An all-weather air tritiated water sampling method and system

Abstract

The application discloses a kind of air tritiated water sampling method and system for all-weather, it is related to air tritiated water sampling field, the method comprises: four kinds of environmental parameters of temperature, relative humidity, atmospheric pressure and air flow rate of sampling point are acquired in real time;The environmental parameters acquired in real time are input to the preset dynamic parameter generator, and output a set of optimized key sampling parameter combination;According to the optimized key sampling parameter combination, dynamically adjust sampling pump, temperature adjusting device to execute sampling operation;In the whole sampling cycle, the effective adsorption capacity of adsorbent is continuously monitored, and the early warning information of adsorbent replacement is provided to the user.The problems such as condensation icing, adsorbent premature saturation or resolution under all-weather can be effectively avoided by the application, and the sampling efficiency and accuracy are significantly improved;At the same time, through adsorbent residual capacity monitoring and failure warning, the sampling is continuously stable, and high-precision, intelligent air tritiated water sampling under any weather condition is realized.

Description

Technical Field

[0001] This invention relates to the field of air tritized water sampling, and more particularly to an air tritized water sampling method and system for all climates. Background Technology

[0002] Existing air tritized water sampling methods typically operate based on fixed or empirical parameters (such as sampling flow rate, adsorbent replacement cycle, and temperature control threshold). However, under "all-climate" conditions (i.e., environments that change rapidly or are extremely cold and dry to hot and humid), these fixed parameters significantly reduce sampling efficiency and accuracy. Specifically, under low temperature and high humidity conditions, water vapor easily condenses or freezes, blocking the flow path; under high temperature and dry conditions, the adsorbent may become saturated prematurely or undergo desorption; and under rapidly changing climate conditions, a single parameter cannot adaptively optimize, leading to incomplete tritized water collection or distorted concentration measurements. Currently, there is a lack of an intelligent control method capable of sensing multi-dimensional environmental variables in real time and dynamically and collaboratively adjusting key sampling parameters to ensure stable, efficient, and high-precision tritized water sampling under any climatic conditions. Summary of the Invention

[0003] This invention provides a method for sampling air tritium water for all climates, comprising:

[0004] Step 1: Real-time acquisition of four environmental parameters at the sampling point: temperature, relative humidity, atmospheric pressure, and air velocity;

[0005] Step 2: Input the real-time acquired environmental parameters into the preset dynamic parameter generator, and output a set of optimized key sampling parameter combinations; the dynamic parameter generator is a virtual dynamic system that describes the interaction between microclimate and sampling process, and by solving the optimization problem of the system under specific boundaries, the optimal control parameters are derived.

[0006] Step 3: Dynamically adjust the sampling pump and temperature control device according to the optimized combination of key sampling parameters to perform the sampling operation;

[0007] Step 4: Continuously monitor the effective adsorption capacity of the adsorbent throughout the entire sampling cycle and provide users with early warning information on adsorbent replacement.

[0008] The above-described method for sampling tritium water in the air for all climates includes the following specific construction and solution process for the dynamic parameter generator:

[0009] Define the system state variables and control input vector of the sampling device;

[0010] Using the obtained environmental parameters, the evolution equations of the system state variables are constructed;

[0011] The evolution equations of the coupled system state variables are used to construct the decision function of the dynamic parameter generator, obtain the optimal solution of the control input vector in the finite time domain, and output the combination of key sampling parameters.

[0012] The above-described method for sampling tritized water in air for all climates, wherein the effective adsorption capacity of the adsorbent is continuously monitored throughout the sampling period, and early warning information for adsorbent replacement is provided to the user, is specifically divided into the following sub-steps:

[0013] The remaining effective adsorption capacity of the adsorbent is calculated using the system state variables output by the dynamic parameter generator.

[0014] Based on the historical monitoring sequence of the remaining effective adsorption capacity of the adsorbent, the adsorbent failure time is estimated, and early warning information for adsorbent replacement is generated.

[0015] The present invention also provides an air tritized water sampling system for all climates, comprising: an environmental parameter acquisition module, a sampling parameter generation module, a sampling operation execution module, and an adsorbent monitoring module;

[0016] The environmental parameter acquisition module is used to acquire four environmental parameters at the sampling point in real time: temperature, relative humidity, atmospheric pressure, and air velocity.

