A method and apparatus for evaluating the stability of vacuum ultraviolet deuterium lamp intensity

Abstract

This invention provides a method and apparatus for evaluating the stability of the intensity of a vacuum ultraviolet deuterium lamp, relating to the field of light intensity detection technology. The method includes: guiding ultraviolet light of a target wavelength emitted by a vacuum ultraviolet deuterium lamp to a detection device in a vacuum environment; continuously collecting light intensity data at preset time intervals to obtain a light intensity data sequence; calculating the cumulative offset index, goodness of fit, and peak-to-peak value variation of the target wavelength ultraviolet light based on the light intensity data at each time interval; and determining the stability level of the vacuum ultraviolet deuterium lamp based on the cumulative offset index, goodness of fit, and peak-to-peak value variation according to preset grading rules. A higher stability level indicates greater stability of the target wavelength ultraviolet light emitted by the vacuum ultraviolet deuterium lamp. This invention can intuitively reflect the stability of the light source and provides a standardized and easy-to-operate evaluation framework.

Description

Technical Field

[0001] This invention relates to the field of light intensity detection technology, specifically to a method and apparatus for evaluating the stability of vacuum ultraviolet deuterium lamp light intensity. Background Technology

[0002] Deuterium lamps, as a common ultraviolet light source, are widely used in fields such as spectroscopic analysis instruments, photoelectron spectrometers, and environmental monitoring equipment. Furthermore, the stability of deuterium lamps is particularly important in research where high precision of the light source is required, such as ultraviolet photoelectron spectroscopy (UPS) measurements, fluorescence excitation sources, and material surface analysis.

[0003] However, traditional methods for assessing the stability of deuterium lamp intensity typically rely solely on output power fluctuations at a specific wavelength or within a narrow band, using metrics such as the coefficient of variation (CV) and normalized amplitude (RNI). These metrics primarily focus on short-term or instantaneous fluctuations or changes in light intensity, reflecting only the range of intensity fluctuations at a given moment. They are insufficient for capturing and identifying long-term or periodic attenuation, decreased stability, or other trend-based changes. Therefore, traditional methods cannot comprehensively and accurately assess the stability of deuterium lamp intensity. Summary of the Invention

[0004] This invention provides a method and apparatus for evaluating the stability of vacuum ultraviolet deuterium lamp intensity, aiming to solve the problems existing in the background art. To solve the above-mentioned technical problems, this invention is implemented as follows: In a first aspect, embodiments of the present invention provide a method for evaluating the stability of vacuum ultraviolet deuterium lamp light intensity, comprising: In a vacuum environment, ultraviolet light of the target wavelength emitted by a vacuum ultraviolet deuterium lamp is guided to the detection device; The detection device continuously collects light intensity data at each time point at a preset time interval to obtain a light intensity data sequence; Based on the light intensity data at each moment, the cumulative shift index, goodness of fit, and peak-to-peak value change of the ultraviolet light at the target wavelength are calculated; wherein, the cumulative shift index characterizes the overall drift of the light intensity data sequence relative to the initial light intensity, the goodness of fit characterizes the degree to which the trend of the light intensity data sequence changing over time conforms to the target fitting function, and the peak-to-peak value change characterizes the maximum instantaneous fluctuation amplitude of the light intensity data sequence within the measurement period. According to the preset grading rules, the stability level of the vacuum ultraviolet deuterium lamp is determined based on the cumulative offset index, the goodness of fit, and the peak-to-peak value variation. The higher the stability level, the more stable the ultraviolet light of the target wavelength emitted by the vacuum ultraviolet deuterium lamp is.

[0005] Optionally, based on the light intensity data at each moment, the cumulative shift index of the ultraviolet light at the target wavelength is calculated, including: Using the light intensity data collected at the first moment in the light intensity data sequence as the reference value, the deviation of the light intensity data at each subsequent moment in the light intensity data sequence from the reference value is calculated respectively. Determine the absolute value of the deviation at each moment in the light intensity data sequence, and calculate the sum of the absolute values ​​of the deviation at all moments in the light intensity data sequence; The sum of the absolute values ​​of the deviations at all times in the light intensity data sequence is normalized to obtain the cumulative offset index of the ultraviolet light at the target wavelength.

[0006] Optionally, the sum of the absolute values ​​of the deviations at all times in the light intensity data sequence is normalized to obtain the cumulative shift index of the ultraviolet light at the target wavelength, including: A corresponding weight is assigned to each moment in the light intensity data sequence, wherein the weight of the acquisition moment that is closer to the current time is greater, and the weight is calculated based on the time decay factor; Multiply the absolute value of the deviation at each time step by the corresponding weight to obtain the weighted deviation. Calculate the sum of weighted deviations at all times, and calculate the mean light intensity of all light intensity data in the light intensity data sequence; The total number of light intensity data in the light intensity data sequence is determined, and the cumulative offset index of the ultraviolet light of the target wavelength is calculated based on the sum of the weighted deviations at all times, the total number of light intensity data in the light intensity data sequence, and the average light intensity.

[0007] Optionally, based on the light intensity data at each time moment, the goodness of fit of the ultraviolet light at the target wavelength is calculated, including: Using the acquisition time as the independent variable and the corresponding light intensity data as the dependent variable, the light intensity data sequence is fitted to obtain the target fitting function, which is composed of the predicted value output by the preset fitting model for each acquisition time. Calculate the residual between each light intensity data point and the corresponding predicted value on the target fitting function to obtain the residual of each light intensity data point; Calculate the average light intensity of all light intensity data in the light intensity data sequence; The goodness of fit is calculated based on the residual of each light intensity data point and the difference between each light intensity data point and the mean light intensity.

[0008] Optionally, the light intensity data sequence is fitted with the acquisition time as the independent variable and the corresponding light intensity data as the dependent variable to obtain the target fitting function, including: Calculate information criterion values ​​for multiple fitting models, including linear function models, exponential decay function models, and logarithmic function models. The information criterion values ​​are used to evaluate the complexity and fitting accuracy of the fitting models. The smaller the complexity and the higher the fitting accuracy of the fitting model, the smaller the information criterion value. The fitting model with the smallest information criterion value is determined as the optimal fitting model; Based on the optimal fitting model, the light intensity data sequence is fitted with the acquisition time as the independent variable and the corresponding light intensity data as the dependent variable to obtain the target fitting function.

[0009] Optionally, based on the light intensity data at each moment, the peak-to-peak value variation of the ultraviolet light at the target wavelength is calculated, including: From the light intensity data sequence, determine the maximum light intensity data with the largest value and the minimum light intensity data with the smallest value; Calculate the difference between the maximum light intensity data and the minimum light intensity data; Calculate the average light intensity of all light intensity data in the light intensity data sequence; The peak-to-peak value variation is calculated based on the difference and the average light intensity.

