A method, device, equipment, medium and product for correlation analysis of hydrogen permeation performance and hydrogen charging performance

Abstract

The application discloses a kind of hydrogen permeation performance and the correlation analysis method of hydrogen charging performance, device, equipment, medium and product, comprising: hydrogen permeation performance test data is acquired based on hydrogen permeation performance parameter under setting constraint, and the hydrogen permeation performance index of ring weld joint is determined based on the hydrogen permeation performance test data;Hydrogen charging performance test data is acquired based on hydrogen charging performance parameter under setting constraint, and the hydrogen charging performance index of ring weld joint is determined based on the hydrogen charging performance test data;Material parameter of ring weld joint is acquired, and target model is established based on the material parameter, setting constraint, hydrogen permeation performance index and hydrogen charging performance index, and then the correlation analysis for ring weld joint hydrogen permeation performance and hydrogen charging performance is realized based on the target model.The above technical solution realizes the accurate evaluation analysis of ring weld joint hydrogen permeation performance and hydrogen charging performance.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, apparatus, equipment, medium, and product for correlation analysis of hydrogen permeation performance and hydrogen charging performance. Background Technology

[0002] In many fields such as oil and gas transportation, pipeline steel ring welded joints face complex service environments. The permeation and filling of hydrogen has a crucial impact on their performance and may lead to serious problems such as hydrogen-induced cracking, threatening the safe operation of pipelines.

[0003] However, existing technologies lack systematic and comprehensive analytical methods for the correlation between hydrogen permeation and hydrogen charging performance of ring welded joints, making it difficult to accurately grasp their underlying mechanisms. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, medium, and product for correlation analysis of hydrogen permeation performance and hydrogen charging performance, enabling accurate evaluation and analysis of the hydrogen permeation performance and hydrogen charging performance of ring welded joints.

[0005] In a first aspect, embodiments of this disclosure provide a method for correlation analysis between hydrogen permeation performance and hydrogen charging performance, including:

[0006] Under set constraints, hydrogen permeation performance test data is obtained based on hydrogen permeation performance parameters, and hydrogen permeation performance index of the ring weld joint is determined based on the hydrogen permeation performance test data.

[0007] Under set constraints, hydrogen charging performance test data is obtained based on hydrogen charging performance parameters, and hydrogen charging performance indicators of the ring weld joint are determined based on the hydrogen charging performance test data.

[0008] The material parameters of the ring welded joint are obtained. Based on the material parameters, set constraints, hydrogen permeation performance index and hydrogen filling performance index, a target model is established. Then, based on the target model, a correlation analysis of the hydrogen permeation performance and hydrogen filling performance of the ring welded joint is carried out.

[0009] Secondly, embodiments of this disclosure provide a correlation analysis device for hydrogen permeation performance and hydrogen charging performance, comprising:

[0010] The hydrogen permeation performance analysis module is used to obtain hydrogen permeation performance test data based on hydrogen permeation performance parameters under set constraints, and to determine the hydrogen permeation performance index of the ring weld joint based on the hydrogen permeation performance test data.

[0011] The hydrogen charging performance analysis module is used to obtain hydrogen charging performance test data based on hydrogen charging performance parameters under set constraints, and to determine the hydrogen charging performance index of the ring weld joint based on the hydrogen charging performance test data.

[0012] The correlation analysis module is used to obtain the material parameters of the ring weld joint, establish a target model based on the material parameters, set constraints, hydrogen permeation performance index and hydrogen filling performance index, and then perform correlation analysis on the hydrogen permeation performance and hydrogen filling performance of the ring weld joint based on the target model.

[0013] Thirdly, embodiments of this disclosure provide an electronic device, including:

[0014] At least one processor; and

[0015] A memory that is communicatively connected to at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor can perform a method for analyzing the correlation between hydrogen permeation performance and hydrogen charging performance provided in the first aspect embodiment above.

[0017] Fourthly, embodiments of this disclosure provide a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the correlation analysis method for hydrogen permeation performance and hydrogen charging performance provided in the first aspect of the embodiments described above.