[0017] The sampling parameter generation module is used to input the environmental parameters acquired in real time into the preset dynamic parameter generator and output a set of optimized key sampling parameter combinations.

[0018] The sampling operation execution module is used to dynamically adjust the sampling pump and temperature control device according to the optimal combination of key sampling parameters to perform the sampling operation.

[0019] The adsorbent monitoring module is used to continuously monitor the effective adsorption capacity of the adsorbent throughout the entire sampling cycle and provide users with early warning information for adsorbent replacement.

[0020] As described above, an air tritium water sampling system for all climates includes a sampling parameter generation module, specifically comprising:

[0021] The coupling quantity definition submodule is used to define the system state variables and control input vectors of the sampling device;

[0022] The system state reasoning submodule is used to construct the evolution equation of the system state variables using the acquired environmental parameters;

[0023] The control input vector solving submodule is used to couple the evolution equations of the system state variables to construct the decision function of the dynamic parameter generator, obtain the optimal solution of the control input vector in the finite time domain, and output the combination of key sampling parameters.

[0024] As described above, an air tritium water sampling system for all climates includes an adsorbent monitoring module, specifically comprising:

[0025] The effective adsorption capacity calculation submodule is used to calculate the remaining effective adsorption capacity of the adsorbent using the system state variables output by the dynamic parameter generator.

[0026] The early warning information generation submodule is used to estimate the adsorbent failure time based on the historical monitoring sequence of the remaining effective adsorption capacity of the adsorbent, and generate early warning information for adsorbent replacement.

[0027] The beneficial effects achieved by this invention are as follows: By collecting multi-dimensional environmental parameters in real time and dynamically optimizing the sampling pump speed and temperature control parameters, problems such as condensation and freezing, premature saturation or desorption of adsorbents under all climate conditions are effectively avoided, significantly improving sampling efficiency and accuracy; at the same time, by monitoring the remaining capacity of the adsorbent and providing early warning of failure, continuous and stable sampling is ensured, enabling high-precision and intelligent sampling of tritium water in the air under any climatic conditions. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0029] Figure 1 This is a flowchart of an air tritium water sampling method for all climates provided in Embodiment 1 of this application;

[0030] Figure 2 This is a schematic diagram of an air tritized water sampling system for all climates provided in Embodiment 1 of this application. Detailed Implementation

[0031] 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.

[0032] Example 1

[0033] like Figure 1 As shown, Embodiment 1 of this application provides a method for sampling air tritium water for all climates, including:

[0034] Step S10: Real-time acquisition of four environmental parameters at the sampling point: temperature, relative humidity, atmospheric pressure, and air velocity;

[0035] A multi-parameter environmental sensing unit is deployed at the sampling point. This unit includes at least a temperature sensor, a relative humidity sensor, an atmospheric pressure sensor, and an air velocity sensor. Each sensor is located near the sampling inlet and exposed to the same environmental conditions to ensure that the measured parameters are consistent with the state of the air to be sampled. The output signals of each sensor are collected synchronously at a preset sampling frequency (once per second to once per minute, which can be configured according to requirements). The acquisition process is marked with timestamps to ensure that the four types of data, namely temperature, relative humidity, atmospheric pressure, and air velocity, are aligned in time. Based on the sensor calibration parameters and conversion relationship, the digital signals are converted into actual physical quantity values.

[0036] Step S20: Input the real-time acquired environmental parameters into the preset dynamic parameter generator and output a set of optimized key sampling parameter combinations;

[0037] The dynamic parameter generator is a virtual dynamic system describing the interaction between the microclimate and sampling processes. By solving the optimization problem of this system under specific boundaries, the optimal control parameters are derived. The specific construction and solution process is as follows:

[0038] Step S21: Define the system state variables and control input vector of the sampling device;

[0039] The system state variables of the sampling device are described by two coupled variables: A dimensionless state quantity used to characterize the effective adsorption potential of the adsorbent for tritized water at time t. The icing / over-analysis risk coefficient is used to characterize the sampling flow path interface at time t.

[0040] The control input vector is defined as , Let be the normalized rate of the sampling pump at time t. The temperature adjustment amount of the temperature control device at time t (relative to the ambient temperature).