[0010] Optionally, after calculating the peak-to-peak value change, the method further includes: Multiple time windows are determined based on the total number of light intensity data in the light intensity data sequence, the preset window length, and the preset sliding step size; The light intensity data sequence is divided into multiple sub-data segments using the multiple time windows; Calculate the local peak-to-peak value change of each of the multiple sub-data segments, where the local peak-to-peak value change represents the instantaneous fluctuation amplitude of the light intensity data within the sub-data segment; The average fluctuation level is calculated based on the local peak-to-peak changes of each of the multiple sub-data segments. The abnormal fluctuation ratio is calculated based on the number of sub-data segments whose local peak-to-peak value changes exceed a preset fluctuation threshold, and the total number of the multiple sub-data segments. Based on the average fluctuation level and the abnormal fluctuation ratio, a periodic fluctuation value is determined. The larger the periodic fluctuation value, the more obvious the periodic fluctuation of the light intensity data sequence in the time dimension.

[0011] Optionally, the stability level of the vacuum ultraviolet deuterium lamp is determined according to a preset grading rule, based on the cumulative offset index, the goodness of fit, and the peak-to-peak value variation, including: If the cumulative offset index is less than a first preset threshold, the goodness of fit is greater than a second preset threshold, and the peak-to-peak value change is less than a third preset threshold, the stability level of the vacuum ultraviolet deuterium lamp is determined to be level one, and level one indicates that the vacuum ultraviolet deuterium lamp is in a stable working state. If the cumulative offset index is less than the fourth preset threshold, the goodness of fit is greater than the fifth preset threshold, and the peak-to-peak value change is less than the third preset threshold, the stability level of the vacuum ultraviolet deuterium lamp is determined to be level two. Level two indicates that the vacuum ultraviolet deuterium lamp is in a drift working state. Level two is lower than level one. Otherwise, the stability level of the vacuum ultraviolet deuterium lamp is determined to be level three, which indicates that the vacuum ultraviolet deuterium lamp is in an unstable working state, and level three is lower than level two.

[0012] Secondly, embodiments of the present invention provide a stability testing device for vacuum ultraviolet deuterium lamp intensity, applied to the steps of performing the method as described in the first aspect; including: The light source module is used to guide the ultraviolet light of the target wavelength emitted by the vacuum ultraviolet deuterium lamp to the detection device in a vacuum environment; The detection module is used by the detection device to continuously collect light intensity data at each moment at a preset time interval to obtain a light intensity data sequence. The calculation module is used to calculate the cumulative shift index, goodness of fit, and peak-to-peak value change of the ultraviolet light of the target wavelength based on the light intensity data at each moment. The cumulative shift index represents the overall drift of the light intensity data sequence relative to the initial light intensity, the goodness of fit represents the degree to which the trend of the light intensity data sequence changing over time conforms to the target fitting function, and the peak-to-peak value change represents the maximum instantaneous fluctuation amplitude of the light intensity data sequence within the measurement period. The judgment module is used to determine the stability level of the vacuum ultraviolet deuterium lamp based on the cumulative offset index, the goodness of fit, and the peak-to-peak value change according to the preset classification rules. The higher the stability level, the more stable the ultraviolet light of the target wavelength emitted by the vacuum ultraviolet deuterium lamp is.

[0013] Optionally, the computing module includes: The first calculation submodule is used to calculate the deviation of the light intensity data at each subsequent moment in the light intensity data sequence from the reference value, using the light intensity data collected at the first moment in the light intensity data sequence as the reference value. The second calculation submodule is used to determine the absolute value of the deviation at each moment in the light intensity data sequence, and to calculate the sum of the absolute values ​​of the deviation at all moments in the light intensity data sequence. The third calculation submodule is used to normalize the sum of the absolute values ​​of the deviations at all times in the light intensity data sequence to obtain the cumulative offset index of the ultraviolet light of the target wavelength.

[0014] Optionally, the third computing submodule includes: The first calculation unit is used to assign a corresponding weight to each moment in the light intensity data sequence, wherein the weight of the acquisition moment that is closer to the current time is greater, and the weight is calculated based on the time decay factor. The second calculation unit is used to multiply the absolute value of the deviation at each time step by the corresponding weight to obtain the weighted deviation. The third calculation unit is used to calculate the sum of weighted deviations at all times, and to calculate the average light intensity of all light intensity data in the light intensity data sequence. The fourth calculation unit is used to determine the total number of light intensity data in the light intensity data sequence, and to calculate the cumulative offset index of ultraviolet light of the target wavelength based on the sum of the weighted deviations at all times, the total number of light intensity data in the light intensity data sequence, and the average light intensity.

[0015] Optionally, the computing module includes: The fourth calculation submodule is used to fit the light intensity data sequence with the acquisition time as the independent variable and the corresponding light intensity data as the dependent variable to obtain the target fitting function. The target fitting function is composed of the predicted value output by the preset fitting model for each acquisition time. The fifth calculation submodule is used to calculate the residual between each light intensity data and the corresponding predicted value on the target fitting function, so as to obtain the residual of each light intensity data. The sixth calculation submodule is used to calculate the average light intensity of all light intensity data in the light intensity data sequence; The seventh calculation submodule is used to calculate the goodness of fit based on the residual of each light intensity data and the difference between each light intensity data and the mean light intensity.

[0016] Optionally, the fourth computing submodule includes: The fifth calculation unit is used to calculate the information criterion value of multiple fitting models, including linear function models, exponential decay function models and logarithmic function models. The information criterion value is used to evaluate the complexity and fitting accuracy of the fitting model. The smaller the complexity and the higher the fitting accuracy of the fitting model, the smaller the information criterion value. The sixth calculation unit is used to determine the fitting model with the minimum information criterion value as the optimal fitting model; The seventh calculation unit is used to fit the light intensity data sequence based on the optimal fitting model, with the acquisition time as the independent variable and the corresponding light intensity data as the dependent variable, to obtain the target fitting function.

[0017] Optionally, the computing module includes: The eighth calculation submodule is used to determine the maximum light intensity data with the largest value and the minimum light intensity data with the smallest value from the light intensity data sequence; The ninth calculation submodule is used to calculate the difference between the maximum light intensity data and the minimum light intensity data; The tenth calculation submodule is used to calculate the average light intensity of all light intensity data in the light intensity data sequence; The eleventh calculation submodule is used to calculate the peak-to-peak value change based on the difference and the average light intensity.