[0018] Fifthly, this disclosure provides a computer program product, which includes a computer program that, when executed by a processor, implements a method for correlation analysis of hydrogen permeation performance and hydrogen charging performance provided in the first aspect embodiment.

[0019] This invention discloses a method, apparatus, device, medium, and product for correlation analysis of hydrogen permeation performance and hydrogen filling performance. The method includes: acquiring hydrogen permeation performance test data based on hydrogen permeation performance parameters under set constraints; determining the hydrogen permeation performance index of a ring-welded joint based on the hydrogen permeation performance test data; acquiring hydrogen filling performance test data based on hydrogen filling performance parameters under set constraints; determining the hydrogen filling performance index of the ring-welded joint based on the hydrogen filling performance test data; acquiring the material parameters of the ring-welded joint; establishing a target model based on the material parameters, set constraints, hydrogen permeation performance index, and hydrogen filling performance index; and then performing correlation analysis of the hydrogen permeation performance and hydrogen filling performance of the ring-welded joint based on the target model. This technical solution enables accurate evaluation and analysis of the hydrogen permeation performance and hydrogen filling performance of the ring-welded joint, thereby predicting its safety performance in actual use, helping to avoid engineering accidents caused by hydrogen embrittlement, and improving the safety and reliability of engineering projects.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of a correlation analysis method between hydrogen permeation performance and hydrogen charging performance provided in Embodiment 1 of the present invention;

[0023] Figure 2 This is a flowchart of a correlation analysis method between hydrogen permeation performance and hydrogen charging performance provided in Embodiment 2 of the present invention;

[0024] Figure 3 This is a schematic diagram of the structure of a correlation analysis device for hydrogen permeation performance and hydrogen charging performance provided in Embodiment 3 of the present invention;

[0025] Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first," "second," and "target," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] Example 1

[0029] Figure 1 This is a flowchart of a correlation analysis method for hydrogen permeation performance and hydrogen charging performance provided in Embodiment 1 of the present invention. This embodiment can be applied to the situation of performing correlation analysis on hydrogen permeation hydrogen energy and hydrogen charging performance of ring welded joints. The method can be executed by a correlation analysis device for hydrogen permeation performance and hydrogen charging performance, which can be implemented in hardware and / or software.

[0030] like Figure 1 As shown, the method includes:

[0031] S101. Under set constraints, obtain hydrogen permeation performance test data based on hydrogen permeation performance parameters, and determine the hydrogen permeation performance index of the ring weld joint based on the hydrogen permeation performance test data.

[0032] In this embodiment, the constraints can be understood as pre-defined experimental environment and conditions for obtaining hydrogen permeation performance test data and hydrogen charging performance test data of the ring weld joint. Since this invention focuses on the process of welding pipeline steel under different soil environments and how to deal with possible interference types, the constraints at least include the material type, welding process, sampling location, soil environment, and interference type for the ring weld joint. The material type includes pipeline steel; for example, X70 and X80 grade pipeline steels, which are widely used in oil and gas transportation and are favored for their high strength and good weldability. The welding process includes automatic welding and semi-automatic welding; automatic welding is typically used in large-scale, high-efficiency production environments, providing stable and consistent weld quality; semi-automatic welding is used in special cases, such as in situations with limited space or complex welding positions, allowing operators greater flexibility and control. Sampling locations included root welds, filler welds, and capping welds. The root weld, the first layer of the weld, plays a decisive role in the overall weld quality. The filler weld, performed after the root weld, fills the weld to the required dimensions. The capping weld, the final layer, significantly impacts the weld's appearance and corrosion resistance. Precisely locating each welding area helps to understand the permeation and filling characteristics of hydrogen at different parts of the joint, providing a basis for targeted improvements. Soil environments included low-salt loam, medium-salt clay, and high-salt sand. These soil types exhibit varying degrees of corrosivity to pipeline steel; low-salt loam is less corrosive, while medium-salt clay and high-salt sand are more corrosive. Therefore, additional anti-corrosion measures are required when welding pipeline steel in these environments. The sampling closely approximates real-world working conditions, allowing experimental results to directly guide actual pipeline construction and maintenance, reducing risks caused by environmental factors. Interference types include dynamic DC interference from the subway, high-voltage DC interference, AC interference, and mixed AC / DC interference. These interferences may originate from nearby power systems or subway systems, affecting the current during the welding process and thus impacting weld quality. Therefore, understanding and addressing these interferences is crucial for ensuring weld quality. A comprehensive investigation of changes in hydrogen permeation and charging performance under external interference is necessary to provide proactive solutions for pipeline safety issues in complex electromagnetic environments. Understandably, setting constraints may also include sample preparation (i.e., the ring weld joint sample), hydrogen purity, and calibration of testing equipment.