[0041] Step S22: Using the obtained environmental parameters, construct the evolution equations of the system state variables;

[0042] Based on the principles of mass and energy transfer, the system state variables are constructed using real-time acquired data such as temperature T, relative humidity H, atmospheric pressure P, and air velocity V. and Evolution equation:

[0043]

[0044]

[0045] in For reference relative humidity, it is usually set to the humidity value under standard operating conditions or typical working environment. In this embodiment, it is set to 50%, which is used to perform dimensionless normalization of real-time humidity. The optimal temperature for the adsorbent to operate; The temperature-sensitive time constant is used to reflect the sensitivity of the adsorption process to temperature. It is estimated by conducting adsorption kinetic experiments under different isothermal conditions and fitting the curve of adsorption capacity changing with time. Standard atmospheric pressure; Let t be the normalized rate of the sampling pump at time t; The dissipation coefficient of the adsorption potential is given by the risk of freezing / over-desorption, characterizing the dissipation coefficient of the adsorption potential when the risk coefficient is... Exceeding the safety threshold At that time, its effective adsorption potential The degradation rate was obtained by fitting the adsorption performance decay data under ideal and disturbed conditions under conditions with the risk of condensation or high temperature. The intensity coefficient of the high-temperature analytical effect; The shape parameter is used to clarify the effect of high-temperature analysis, i.e., it intensifies with increasing temperature. and The results were obtained by fitting the analytical kinetics data of the adsorbent at high temperature. The high-temperature desorption risk threshold is the rate at which the adsorbent desorbs (desorbs) the captured tritium water when the temperature exceeds this value. This value is determined by thermogravimetric analysis (TGA) or temperature-programmed desorption (TPD) experiments on the adsorbent material. This is the critical threshold for high humidity condensation. When the relative humidity of the environment exceeds this value, the risk of water vapor condensation or ice formation on the flow path or adsorbent surface increases sharply. Its value is obtained through experimental observation. To mitigate the risk of condensation at critical humidity The smaller the value of the transition width, the more abrupt the transition, indicating that condensation occurs faster near the critical point. This parameter can be identified through experiments on humidity step changes and by observing the system response (such as the time it takes for an optical sensor to detect condensation). The reference air velocity is the rated operating velocity of the sampling pump. The temperature adjustment amount of the temperature control device at time t; This is a scaling parameter for temperature deviation, used to measure temperature deviation. Dimensionless; The weighting coefficients for the tendency of condensation are determined through condensation experiments under controlled humidity and flow rate. The weighting coefficient for the impact of temperature deviation on risk reflects the enhanced effect of actual temperature deviating from the optimal temperature on the risk coefficient. It is calibrated by testing the change of the risk coefficient under different temperature settings. Risk decay rate is the rate at which the risk coefficient decreases by the system itself (e.g., through equilibrium diffusion) without external driving force. It can be estimated by observing the decay process of risk indicators (e.g., pressure difference, humidity) after temperature control is stopped in a stable environment.

[0046] The coefficient characterizes the rate at which the risk of condensation increases, driven by both ambient humidity and flow velocity. Its specific calibration procedure is as follows:

[0047] Keep the ambient temperature within a safe range to avoid triggering the risk of high-temperature desorption, turn off the temperature control device, fix the atmospheric pressure and air flow rate, and rapidly increase the relative humidity from a low level (30%) to above the critical value and keep it stable.

[0048] An optical transmittance sensor was used to monitor changes in light scattering intensity in the flow path window caused by fogging / icing, and the monitored raw signal was normalized to a risk factor. ;

[0049] Under these experimental conditions, the risk coefficient will be... The dynamic evolution equation is discretized, and a formula for the sum of squared errors between predicted and measured values ​​is constructed. This sum of squared errors is then minimized using an optimization algorithm (such as Levenberg-Marquardt) to obtain the result. ;

[0050] After discretization, Predicted value of risk coefficient at any time The calculation formula is expressed as: , where i is a discrete sampling node, for The relative humidity measurement at that moment. The sampling time interval, for The predicted risk coefficient at time 1, the predicted risk coefficient at the initial time 2, i.e. Let the measured initial value be used. It is the calibrated and known natural decay rate of risk;

[0051] The formula for the sum of squared errors is then expressed as: Where SS is the result of the sum of squared errors. for The measured risk coefficient at time SS is used, where i ranges from 1 to n, and n is the total number of sampling nodes. A nonlinear least squares optimization algorithm is employed to find the value that minimizes the SS value. The parameters are used as the final calibration result.