[0018] Optionally, the device further includes: The first determining module is used to determine multiple time windows based on the total number of light intensity data in the light intensity data sequence, the preset window length, and the preset sliding step size; The segmentation module is used to divide the light intensity data sequence into multiple sub-data segments through the multiple time windows; The first sub-data segment calculation module is used to calculate the local peak-to-peak value change of each of the plurality of sub-data segments, wherein the local peak-to-peak value change represents the instantaneous fluctuation amplitude of the light intensity data within the sub-data segment; The second sub-data segment calculation module is used to calculate the average fluctuation level based on the local peak-to-peak changes of each of the multiple sub-data segments; The third sub-data segment calculation module is used to calculate the abnormal fluctuation ratio based on the number of sub-data segments whose local peak-to-peak value changes exceed a preset fluctuation threshold and the total number of the multiple sub-data segments. The second determining module is used to determine the periodic fluctuation value based on the average fluctuation level and the abnormal fluctuation ratio. The larger the periodic fluctuation value, the more obvious the periodic fluctuation of the light intensity data sequence in the time dimension.

[0019] Optionally, the determination module includes: The first judgment module is used to determine the stability level of the vacuum ultraviolet deuterium lamp as Level 1 when the cumulative offset index is less than a first preset threshold, the goodness of fit is greater than a second preset threshold, and the peak-to-peak value change is less than a third preset threshold. Level 1 indicates that the vacuum ultraviolet deuterium lamp is in a stable working state. The second judgment module is used to determine the stability level of the vacuum ultraviolet deuterium lamp as level two when the cumulative offset index is less than the fourth preset threshold, the goodness of fit is greater than the fifth preset threshold, and the peak-to-peak value change is less than the third preset threshold. Level two indicates that the vacuum ultraviolet deuterium lamp is in a drift working state. Level two is lower than level one. The third judgment module is used to determine that the stability level of the vacuum ultraviolet deuterium lamp is level three if otherwise. Level three indicates that the vacuum ultraviolet deuterium lamp is in an unstable working state, and level three is lower than level two.

[0020] Thirdly, embodiments of the present invention provide an electronic device, including: a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, it implements the steps of a method for evaluating the stability of vacuum ultraviolet deuterium lamp light intensity.

[0021] The technical solutions provided by the embodiments of the present invention bring at least the following beneficial effects: This invention quantifies the overall drift of a light intensity data sequence relative to its initial intensity by calculating a cumulative offset index, thus identifying long-term trends in deuterium lamp intensity, such as attenuation and drift, rather than relying solely on instantaneous fluctuations. This allows the invention to identify and warn of stability issues in deuterium lamps during long-term use, overcoming the limitation of existing methods that are only sensitive to short-term fluctuations. Furthermore, the invention employs a goodness-of-fit index to quantify the degree to which the trend of light intensity data over time conforms to a target fitting function. This not only identifies instantaneous fluctuations in light intensity but also effectively reflects the regular trend of light intensity changes over time, thereby accurately determining whether a systematic decrease or degradation in deuterium lamp intensity has occurred. Furthermore, by combining a peak-to-peak value variation index, the maximum instantaneous fluctuation amplitude of light intensity within the measurement period is evaluated. This comprehensively reflects the light intensity stability of the deuterium lamp, including instantaneous fluctuations and long-term trend changes, avoiding the limitations of focusing only on short-term fluctuations. Finally, based on a grading rule, combining the cumulative offset index, goodness-of-fit, and peak-to-peak value variation, a clear evaluation level for the light intensity stability of vacuum ultraviolet deuterium lamps can be provided. It intuitively reflects the stability of the light source and can be used for comparison between different devices, providing a standardized and easy-to-use evaluation framework. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments of the present invention will be briefly introduced below.

[0023] Figure 1 This is a schematic diagram of the steps of a method for evaluating the stability of vacuum ultraviolet deuterium lamp light intensity according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the optical path of a vacuum ultraviolet deuterium lamp intensity stability testing device proposed in one embodiment of the present invention; Figure 3 This is a schematic diagram of the frame of a vacuum ultraviolet deuterium lamp intensity stability testing device in one embodiment of the present invention; Figure 4 This is a structural block diagram of a vacuum ultraviolet deuterium lamp intensity stability testing device provided in one embodiment of the present invention.

[0024] Explanation of reference numerals in the attached figures: 1. Vacuum ultraviolet deuterium lamp; 2. Ring mirror; 3. Filter; 4. Monochromator concave grating; 5. Reflector; 6. Beam splitter; 7. Detection device; 8. Focusing lens; 9. Sample. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] In related technologies, the light intensity stability of a light source is usually evaluated by the output power fluctuation at a certain wavelength or narrow band. Common evaluation indicators include coefficient of variation (CV) and normalized amplitude (RNI). Although these indicators can reflect the light intensity fluctuation to some extent, they are not good at identifying trend-based attenuation or regular changes. At the same time, most tests rely on manual data analysis and lack real-time feedback mechanisms and repeatability.

[0027] To address the aforementioned issues, the core idea of ​​this invention lies in continuously acquiring ultraviolet light intensity data of the target wavelength emitted by a vacuum ultraviolet deuterium lamp in a vacuum environment, and then comprehensively analyzing this data using multiple indicators to identify the trend of intensity decay and regular changes. Specifically, this invention employs three indicators: cumulative offset index, goodness of fit, and peak-to-peak value variation, to evaluate the overall drift of the intensity data, the trend consistency over time, and the instantaneous fluctuation amplitude, respectively. These comprehensive indicators not only identify short-term fluctuations in deuterium lamp intensity but also effectively capture long-term decay and regular changes, thus providing a more accurate and comprehensive assessment of intensity stability. Furthermore, this invention introduces an automated data analysis and real-time feedback mechanism, avoiding the limitations of traditional manual analysis, improving the efficiency and repeatability of the testing process, and ensuring the stability and reliability of the test results.

[0028] Figure 1This is a schematic diagram illustrating the steps of a method for evaluating the stability of vacuum ultraviolet deuterium lamp intensity according to an embodiment of the present invention, including: Step S11: In a vacuum environment, guide the ultraviolet light of the target wavelength emitted by the vacuum ultraviolet deuterium lamp to the detection device.

[0029] Figure 2 This is a schematic diagram of the optical path of a stability testing device for vacuum ultraviolet deuterium lamp intensity according to one embodiment of the present invention. The following describes the various components in the optical path of the stability testing device for vacuum ultraviolet deuterium lamp intensity upon which this embodiment of the invention depends. The vacuum ultraviolet deuterium lamp 1 serves as the ultraviolet light source; the annular mirror 2 is used for initial collection and guiding of the light beam; the filter 3 filters stray light of non-target wavelengths to improve the signal-to-noise ratio; the monochromator concave grating 4 performs wavelength selection and outputs monochromatic ultraviolet light; the reflector 5 adjusts the direction of the optical path; the beam splitter 6 divides the light beam into two paths, one for light intensity monitoring and the other for transmission to the sample; the detection device 7 includes a sodium salicylate fluorescent screen and a photomultiplier tube (PMT), responsible for converting ultraviolet light into visible light and quantifying the light intensity signal; the focusing lens 8 is used to focus the light beam onto the sample 9, ensuring that the spot size and energy density meet the experimental requirements.