[0033] Hydrogen permeation performance parameters can be understood as the variable parameters in the hydrogen permeation performance testing process. These parameters are crucial for ensuring the accuracy and repeatability of test results and include at least hydrogen permeation time, hydrogen permeation temperature, and hydrogen permeation pressure. Hydrogen permeation time refers to the time required for hydrogen gas to permeate through the material and reach a stable state. This time parameter is essential for evaluating the material's hydrogen permeation rate and its ability to reach equilibrium. Hydrogen permeation temperature refers to the ambient temperature of the material during the test, as temperature affects the velocity of hydrogen molecules and the microstructure of the material, thus influencing hydrogen permeation performance. Hydrogen permeation pressure refers to the pressure exerted by hydrogen gas on the material surface, which directly relates to the driving force for hydrogen molecules to penetrate the material.

[0034] Hydrogen permeation performance test data can be understood as test data obtained by measuring hydrogen permeation performance parameters under set constraints, including at least the trace density and intensity of hydrogen elemental characteristic spectral lines after the hydrogen microprinting reagent reacts with hydrogen. Hydrogen permeation performance indices can be understood as performance indices related to hydrogen permeation of the ring weld joint obtained through relevant calculations based on the hydrogen permeation performance test data, including at least the subsurface hydrogen concentration and hydrogen diffusion coefficient of the ring weld joint.

[0035] Specifically, this involves acquiring hydrogen permeability performance test data obtained under defined constraints based on hydrogen permeability performance parameters. This data can include: measuring the trace density after the reaction of hydrogen microprinting reagents with hydrogen using Hydrogen Microprinting Technique (HMT), and measuring the intensity of characteristic hydrogen spectral lines using Auger Electron Spectroscopy (AES). Hydrogen microprinting is a method to evaluate the hydrogen permeability of materials by utilizing the traces left after the reaction of hydrogen with the material. By measuring the trace density after the reaction of hydrogen microprinting reagents with hydrogen, the depth and distribution of hydrogen permeation in the material can be obtained. AES is a surface analysis technique that analyzes the elemental composition and chemical state of materials by measuring the Auger electrons emitted from the material surface. AES provides the intensity of characteristic hydrogen spectral lines, reflecting the concentration and distribution of hydrogen on the material surface. Combining these hydrogen permeability test data allows for a comprehensive evaluation of the material's hydrogen permeability, providing a scientific basis for material selection and application. The subsurface hydrogen concentration of the ring weld joint is determined based on the trace density and characteristic spectral intensity of hydrogen in the hydrogen permeability test data. Then, under the constraints of initial and boundary conditions, the hydrogen diffusion coefficient of the ring weld joint is determined based on the subsurface hydrogen concentration, thus obtaining a hydrogen permeability performance index that includes the subsurface hydrogen concentration and the hydrogen diffusion coefficient.

[0036] S102. Under set constraints, obtain hydrogen charging performance test data based on hydrogen charging performance parameters, and determine the hydrogen charging performance index of the ring weld joint based on the hydrogen charging performance test data.