[0052] Step S23: Construct the decision function of the dynamic parameter generator by coupling the evolution equations of the system state variables, obtain the optimal solution of the control input vector in the finite time domain, and output the combination of key sampling parameters;

[0053] The decision function based on the dynamic parameter generator can be used in the finite time domain. Internal solution of control input vector The optimal solution is expressed mathematically as follows:

[0054]

[0055] Where J is the return value of the decision function. , , , These are weighting coefficients, used to balance adsorption efficiency, pump speed regulation energy consumption, temperature control energy consumption, and system risk, respectively. for The effective adsorption potential of the adsorbent for tritium-treated water at any given time. for The icing / over-analysis risk coefficient at the sampling flow path interface is obtained through the evolution equation of the system state variables. Specifically, based on the above evolution equation, combined with the effective adsorption potential given by the technician when the sampling device is turned on, the initial value of the risk coefficient, the real-time acquired environmental parameters, and the current... , The iterative values ​​are calculated directly at each time step using numerical integration. and ; for Normalized rate of the sampling pump at any given time. for The temperature adjustment amount of the temperature control device is constantly monitored. This is a reference value for pump speed; The initial time of the prediction window, This is the preset prediction window size;

[0056] Its constraints are: ; ; ; ;in , These represent the upper and lower boundaries of the normalized rate of the sampling pump, ensuring that the optimized pump speed command is within the actual operating capacity of the sampling pump; T represents the current ambient temperature. , The upper and lower temperature limits that the temperature control device can adjust;

[0057] Numerical optimization methods (such as direct transcription) are used to solve for the control input vector that satisfies the above constraints and minimizes the J value. In the finite time domain Find the optimal discrete time series within the range; use this time series as the key sampling parameter combination for output.

[0058] Step S30: Dynamically adjust the sampling pump and temperature control device according to the optimized combination of key sampling parameters to perform the sampling operation;

[0059] Normalize the sampling pump rate in the key sampling parameter combination in chronological order. ,and The temperature regulation amount is converted into an actual control signal and simultaneously sent to the sampling pump and temperature regulation device of the sampling device to continuously perform the sampling operation.

[0060] Step S40: Continuously monitor the effective adsorption capacity of the adsorbent throughout the entire sampling cycle and provide users with early warning information for adsorbent replacement; specifically, this is divided into the following sub-steps:

[0061] Step S41: Calculate the remaining effective adsorption capacity of the adsorbent using the system state variables output by the dynamic parameter generator;

[0062] The real-time system state variables derived from the evolution equations of the system state variables received by the dynamic parameter generator are the effective adsorption potential at the current moment. and risk coefficient Based on the formula: Real-time calculation of the remaining effective adsorption capacity of the adsorbent ,in This represents the maximum theoretical adsorption capacity of the adsorbent. Let t be the initial time of adsorbent use, and t be the current time. As a preset risk threshold, The risk reduction factor is determined through a controllable risk experiment: under stable, non-high-temperature conditions, artificially induced... And maintain, and measure the difference in actual adsorption capacity of the adsorbent before and after. Using the formula The results were obtained through reverse fitting. for Temperature measurement at time, The preset high-temperature analysis risk threshold, The high-temperature decomposition reduction factor was calibrated through a stepped temperature rise decomposition experiment: under low-risk conditions, the temperature was stabilized at multiple levels higher than [a certain value]. The adsorbent was measured at each step of the ladder to determine its capacity loss. Using the formula The results were obtained through reverse fitting. For indicator functions, when The value is 1 if it is true, and 0 otherwise.

[0063] Step S42: Based on the historical monitoring sequence of the remaining effective adsorption capacity of the adsorbent, estimate the adsorbent failure time and generate early warning information for adsorbent replacement;

[0064] The system records the calculation results of the remaining effective adsorption capacity of the adsorbent in real time and organizes them into a time series; a linear fitting method is used to establish the historical remaining effective adsorption capacity. The formula relating to time t is: ,in Let be the decay rate, and b be the fitting constant. The solution is obtained using the least squares method. With b; then let the fitting formula in (Preset adsorbent failure threshold) to deduce failure time Calculate the current remaining usage time. (Current moment); A warning message will be displayed to the user via a pop-up window: The estimated remaining usage time of the adsorbent is... Please remember to replace the adsorbent in a timely manner.

[0065] Example 2

[0066] like Figure 2 As shown in Embodiment 2 of this application, an air tritized water sampling system for all climates is provided, including: an environmental parameter acquisition module 21, a sampling parameter generation module 22, a sampling operation execution module 23, and an adsorbent monitoring module 24.