[0030] In the specific implementation of step S11, a vacuum system is used to evacuate the vacuum chamber until it reaches a preset vacuum level, for example, ≤1×10⁻⁶. -4 Pa is used to eliminate the absorption / scattering of vacuum ultraviolet light by air molecules. The pumping system can be a series configuration of a mechanical pump and a molecular pump.

[0031] The vacuum ultraviolet deuterium lamp emits a continuous ultraviolet light spectrum and preheats for 20 minutes to reach a stable working state.

[0032] The guiding device for directing the ultraviolet light emitted by the vacuum ultraviolet deuterium lamp to the target wavelength includes an energy optimization module and a vacuum ultraviolet monochromator. The energy optimization module, located at the deuterium lamp outlet, comprises a condenser lens assembly and optional filters. It focuses the light beam and filters out stray light from non-target wavelengths, improving the signal-to-noise ratio. The vacuum ultraviolet monochromator provides wavelength adjustment, covering 115–400 nm, ensuring the output light is the pure target wavelength λ.

[0033] The detection device is used to detect the intensity of vacuum ultraviolet deuterium lamps. The device consists of a sodium salicylate fluorescent screen and a photomultiplier tube (PMT). The sodium salicylate fluorescent screen converts the vacuum ultraviolet light into visible light, matching the response range of the PMT. The PMT responds to the signal converted by the sodium salicylate fluorescent screen, outputting photon pulse signals, which are quantized and acquired by a pulse counter.

[0034] In practice, the target wavelength λ of the monochromator is set via a control terminal. The monochromator automatically adjusts the angle of the concave grating to output narrowband monochromatic light. The monochromated beam is converted into visible light by a sodium salicylate fluorescent screen and then incident on a photomultiplier tube. The control terminal has automatic calculation and graphical processing capabilities and includes a built-in standardized algorithm module for cumulative offset index, goodness of fit, and peak-to-peak value variation index. Step S12: The detection device continuously collects light intensity data at each time interval to obtain a light intensity data sequence.

[0035] A pulse counter acquires the photomultiplier tube output signal at a fixed frequency (which can be set to 1 Hz), recording one light intensity data point per second. Continuous acquisition should last for ≥30 minutes to ensure coverage of potential short-term fluctuations and long-term drifts in the deuterium lamp (such as thermal equilibrium fluctuations after preheating, power supply noise, etc.). Acquisition should begin after the deuterium lamp has preheated for 20 minutes and entered a stable operating state to avoid unsteady-state interference during the initial heating phase.

[0036] The sampling time is set based on the stability characteristics of the deuterium lamp after preheating, with a preferred sampling time of 30 minutes to fully capture light intensity decay or periodic changes. In the control terminal, the user can set the sampling duration, and the system automatically times the sampling and triggers an end.

[0037] Every moment (i is the sequence index), record the light intensity value Timestamp It is generated synchronously by the internal clock of the control terminal. Data acquisition continues, resulting in a time series. Light intensity data sequence ,in, This represents the total number of sampling points. The output is structured data pairs. The sequence header contains metadata: wavelength. The start and end times of data collection and the average light intensity.

[0038] Step S13: Based on the light intensity data at each moment, calculate the cumulative shift index, goodness of fit, and peak-to-peak value change of the ultraviolet light of the target wavelength; wherein, the cumulative shift index characterizes the overall drift of the light intensity data sequence relative to the initial light intensity, the goodness of fit characterizes the degree to which the trend of the light intensity data sequence changing over time conforms to the target fitting function, and the peak-to-peak value change characterizes the maximum instantaneous fluctuation amplitude of the light intensity data sequence within the measurement period.

[0039] This embodiment performs multidimensional analysis of light intensity data sequences using quantitative indicators. The analysis is based on the light intensity time series acquired in step S12. and time series Calculate the following indicators: The Cumulative Displacement Index (CDI) characterizes the overall drift of a light intensity data sequence relative to its initial light intensity (such as linear decay or continuous shift).

[0040] Goodness of fit ( This is used to evaluate how well the trend of light intensity data sequence changes over time conforms to a target fitting function (such as a linear function).

[0041] Peak-to-peak value variation ( ), used to quantify the maximum instantaneous fluctuation amplitude of the light intensity data sequence within the measurement period.

[0042] In the above-mentioned indicators proposed in this embodiment, the smaller the CDI value, the weaker the overall light intensity drift. The closer the value is to 1, the more significant the linear trend of light intensity change over time (such as continuous decay). The smaller the dimensionless value, the smaller the instantaneous fluctuation amplitude (e.g., weaker power supply noise influence). CDI focuses on the cumulative deviation (overall drift) between the start and end points of the light intensity data sequence. To examine whether the light intensity data sequence conforms to the trend represented by the target fitting function; Capture the extreme differences (instantaneous noise) in the light intensity data sequence. Combining these three factors allows for the identification of stable drift; that is, CDI and... Jointly capture trend drift, It independently reflects instantaneous noise and covers all dimensions of stability evaluation.

[0043] In an optional implementation, step S13 specifically includes steps S131 to S133: Step S131: Using the light intensity data collected at the first moment in the light intensity data sequence as the reference value, calculate the deviation of the light intensity data at each subsequent moment in the light intensity data sequence relative to the reference value.

[0044] Light intensity of the first point in the light intensity data sequence Using the baseline value, calculate the value for each subsequent point. Relative deviation:

[0045] In the formula, The initial light intensity is taken from the first point of the light intensity data sequence and represents the reference benchmark of the "ideal steady state". For the first The light intensity value at each sampling point. This is the deviation value; a positive value indicates an increase in light intensity, while a negative value indicates an decrease.

[0046] The control terminal traverses the light intensity data sequence Parallel computing of all .

[0047] Step S132: Determine the absolute value of the deviation at each moment in the light intensity data sequence, and calculate the sum of the absolute values ​​of the deviation at all moments in the light intensity data sequence.

[0048] Output of step S131 Take the absolute value and sum:

[0049] In the formula, This represents the absolute value of the deviation. Sum This represents the sum of absolute deviations; a larger value indicates a more significant overall drift.

[0050] Real-time calculation using accumulator Sum To optimize efficiency, when In such cases, enable block-based parallel summation (e.g., grouping 1000 points together).

[0051] Step S133: Normalize the sum of the absolute values ​​of the deviations at all times in the light intensity data sequence to obtain the cumulative offset index of the ultraviolet light of the target wavelength.

[0052] Sum of absolute deviations Sum Normalization:

[0053] In the formula, This represents the total number of sampling points (dimensionless). The average light intensity is calculated as follows:

[0054] Considering that the aforementioned Cumulative Displacement Index (CDI) only focuses on the absolute value of the overall drift, this invention proposes to introduce a time decay factor into the CDI calculation, assigning higher weight to recent data through exponential decay weighting. This is because light source performance degradation often begins to manifest in the recent past. To make the CDI more sensitive to changes in the current state and to avoid early stable data masking recent anomalies, in an optional implementation, step S133 specifically includes steps S1331 to S1333: Step S1331: Multiply the absolute value of the deviation at each time point by the corresponding weight to obtain the weighted deviation.