[0037] In this embodiment, hydrogen charging performance parameters can be understood as variable parameters in the hydrogen charging performance testing process. These parameters are crucial for ensuring the accuracy and repeatability of the test results and include at least hydrogen charging time, hydrogen charging temperature, and current density. Hydrogen charging time refers to the duration during which hydrogen is introduced into the material or battery system during the test. The length of the charging time affects the total amount of hydrogen absorbed by the material and therefore needs to be determined based on the specific experimental purpose and material characteristics. Hydrogen charging temperature is an important factor affecting the solubility and diffusion rate of hydrogen in the material. Under different temperature conditions, the material's ability to absorb hydrogen may vary significantly; therefore, selecting an appropriate hydrogen charging temperature is crucial for the test results. In experiments involving electrochemical hydrogen charging, current density is a key parameter controlling the hydrogen charging rate. The magnitude of the current density directly affects the rate of hydrogen generation on the electrode surface, thus affecting the hydrogen charging performance of the material.

[0038] Hydrogen charging performance test data can be understood as test data obtained by measuring hydrogen charging performance parameters under set constraints. This data includes at least the hydrogen desorption peak area, hydrogen volume, and mass change during physical adsorption. It may also include the hydrogen content calculated based on the hydrogen desorption peak area and hydrogen volume, and obtained after chemical extraction. Hydrogen charging performance indicators can be understood as performance indicators related to hydrogen charging of ring-welded joints obtained through relevant calculations based on hydrogen charging performance test data. These indicators include at least the diffusible hydrogen content and the trapped hydrogen content.

[0039] Specifically, hydrogen charging performance test data is obtained when hydrogen charging performance tests are conducted based on hydrogen charging performance parameters under set constraints. This data can include: hydrogen desorption peak area detected by thermal desorption spectroscopy (TDS); hydrogen volume obtained by gas analysis; hydrogen content obtained by chemical extraction; and mass change during physical adsorption measured by physical adsorption techniques. Thermal desorption spectroscopy can detect the amount of hydrogen released during heating, and the hydrogen desorption peak area reflects the amount and stability of hydrogen stored in the material. Gas analysis measures the volume of hydrogen released into the environment during hydrogen charging, helping to understand the dynamics of hydrogen absorption and release under specific conditions. Chemical extraction can be used to determine the dissolved hydrogen content in the material, releasing hydrogen through chemical treatment and quantifying it using appropriate analytical methods. Physical adsorption can measure the mass change of the material during hydrogen charging; an increase in mass reflects the amount of hydrogen absorbed, while a decrease in mass may indicate the release of hydrogen. The hydrogen charging performance test data obtained through the above-mentioned technical means can comprehensively evaluate the hydrogen charging performance of materials or battery systems, including hydrogen absorption capacity, storage stability, and hydrogen charging and discharging kinetics. Based on the hydrogen desorption peak area and hydrogen volume in the hydrogen charging performance test data, the diffusible hydrogen content of the ring-welded joint is calculated. The diffusible hydrogen content is then chemically extracted to obtain the extracted hydrogen content. Based on the extracted hydrogen content and the mass change during physical adsorption in the hydrogen charging performance test data, the trapped hydrogen content is calculated. Finally, a hydrogen charging performance index including both diffusible and trapped hydrogen content is obtained.

[0040] S103. Obtain the material parameters of the ring weld joint, establish a target model based on the material parameters, set constraints, hydrogen permeation performance index and hydrogen filling performance index, and then perform correlation analysis on the hydrogen permeation performance and hydrogen filling performance of the ring weld joint based on the target model.

[0041] In this embodiment, the material parameters of the ring weld joint can be understood as the material composition and microstructure parameters of the ring weld joint, including at least: the phase type, morphology, size, and distribution of the ring weld joint; the chemical composition and elemental distribution of the ring weld joint; and the hydrogen enrichment location and distribution of the ring weld joint. The target model can be understood as a machine learning model used to perform correlation analysis on the hydrogen permeation performance and hydrogen charging performance of the ring weld joint.