[0067] The environmental parameter acquisition module 21 is used to acquire four environmental parameters at the sampling point in real time: temperature, relative humidity, atmospheric pressure, and air velocity.

[0068] The sampling parameter generation module 22 is used to input the real-time acquired environmental parameters into a preset dynamic parameter generator and output a set of optimized key sampling parameter combinations; specifically including:

[0069] 1. The coupling quantity definition submodule is used to define the system state variables and control input vectors of the sampling device;

[0070] 2. System state reasoning submodule, used to construct the evolution equation of system state variables using the acquired environmental parameters;

[0071] 3. Control input vector solution submodule: This module is used to couple the evolution equations of the system state variables to construct the decision function of the dynamic parameter generator, obtain the optimal solution of the control input vector in the finite time domain, and output the combination of key sampling parameters.

[0072] The sampling operation execution module 23 is used to dynamically adjust the sampling pump and temperature control device according to the optimal combination of key sampling parameters to perform the sampling operation.

[0073] The adsorbent monitoring module 24 is used to continuously monitor the effective adsorption capacity of the adsorbent throughout the entire sampling cycle and provide users with early warning information for adsorbent replacement; specifically, it includes:

[0074] 1. Effective adsorption capacity calculation submodule, used to calculate the remaining effective adsorption capacity of the adsorbent using the system state variables output by the dynamic parameter generator;

[0075] 2. Early warning information generation submodule, which is used to estimate the adsorbent failure time based on the historical monitoring sequence of the remaining effective adsorption capacity of the adsorbent, and generate early warning information for adsorbent replacement.

[0076] Corresponding to the above embodiments, the present invention provides a computer storage medium, including: at least one memory and at least one processor;

[0077] The memory is used to store one or more program instructions;

[0078] A processor for running one or more program instructions to execute a method for sampling air tritized water for all climates.

[0079] Corresponding to the above embodiments, this embodiment of the invention provides a computer-readable storage medium containing one or more program instructions, which are executed by a processor to provide a method for sampling air tritized water for all climates.

[0080] The embodiments disclosed in this invention provide a computer-readable storage medium storing computer program instructions that, when executed on a computer, cause the computer to perform the above-described method for sampling tritized water in air for all climates.

[0081] In this embodiment of the invention, the processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0082] The various methods, steps, and logic diagrams disclosed in the embodiments of this invention can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor reads information from the storage medium and, in conjunction with its hardware, completes the steps of the above methods.

[0083] The storage medium can be memory, such as volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.

[0084] Among them, non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory.

[0085] Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (Synchlink DRAM, SLDRAM), and direct memory bus RAM (DRRAM).

[0086] The storage media described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memory.