[0055] absolute value of deviation at each time point Multiply by time decay weight The weighted bias is obtained. , that is:

[0056] Among them, time decay weight Defined as:

[0057] In the formula, For the first The time of each sampling point. This is the initial sampling time. As the attenuation factor, The larger the value, the higher the weight of recent time decay; The smaller the value, the more uniform the distribution of time decay weights.

[0058] Time decay factor This reflects the timeliness of the offset; that is, recent offsets have a greater impact on stability than earlier offsets.

[0059] Step S1332: Calculate the sum of weighted deviations at all times, and calculate the mean light intensity of all light intensity data in the light intensity data sequence.

[0060] Sum of weighted biases It can be represented by the following formula:

[0061] A larger value indicates a more significant recent drift.

[0062] As mentioned earlier, the average light intensity It can be represented by the following formula:

[0063] Average light intensity As a normalization benchmark, the influence of absolute brightness is eliminated.

[0064] Step S1333: Determine the total number of light intensity data in the light intensity data sequence, and calculate the cumulative offset index of ultraviolet light of the target wavelength based on the sum of weighted deviations at all times, the total number of light intensity data in the light intensity data sequence, and the average light intensity.

[0065] Sum of weighted biases Normalize and output the cumulative offset exponent. :

[0066] For the improved CDI in this embodiment, when hour, The value remains unchanged; that is, the CDI directly obtained in step S133 and the improved CDI obtained in step S1333 are the same. They are equal under the following circumstances.

[0067] In an optional implementation, step S13 specifically includes steps S134 to S137: Step S134: Using the acquisition time as the independent variable and the corresponding light intensity data as the dependent variable, fit the light intensity data sequence to obtain the target fitting function. The target fitting function is composed of the predicted value output by the preset fitting model for each acquisition time.

[0068] Based on the time of data collection Light intensity data is the independent variable. As the dependent variable, the least squares method is used for fitting. The goal of the least squares method is to minimize the error between the fitted curve and the actual collected data points by optimizing the parameters of the target fitting function. At each acquisition time, the selected fitting model will output the corresponding predicted value, reflecting the theoretical value of the light intensity data at that acquisition time in the target fitting function.

[0069] The fitting model used can be a linear fitting model, and correspondingly, the target fitting function can be a fitted straight line:

[0070] In the formula, The sampling time reflects the cumulative effect over time. The time decay factor, also known as the slope, characterizes the trend of light intensity changing over time. This indicates an increase in light intensity. (Indicates attenuation); Intercept represents the theoretical light intensity at the initial moment. Each is output as the objective fitting function Predicted light intensity value at time .

[0071] Considering that traditional methods rely on a pre-set fitting model, and that the decay of deuterium lamp light may be linear (constant decay), exponential (rapid decay), or logarithmic (drastic initial change followed by gradual decay), in order to dynamically select the optimal fitting function, in an optional implementation, step S134 specifically includes steps S1341 to S1343: Step S1341: Calculate the information criterion values ​​of multiple fitting models, including linear function models, exponential decay function models, and logarithmic function models. The information criterion values ​​are used to evaluate the complexity and fitting accuracy of the fitting models. The smaller the complexity and the higher the fitting accuracy of the fitting model, the smaller the information criterion value.

[0072] Light intensity data sequence and the time sequence of data collection The following three types of function models were used for fitting: One is the linear function model:

[0073] The second is the exponential decay function model:

[0074] Thirdly, the logarithmic function model:

[0075] Calculate the Information Criterion Value (AIC) for each fitted model. The AIC value comprehensively evaluates the model complexity and fitting accuracy (the smaller the value, the better the model).

[0076] In the formula, The number of parameters for the fitted model (linear model) Exponential / logarithmic model ); The maximum likelihood value of the fitted model is calculated from the sum of squared residuals using the following formula:

[0077] In the formula, This is the sum of squared residuals, used to measure the accuracy of the model fit; This represents the number of data points.

[0078] Step S1342: The fitting model with the smallest information criterion value is determined as the optimal fitting model.

[0079] By comparing the AIC values ​​of the three types of models, the fitted model with the smallest AIC value is determined as the optimal fitted model. For example, if the linear model has the smallest AIC value, then the linear function is selected as the optimal model to achieve the best balance between fitting accuracy and complexity.

[0080] Step S1343: Based on the optimal fitting model, with the acquisition time as the independent variable and the corresponding light intensity data as the dependent variable, the light intensity data sequence is fitted to obtain the target fitting function.

[0081] Based on the selected optimal model, the model parameters are optimized using the least squares method: When the optimal fitting model is a linear function model, solve... ,make Minimize. When the optimal fit model is an exponential function, solve after linearization. For example, taking the logarithm: When the optimal fitting model is a linear function model, solve... make minimize.

[0082] For each acquisition time Output predicted value This constitutes a complete target fitting image.

[0083] Step S135: Calculate the residual between each light intensity data and the corresponding predicted value on the target fitting function to obtain the residual of each light intensity data.

[0084] For each sampling point, calculate the observed light intensity. Compared with the fitted predicted value The residuals, which are the differences between the actual observed values ​​and the predicted values ​​of the fitted model, are represented by the following formula:

[0085] In the formula, No. The residual at each sampling point reflects the degree of deviation between the actual light intensity and the time decay model.

[0086] Step S136: Calculate the average light intensity of all light intensity data in the light intensity data sequence.

[0087] Calculate the arithmetic mean of all light intensity data in the light intensity data sequence. The indicator has already been explained in the previous text, so it will not be repeated here.

[0088] Step S137: The goodness of fit is calculated based on the residual of each light intensity data and the difference between each light intensity data and the mean light intensity.

[0089] The goodness of fit is calculated based on the residuals and the mean light intensity. That is, the goodness of fit is quantified by the residuals and the differences between the data points and the mean. The goodness of fit is characterized by the following formula:

[0090] In the formula, It is the sum of squared residuals; The total sum of squares; The goodness of fit characterizes the ability of the fitted model to explain changes in light intensity. The goodness of fit ranges from 0 to 1. The closer the value is to 1, the better the fit and the stronger the ability of the fitted model to explain the data.

[0091] In an optional implementation, step S13 includes steps S138 to S1311: Step S138: From the light intensity data sequence, determine the maximum light intensity data with the largest value and the minimum light intensity data with the smallest value.

[0092] From light intensity data sequence Extract the maximum value and minimum value :

[0093]

[0094] The measurement period is used to measure the peak light intensity, reflecting the instantaneous highest output. The measurement is used to measure the lowest light intensity value within a measurement period, reflecting the instantaneous lowest output.

