accelerated testing unit is used to perform accelerated testing on the metasurface grating sample and record various environmental parameters and the state of the metasurface grating sample.

[0096] The critical judgment module includes: a multi-dimensional table construction unit, a feature extraction unit, and a critical failure calculation unit;

[0097] The multi-dimensional table construction unit is used to clean and repair abnormal data in the optical performance parameters, structural parameters, interface stress parameters and environmental stress parameters of the metasurface grating sample using timestamps as indexes, and construct a multi-dimensional table.

[0098] The feature extraction unit is used to extract features of parameters in a multi-dimensional table and construct a multi-dimensional failure feature database.

[0099] The critical failure calculation unit is used to calculate the critical failure time and critical failure parameters using multi-model compensation based on a preset failure threshold.

[0100] In addition, the parts of the technical solutions provided in the embodiments of this application that are consistent with the implementation principles of the corresponding technical solutions in the prior art have not been described in detail, so as to avoid excessive elaboration.

[0101] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the invention. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for accelerated reliability testing of metasurface gratings under high temperature and high humidity conditions, characterized in that, include: Initial performance characterization of metasurface grating samples was performed to obtain their optical parameters, structural parameters, and interface performance parameters. The metasurface grating sample was placed in a multi-stress coupling loading device, and coupled loads of preset temperature, humidity and periodic mechanical stress were applied to conduct accelerated testing. Based on the optical performance parameters, structural parameters, interface stress parameters and environmental stress parameters of the metasurface grating sample monitored in real time during the loading process, a multi-dimensional failure feature database is constructed. Based on the preset failure threshold, the critical failure time and critical failure parameters are calculated using multi-model compensation. Using the multi-dimensional failure feature database and machine learning algorithm, the reliability lifetime of metasurface gratings under the current environment is predicted.

2. The method for accelerated reliability testing of metasurface gratings under high temperature and high humidity environments as described in claim 1, characterized in that, The step of placing the metasurface grating sample in a multi-stress coupling loading device and applying coupled loads of preset temperature, humidity, and periodic mechanical stress for accelerated testing includes: A multi-stress coupling loading device was constructed to simultaneously control temperature, humidity, and mechanical stress, and the metasurface grating sample was mounted on a dedicated sample holder; Pre-set the initial parameters for temperature, humidity, and mechanical stress, and then apply the load; Preset temperature, humidity, and periodic mechanical stress are applied to the metasurface grating sample for accelerated testing. During the accelerated testing, various environmental parameters and the state of the metasurface grating sample are automatically recorded.

3. The method for accelerated reliability testing of metasurface gratings under high temperature and high humidity conditions as described in claim 1, characterized in that, The process involves constructing a multi-dimensional failure characteristic database based on real-time monitoring of the optical performance parameters, structural parameters, interface stress parameters, and environmental stress parameters of the metasurface grating sample during loading. According to a preset failure threshold, the critical failure time and critical failure parameters are calculated using multi-model compensation, including: Using timestamps as indexes, abnormal data in the optical performance parameters, structural parameters, interface stress parameters, and environmental stress parameters of metasurface grating samples are cleaned and repaired, and then constructed into multi-dimensional tables. Extract the features of parameters from the multi-dimensional table and construct a multi-dimensional failure feature database; Based on the preset failure threshold, the critical failure time and critical failure parameters are calculated using multi-model compensation.

4. The method for accelerated reliability testing of metasurface gratings under high temperature and high humidity conditions as described in claim 3, characterized in that, The step of calculating the critical failure time and critical failure parameters using multi-model compensation based on a preset failure threshold includes: Based on the initial performance parameters of the metasurface grating sample, and combined with the applied preset temperature and humidity environment, a multi-parameter coupling threshold is set. Based on a multi-dimensional failure feature database, a weighted average method is used to calculate the comprehensive failure degree. The parameter weights are adjusted according to environmental stress to obtain the real-time failure degree of the metasurface grating sample. Construct an array from any two consecutive real-time failure values, filter all arrays, and remove arrays whose values ​​are all greater than or equal to or less than or equal to the multi-parameter coupling threshold; retain arrays whose multi-parameter coupling threshold is within the array range, and set the number of retained arrays to n; For the retained n arrays, the failure time is calculated using linear interpolation, exponential decay model, and polynomial regression model respectively, resulting in multiple sets of critical failure time values. The differences between any set of critical failure time values ​​are analyzed to obtain a set of difference values. A consistency threshold is set. If the maximum value in a set of difference values ​​is less than or equal to the consistency threshold, the median of any set of critical failure time values ​​is taken as the final critical failure time. If the maximum value in a set of difference values ​​is greater than the consistency threshold, the mean of any set of critical failure time values ​​is taken as the final critical failure time. The final critical failure value and the final critical failure parameter are determined based on the final critical failure time.

5. The method for accelerated reliability testing of metasurface gratings under high temperature and high humidity conditions as described in claim 3, characterized in that, The multi-dimensional failure feature database includes: derived parameter features, correlation features, and failure sensitivity features.

6. The method for accelerated reliability testing of metasurface gratings under high temperature and high humidity environments as described in claim 4, characterized in that, The array is in the form of [real-time failure 1, real-time failure 2], and real-time failure 1 and real-time failure 2 are continuously detected data.

7. A reliability acceleration testing system for metasurface gratings under high temperature and high humidity environments, used to implement the reliability acceleration testing method for metasurface gratings under high temperature and high humidity environments as described in any one of claims 1-6, characterized in that, include: Parameter acquisition module, accelerated testing module, criticality judgment module, and lifetime prediction module; The parameter acquisition module is used to perform initial performance characterization on the metasurface grating sample and acquire the optical parameters, structural parameters and interface performance parameters of the metasurface grating sample. The accelerated testing module is used to place the metasurface grating sample in a multi-stress coupling loading device and apply a coupling load of preset temperature, humidity and periodic mechanical stress to carry out accelerated testing. The critical judgment module is used to construct a multi-dimensional failure feature database based on the optical performance parameters, structural parameters, interface stress parameters and environmental stress parameters of the metasurface grating sample monitored in real time during the loading process, and to calculate the critical failure time and critical failure parameters using multi-model compensation based on the preset failure threshold. The lifetime prediction module is used to predict the reliability lifetime of metasurface gratings under the current environment by utilizing the multi-dimensional failure feature database and machine learning algorithm.

8. The reliability acceleration testing system for metasurface gratings under high temperature and high humidity environments as described in claim 7, characterized in that, The accelerated testing module includes: an installation unit and an accelerated testing unit; The mounting unit is used to construct a multi-stress coupling loading device that simultaneously controls temperature, humidity and mechanical stress, and to mount the metasurface grating sample on a special sample holder and apply load. The accelerated testing unit is used to perform accelerated testing on the metasurface grating sample and record various environmental parameters and the state of the metasurface grating sample.

9. The reliability acceleration testing system for metasurface gratings under high temperature and high humidity environments as described in claim 8, characterized in that, The critical judgment module includes: a multi-dimensional table construction unit, a feature extraction unit, and a critical failure calculation unit; The multi-dimensional table construction unit is used to clean and repair abnormal data in the optical performance parameters, structural parameters, interface stress parameters and environmental stress parameters of the metasurface grating sample using timestamps as indexes, and construct a multi-dimensional table. The feature extraction unit is used to extract features of parameters in a multi-dimensional table and construct a multi-dimensional failure feature database. The critical failure calculation unit is used to calculate the critical failure time and critical failure parameters using multi-model compensation based on a preset failure threshold.

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