[0087] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in this invention can be implemented using a combination of hardware and software. When applied as software, the corresponding functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of computer programs from one place to another. Storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0088] 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 description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solution of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for sampling tritium-enriched air in all climates, characterized in that, include: Step S10: Real-time acquisition of four environmental parameters at the sampling point: temperature, relative humidity, atmospheric pressure, and air velocity; Step S20: Input the real-time acquired environmental parameters into a preset dynamic parameter generator, and output a set of optimized key sampling parameter combinations. The dynamic parameter generator is a virtual dynamic system describing the interaction between the microclimate and the sampling process. By solving the optimization problem of this system under specific boundaries, the optimal control parameters are derived. It has a built-in evolution equation of the system state variables and a decision function. The evolution equation of the system state variables is used to predict the real-time system state variables based on the real-time acquired environmental parameters. The specific construction and solution process is as follows: Define the system state variables and control input vector of the sampling device; The system state variables of the sampling device are described by two coupled variables: A dimensionless state quantity used to characterize the effective adsorption potential of the adsorbent for tritized water at time t. The icing / over-analysis risk coefficient is used to characterize the sampling flow path interface at time t; The control input vector is defined as , Let be the normalized rate of the sampling pump at time t. The temperature adjustment amount of the temperature control device at time t; Using the obtained environmental parameters, the evolution equations of the system state variables are constructed; Based on the principles of mass and energy transfer, the system state variables are constructed using real-time acquired data such as temperature T, relative humidity H, atmospheric pressure P, and air velocity B. and Evolution equation: in For reference relative humidity, The optimal temperature for the adsorbent to operate; This is the temperature-sensitive time constant, used to reflect the sensitivity of the adsorption process to temperature; Standard atmospheric pressure; Let t be the normalized rate of the sampling pump at time t; The dissipation coefficient of the adsorption potential is given by the risk of freezing / over-desorption, characterizing the dissipation coefficient of the adsorption potential when the risk coefficient is... Exceeding the safety threshold At that time, its effective adsorption potential The rate of destruction; The intensity coefficient of the high-temperature analytical effect; The shape parameter is used to clarify the law of high-temperature analytical effect, that is, it intensifies with increasing temperature; The high-temperature analysis risk threshold; This represents the critical threshold for high-humidity condensation. To mitigate the risk of condensation at critical humidity The smaller the value of the transition width near the critical point, the more rapid the transition, indicating that condensation occurs faster near the critical point; The reference air velocity is the rated operating velocity of the sampling pump. The temperature adjustment amount of the temperature control device at time t; This is a scaling parameter for temperature deviation, used to measure temperature deviation. Dimensionless; The weighting coefficient for the tendency of condensation formation represents the rate at which environmental humidity and flow velocity jointly drive the increase in condensation risk. The weighting coefficient for the impact of temperature deviation on risk reflects the enhanced effect of actual temperature deviating from the optimal temperature on the risk coefficient. Risk decay rate is the rate at which the system itself reduces the risk coefficient without external driving force. The evolution equations of the coupled system state variables are used to construct the decision function of the dynamic parameter generator, obtain the optimal solution of the control input vector in the finite time domain, and output the combination of key sampling parameters. Step S30: Dynamically adjust the sampling pump and temperature control device according to the optimized combination of key sampling parameters to perform the sampling operation; Step S40: Continuously monitor the effective adsorption capacity of the adsorbent throughout the entire sampling cycle and provide users with early warning information on adsorbent replacement.

2. The method for sampling tritium-enriched air for all climates according to claim 1, characterized in that, Throughout the sampling cycle, the effective adsorption capacity of the adsorbent is continuously monitored, and users are provided with early warning information regarding adsorbent replacement. This process is divided into the following sub-steps: The remaining effective adsorption capacity of the adsorbent is calculated using the system state variables output by the dynamic parameter generator. Based on the historical monitoring sequence of the remaining effective adsorption capacity of the adsorbent, the adsorbent failure time is estimated, and early warning information for adsorbent replacement is generated.

3. A system for sampling tritized air water in all climates, characterized in that, include: Environmental parameter acquisition module, sampling parameter generation module, sampling operation execution module, adsorbent monitoring module; The environmental parameter acquisition module is used to acquire four environmental parameters at the sampling point in real time: temperature, relative humidity, atmospheric pressure, and air velocity. The sampling parameter generation module is used to input the environmental parameters acquired in real time into the preset dynamic parameter generator and output a set of optimized key sampling parameter combinations. The sampling operation execution module is used to dynamically adjust the sampling pump and temperature control device according to the optimal combination of key sampling parameters to perform the sampling operation. The adsorbent monitoring module is used to continuously monitor the effective adsorption capacity of the adsorbent throughout the entire sampling cycle and provide users with early warning information for adsorbent replacement.

4. The air tritium water sampling system for all climates according to claim 3, characterized in that, The sampling parameter generation module specifically includes: The coupling quantity definition submodule is used to define the system state variables and control input vectors of the sampling device; The system state reasoning submodule is used to construct the evolution equation of the system state variables using the acquired environmental parameters; The control input vector solving submodule is used to couple the evolution equations of the system state variables to construct the decision function of the dynamic parameter generator, obtain the optimal solution of the control input vector in the finite time domain, and output the combination of key sampling parameters.

5. The air tritium water sampling system for all climates according to claim 4, characterized in that, The adsorbent monitoring module specifically includes: The effective adsorption capacity calculation submodule is used to calculate the remaining effective adsorption capacity of the adsorbent using the system state variables output by the dynamic parameter generator. The early warning information generation submodule is used to estimate the adsorbent failure time based on the historical monitoring sequence of the remaining effective adsorption capacity of the adsorbent, and generate early warning information for adsorbent replacement.

6. A computer storage medium, characterized in that, Used to store one or more program instructions; When the program instructions are executed by the processor, they implement a method for sampling air tritized water for all climates as described in any one of claims 1-2.

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