[0095] Step S139: Calculate the difference between the maximum light intensity data and the minimum light intensity data.

[0096] Calculate the difference between the maximum and minimum light intensity, which is also known as the peak-to-peak difference. , It characterizes the amplitude change of the output signal. It represents the range of light intensity fluctuations and directly characterizes the amplitude change of the output signal.

[0097]

[0098] Step S1310: Calculate the average light intensity of all light intensity data in the light intensity data sequence.

[0099] Calculate the arithmetic mean of all light intensity data to obtain the average light intensity value. .

[0100] Step S1311: Calculate the peak-to-peak value change based on the difference and the average light intensity.

[0101] Normalize the peak-to-peak difference to the average light intensity level:

[0102] This represents the peak-to-peak value variation; a smaller value indicates a more stable output.

[0103] Considering that the basic peak-to-peak value only reflects the global range and cannot capture the spatiotemporal distribution characteristics of instantaneous fluctuations, in order to ensure that the peak-to-peak value variation not only retains the instantaneous fluctuation characteristics of the light intensity data sequence but also characterizes the global fluctuation characteristics of the light intensity data sequence, therefore, in an optional implementation, after calculating the peak-to-peak value variation, the method further includes: Step S21: Determine multiple time windows based on the total number of light intensity data in the light intensity data sequence, the preset window length, and the preset sliding step size.

[0104] Based on the total number of points in the light intensity data sequence Preset window length Preset sliding step size Calculate the number of time windows :

[0105] In the formula, This represents the total number of light intensity data points. The length of the window; This is the sliding step size; This represents the total number of valid windows.

[0106] Step S22: Divide the light intensity data sequence into multiple sub-data segments through the multiple time windows.

[0107] Light intensity data sequence Divided into Individual data segments:

[0108] No. A window from the index Beginning, containing consecutive Data points.

[0109] Step S23: Calculate the local peak-to-peak value change of each of the multiple sub-data segments, where the local peak-to-peak value change represents the instantaneous fluctuation amplitude of the light intensity data within the sub-data segment.

[0110] For each sub-data segment Calculate the local peak-to-peak value variation A larger value indicates poorer stability during that period.

[0111] In the formula, The peak light intensity within the window reflects the local maximum output; This represents the lowest light intensity value within the window, reflecting the local minimum output. This represents the average light intensity within the window.

[0112] Step S24: Calculate the average fluctuation level based on the local peak-to-peak changes of each of the multiple sub-data segments.

[0113] Based on the local peak-to-peak variations across all windows, the overall average fluctuation level is calculated, i.e.:

[0114] Step S25: Calculate the abnormal fluctuation ratio based on the number of sub-data segments whose local peak-to-peak value changes exceed a preset fluctuation threshold and the total number of the multiple sub-data segments.

[0115] Set fluctuation threshold Statistical abnormal window ratio (Values ​​[0, 1]), reflecting the frequency of fluctuation events:

[0116] When the local peak value changes At that time, it was determined that the first The sliding window exhibits abnormal fluctuations.

[0117] Step S26: Determine the periodic fluctuation value based on the average fluctuation level and the abnormal fluctuation ratio. The larger the periodic fluctuation value, the more obvious the periodic fluctuation of the light intensity data sequence in the time dimension.

[0118] The periodic fluctuation value is obtained by weighting the average fluctuation level and the abnormal fluctuation ratio by using a linear coefficient preset based on empirical values.

[0119] Step S14: According to the preset grading rules, based on the cumulative offset index, the goodness of fit, and the peak-to-peak value change, determine the stability level of the vacuum ultraviolet deuterium lamp. The higher the stability level, the more stable the ultraviolet light of the target wavelength emitted by the vacuum ultraviolet deuterium lamp is.

[0120] Based on the calculated cumulative offset index, goodness of fit, and peak-to-peak value, the stability of the vacuum ultraviolet deuterium lamp is classified according to a preset classification rule. Specifically, the operational stability of the deuterium lamp is evaluated based on the values ​​of these indicators to determine its suitability. The stability level is determined based on preset thresholds. The higher the stability level, the more stable the wavelength of the light source, making it suitable for precise measurements or applications.

[0121] In an optional implementation, step S14 specifically includes steps S141 to S143: Step S141: If the cumulative offset index is less than a first preset threshold, the goodness of fit is greater than a second preset threshold, and the peak-to-peak value change is less than a third preset threshold, the stability level of the vacuum ultraviolet deuterium lamp is determined to be Level 1. Level 1 indicates that the vacuum ultraviolet deuterium lamp is in a stable working state.

[0122] When the cumulative offset index is less than the first preset threshold, the goodness of fit is greater than the second preset threshold, and the peak-to-peak value change is less than the third preset threshold, it indicates that the light intensity data sequence of the deuterium lamp remains basically stable without significant drift or fluctuation. When all indicators meet the above conditions, it indicates that the vacuum ultraviolet deuterium lamp is in a stable working state and can stably emit ultraviolet light of the target wavelength for a long period of time. Therefore, the stability of the vacuum ultraviolet deuterium lamp is determined to be Level 1, reflecting its very high stability, making it suitable for applications with high requirements for light intensity stability.

[0123] Step S142: If the cumulative offset index is less than the fourth preset threshold, the goodness of fit is greater than the fifth preset threshold, and the peak-to-peak value change is less than the third preset threshold, the stability level of the vacuum ultraviolet deuterium lamp is determined to be level two. Level two indicates that the vacuum ultraviolet deuterium lamp is in a drifting working state. Level two is lower than level one.

[0124] When the cumulative offset index is less than the fourth preset threshold, the goodness of fit is greater than the fifth preset threshold, and the peak-to-peak variation is less than the third preset threshold, although the stability of the light intensity data is relatively good, it fails to meet the first-level standard. Specifically, the light intensity data still has some drift or fluctuation, but it does not affect its basic stability. At this time, although the vacuum ultraviolet deuterium lamp can continue to work, its stability decreases slightly, and it is in a state of slight drift. That is to say, this situation indicates that the light intensity data of the deuterium lamp has begun to have slight fluctuations or drift, which is suitable for occasions where extremely high stability is not required. Therefore, the stability level is rated as the second level, indicating that the deuterium lamp is in a drifting working state.

[0125] Step S143, otherwise, determine the stability level of the vacuum ultraviolet deuterium lamp as level three, the level three indicates that the vacuum ultraviolet deuterium lamp is in an unstable working state, the level three is lower than the level two.

[0126] If any of the cumulative offset index, goodness of fit, or peak-to-peak variation fails to meet the first or second level criteria, it indicates a severe decrease in the stability of the light intensity data and a significant reduction in the stability of the vacuum ultraviolet deuterium lamp. In this case, the deuterium lamp is in an unstable operating state and cannot stably emit ultraviolet light of the target wavelength, which may negatively impact experiments or applications. In other words, if any of the indicators does not meet the aforementioned first or second level criteria, the stability will be rated as third level, indicating that the deuterium lamp is in an unstable operating state. At this point, the deuterium lamp needs to be adjusted or replaced to ensure its stability meets operational requirements.

[0127] Figure 3 This is a schematic diagram of the frame of a vacuum ultraviolet deuterium lamp intensity stability testing device according to one embodiment of the present invention. Please refer to [link / reference]. Figure 3 In a vacuum chamber maintained by a pumping system, the testing device emits a beam of light from a vacuum ultraviolet deuterium lamp. The beam is collimated, filtered, and monochromated sequentially by a ring mirror, a filter, and a concave grating of a monochromator. After monochromation, the beam is reflected by a mirror and split into two paths by a beam splitter: one path illuminates the sample through a focusing mirror, and the other path is directly guided to the detection device for light intensity signal acquisition. Finally, the control terminal receives the data from the detection device in real time and monitors, analyzes, and evaluates the light intensity stability, thereby completing the automated testing of the light intensity stability of the entire system.

[0128] This invention quantifies the overall drift of a light intensity data sequence relative to its initial intensity by calculating a cumulative offset index, thus identifying long-term trends in deuterium lamp intensity, such as attenuation and drift, rather than relying solely on instantaneous fluctuations. This allows the invention to identify and warn of stability issues in deuterium lamps during long-term use, overcoming the limitation of existing methods that are only sensitive to short-term fluctuations. Furthermore, the invention employs a goodness-of-fit index to quantify the degree to which the trend of light intensity data over time conforms to a target fitting function. This not only identifies instantaneous fluctuations in light intensity but also effectively reflects the regular trend of light intensity changes over time, thereby accurately determining whether a systematic decrease or degradation in deuterium lamp intensity has occurred. Furthermore, by combining a peak-to-peak value variation index, the maximum instantaneous fluctuation amplitude of light intensity within the measurement period is evaluated. This comprehensively reflects the light intensity stability of the deuterium lamp, including instantaneous fluctuations and long-term trend changes, avoiding the limitations of focusing only on short-term fluctuations. Finally, based on a grading rule, combining the cumulative offset index, goodness-of-fit, and peak-to-peak value variation, a clear evaluation level for the light intensity stability of vacuum ultraviolet deuterium lamps can be provided. It intuitively reflects the stability of the light source and can be used for comparison between different devices, providing a standardized and easy-to-use evaluation framework.

[0129] Figure 4 This is a structural block diagram of a vacuum ultraviolet deuterium lamp intensity stability testing device provided in one embodiment of the present invention, applied to perform the steps of a vacuum ultraviolet deuterium lamp intensity stability testing method as described above, such as... Figure 4 As shown, the device includes: a light source module 31, used to guide ultraviolet light of the target wavelength emitted by a vacuum ultraviolet deuterium lamp to the detection device in a vacuum environment.

[0130] The detection module 32 is used by the detection device to continuously collect light intensity data at each moment at a preset time interval to obtain a light intensity data sequence.

[0131] The calculation module 33 is used to calculate the cumulative offset index, goodness of fit, and peak-to-peak value change of the ultraviolet light of the target wavelength based on the light intensity data at each moment; wherein, the cumulative offset index represents the overall drift of the light intensity data sequence relative to the initial light intensity, the goodness of fit represents the degree to which the trend of the light intensity data sequence changing over time conforms to the target fitting function, and the peak-to-peak value change represents the maximum instantaneous fluctuation amplitude of the light intensity data sequence within the measurement period.

[0132] The judgment module 34 is used to determine the stability level of the vacuum ultraviolet deuterium lamp based on the cumulative offset index, the goodness of fit, and the peak-to-peak value change according to the preset grading rules. The higher the stability level, the more stable the ultraviolet light of the target wavelength emitted by the vacuum ultraviolet deuterium lamp is.

[0133] This invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, it implements the various processes described above in an embodiment of a method for evaluating the stability of vacuum ultraviolet deuterium lamp light intensity, and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0134] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, electronic devices, and media. Therefore, embodiments of the present invention can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention can take the form of a computer program product embodied on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0135] Embodiments of the present invention are described with reference to flowchart illustrations and / or block diagrams of methods and apparatus according to embodiments of the present invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing terminal equipment to cause a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0136] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present invention.

[0137] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the term "comprising" or any other variations thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element. The above provides a detailed description of a method and apparatus for evaluating the stability of vacuum ultraviolet deuterium lamp light intensity provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and its core ideas; at the same time, for those skilled in the art, based on the ideas of the present invention, there will be changes in specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for evaluating the stability of vacuum ultraviolet deuterium lamp light intensity, characterized in that, include: In a vacuum environment, ultraviolet light of the target wavelength emitted by a vacuum ultraviolet deuterium lamp is guided to the detection device; The detection device continuously collects light intensity data at each time point at a preset time interval to obtain a light intensity data sequence; Based on the light intensity data at each moment, the cumulative shift index, goodness of fit, and peak-to-peak value change of the ultraviolet light at the target wavelength are calculated; wherein, the cumulative shift index characterizes the overall drift of the light intensity data sequence relative to the initial light intensity, the goodness of fit characterizes the degree to which the trend of the light intensity data sequence changing over time conforms to the target fitting function, and the peak-to-peak value change characterizes the maximum instantaneous fluctuation amplitude of the light intensity data sequence within the measurement period. According to the preset grading rules, the stability level of the vacuum ultraviolet deuterium lamp is determined based on the cumulative offset index, the goodness of fit, and the peak-to-peak value variation. The higher the stability level, the more stable the ultraviolet light of the target wavelength emitted by the vacuum ultraviolet deuterium lamp is. The calculation of the cumulative shift index of the target wavelength ultraviolet light based on the light intensity data at each moment includes: Using the light intensity data collected at the first moment in the light intensity data sequence as the reference value, the deviation of the light intensity data at each subsequent moment in the light intensity data sequence from the reference value is calculated respectively. Determine the absolute value of the deviation at each moment in the light intensity data sequence, and calculate the sum of the absolute values ​​of the deviation at all moments in the light intensity data sequence; The sum of the absolute values ​​of the deviations at all times in the light intensity data sequence is normalized to obtain the cumulative offset index of the ultraviolet light at the target wavelength. Among them, the goodness of fit of the ultraviolet light of the target wavelength is calculated based on the light intensity data at each time moment, including: Using the acquisition time as the independent variable and the corresponding light intensity data as the dependent variable, the light intensity data sequence is fitted to obtain the target fitting function, which is composed of the predicted value output by the preset fitting model for each acquisition time. Calculate the residual between each light intensity data point and the corresponding predicted value on the target fitting function to obtain the residual of each light intensity data point; Calculate the average light intensity of all light intensity data in the light intensity data sequence; The goodness of fit is calculated based on the residual of each light intensity data and the difference between each light intensity data and the mean light intensity. Specifically, based on the light intensity data at each moment, the peak-to-peak value variation of the target wavelength ultraviolet light is calculated, including: From the light intensity data sequence, determine the maximum light intensity data with the largest value and the minimum light intensity data with the smallest value; Calculate the difference between the maximum light intensity data and the minimum light intensity data; Calculate the average light intensity of all light intensity data in the light intensity data sequence; The peak-to-peak value variation is calculated based on the difference and the average light intensity.

2. The method according to claim 1, characterized in that, The sum of the absolute values ​​of the deviations at all times in the light intensity data sequence is normalized to obtain the cumulative shift index of the ultraviolet light at the target wavelength, including: A corresponding weight is assigned to each moment in the light intensity data sequence, wherein the weight of the acquisition moment that is closer to the current time is greater, and the weight is calculated based on the time decay factor; Multiply the absolute value of the deviation at each time step by the corresponding weight to obtain the weighted deviation. Calculate the sum of weighted deviations at all times, and calculate the mean light intensity of all light intensity data in the light intensity data sequence; The total number of light intensity data in the light intensity data sequence is determined, and the cumulative offset index of the ultraviolet light of the target wavelength is calculated based on the sum of the weighted deviations at all times, the total number of light intensity data in the light intensity data sequence, and the average light intensity.

3. The method according to claim 1, characterized in that, Using the acquisition time as the independent variable and the corresponding light intensity data as the dependent variable, the light intensity data sequence is fitted to obtain the target fitting function, including: Calculate information criterion values ​​for multiple fitting models, including linear function models, exponential decay function models, and logarithmic function models. The information criterion values ​​are used to evaluate the complexity and fitting accuracy of the fitting models. The smaller the complexity and the higher the fitting accuracy of the fitting model, the smaller the information criterion value. The fitting model with the smallest information criterion value is determined as the optimal fitting model; Based on the optimal fitting model, the light intensity data sequence is fitted with the acquisition time as the independent variable and the corresponding light intensity data as the dependent variable to obtain the target fitting function.

4. The method according to claim 1, characterized in that, After calculating the peak-to-peak value change, the method further includes: Multiple time windows are determined based on the total number of light intensity data in the light intensity data sequence, the preset window length, and the preset sliding step size; The light intensity data sequence is divided into multiple sub-data segments using the multiple time windows; Calculate the local peak-to-peak value change of each of the multiple sub-data segments, where the local peak-to-peak value change represents the instantaneous fluctuation amplitude of the light intensity data within the sub-data segment; The average fluctuation level is calculated based on the local peak-to-peak changes of each of the multiple sub-data segments. The abnormal fluctuation ratio is calculated based on the number of sub-data segments whose local peak-to-peak value changes exceed a preset fluctuation threshold, and the total number of the multiple sub-data segments. Based on the average fluctuation level and the abnormal fluctuation ratio, a periodic fluctuation value is determined. The larger the periodic fluctuation value, the more obvious the periodic fluctuation of the light intensity data sequence in the time dimension.

5. The method according to claim 1, characterized in that, According to preset grading rules, the stability level of the vacuum ultraviolet deuterium lamp is determined based on the cumulative offset index, the goodness of fit, and the peak-to-peak value variation, including: If the cumulative offset index is less than a first preset threshold, the goodness of fit is greater than a second preset threshold, and the peak-to-peak value change is less than a third preset threshold, the stability level of the vacuum ultraviolet deuterium lamp is determined to be level one, and level one indicates that the vacuum ultraviolet deuterium lamp is in a stable working state. If the cumulative offset index is less than the fourth preset threshold, the goodness of fit is greater than the fifth preset threshold, and the peak-to-peak value change is less than the third preset threshold, the stability level of the vacuum ultraviolet deuterium lamp is determined to be level two. Level two indicates that the vacuum ultraviolet deuterium lamp is in a drift working state. Level two is lower than level one. Otherwise, the stability level of the vacuum ultraviolet deuterium lamp is determined to be level three, which indicates that the vacuum ultraviolet deuterium lamp is in an unstable working state, and level three is lower than level two.

6. A stability testing device for vacuum ultraviolet deuterium lamp light intensity, characterized in that, The steps applied to performing the method as described in any one of claims 1-5 include: The light source module is used to guide the ultraviolet light of the target wavelength emitted by the vacuum ultraviolet deuterium lamp to the detection device in a vacuum environment; The detection module is used by the detection device to continuously collect light intensity data at each moment at a preset time interval to obtain a light intensity data sequence. The calculation module is used to calculate the cumulative shift index, goodness of fit, and peak-to-peak value change of the ultraviolet light of the target wavelength based on the light intensity data at each moment. The cumulative shift index represents the overall drift of the light intensity data sequence relative to the initial light intensity, the goodness of fit represents the degree to which the trend of the light intensity data sequence changing over time conforms to the target fitting function, and the peak-to-peak value change represents the maximum instantaneous fluctuation amplitude of the light intensity data sequence within the measurement period. The judgment module is used to determine the stability level of the vacuum ultraviolet deuterium lamp based on the cumulative offset index, the goodness of fit, and the peak-to-peak value change according to the preset classification rules. The higher the stability level, the more stable the ultraviolet light of the target wavelength emitted by the vacuum ultraviolet deuterium lamp is. The calculation module is further configured to: Using the light intensity data collected at the first moment in the light intensity data sequence as the reference value, the deviation of the light intensity data at each subsequent moment in the light intensity data sequence from the reference value is calculated respectively. Determine the absolute value of the deviation at each moment in the light intensity data sequence, and calculate the sum of the absolute values ​​of the deviation at all moments in the light intensity data sequence; The sum of the absolute values ​​of the deviations at all times in the light intensity data sequence is normalized to obtain the cumulative offset index of the ultraviolet light at the target wavelength. Using the acquisition time as the independent variable and the corresponding light intensity data as the dependent variable, the light intensity data sequence is fitted to obtain the target fitting function, which is composed of the predicted value output by the preset fitting model for each acquisition time. Calculate the residual between each light intensity data point and the corresponding predicted value on the target fitting function to obtain the residual of each light intensity data point; Calculate the average light intensity of all light intensity data in the light intensity data sequence; The goodness of fit is calculated based on the residual of each light intensity data and the difference between each light intensity data and the mean light intensity. From the light intensity data sequence, determine the maximum light intensity data with the largest value and the minimum light intensity data with the smallest value; Calculate the difference between the maximum light intensity data and the minimum light intensity data; Calculate the average light intensity of all light intensity data in the light intensity data sequence; The peak-to-peak value variation is calculated based on the difference and the average light intensity.

7. An electronic device, characterized in that, include: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the steps of the method as described in any one of claims 1-5.

Images