[0042] Specifically, the material parameters of the ring weld joint are obtained. These parameters are derived through analysis of the ring weld joint, including: metallographic analysis to determine the phase types, morphology, size, and distribution; electron backscatter diffraction (EBSD) analysis to determine the crystal orientation, grain size distribution, and size and angle of grain boundaries; atomic emission spectrometry (AES) analysis to determine the chemical composition and elemental distribution; and hydrogen microimprint analysis to determine the hydrogen enrichment locations and distribution. In-depth analysis of the material composition and microstructure of the ring weld joint is a crucial step in ensuring weld quality and performance. Through a series of precise analytical techniques, the microscopic characteristics of the ring weld joint can be understood in detail, providing a scientific basis for optimizing the welding process and improving material properties. First, metallographic analysis is a crucial tool for studying the microstructure of materials. Observation using a metallographic microscope allows for the identification of phases in the weld joint, revealing their morphology, size, and distribution. This helps in assessing potential defects during welding, such as porosity, inclusions, and cracks. Second, EBSD analysis provides detailed information on the crystal orientation of the weld joint. EBSD analysis yields grain size distribution maps and information on grain boundaries of varying sizes and angles. This data is essential for understanding the mechanical properties and fracture behavior of the weld joint, as grain boundary characteristics directly affect the material's strength and toughness. Third, atomic emission spectrometry (AES) is used to determine the chemical composition and elemental distribution of the weld joint. AES provides high-resolution surface chemical analysis, revealing the distribution of different elements in the weld joint, including the segregation of alloying elements and the formation of oxides. This is significant for evaluating the corrosion resistance and durability of the weld joint. Finally, hydrogen microprinting analysis is used to determine the location and distribution of hydrogen enrichment in the circumferential weld joint. Hydrogen diffusion and enrichment in metals can lead to hydrogen embrittlement and delayed crack formation, threatening the reliability of the weld joint. Hydrogen microprinting analysis provides a direct visual representation of hydrogen distribution within the weld joint, allowing for measures to reduce its impact and improve joint performance. Through metallographic analysis, electron backscatter diffraction analysis, atomic emission spectroscopy, and hydrogen microprinting analysis, a comprehensive understanding of the material composition and microstructure of the circumferential weld joint can be achieved, providing a scientific basis for improving welding processes and enhancing welding quality.

[0043] After obtaining the material parameters of the ring-welded joint, the material parameters, set constraints, hydrogen permeation performance index, and hydrogen filling performance index are preprocessed to obtain preprocessed material parameters, set constraints, hydrogen permeation performance index, and hydrogen filling performance index. The preprocessed material parameters and set constraints are transformed into feature vectors, and a machine learning model is established. Based on the preprocessed hydrogen permeation performance index, hydrogen filling performance index, and feature vectors, the machine learning model is trained and tested to obtain a complete target model, which is used to achieve the correlation analysis of hydrogen permeation performance and hydrogen filling performance of the ring-welded joint.

[0044] This invention provides a method for correlation analysis of hydrogen permeation performance and hydrogen charging performance. The method includes: acquiring hydrogen permeation performance test data based on hydrogen permeation performance parameters under set constraints; determining the hydrogen permeation performance index of the ring-welded joint based on the hydrogen permeation performance test data; acquiring hydrogen charging performance test data based on hydrogen charging performance parameters under set constraints; determining the hydrogen charging performance index of the ring-welded joint based on the hydrogen charging performance test data; acquiring the material parameters of the ring-welded joint; establishing a target model based on the material parameters, set constraints, hydrogen permeation performance index, and hydrogen charging performance index; and then performing a correlation analysis of the hydrogen permeation performance and hydrogen charging performance of the ring-welded joint based on the target model. This technical solution enables accurate evaluation and analysis of the hydrogen permeation performance and hydrogen charging performance of the ring-welded joint, thereby predicting its safety performance in actual use, helping to avoid engineering accidents caused by hydrogen embrittlement, and improving the safety and reliability of engineering projects.

[0045] Example 2

[0046] Figure 2 This is a flowchart of a method for correlation analysis of hydrogen permeation performance and hydrogen charging performance provided in Embodiment 2 of the present invention. This embodiment is a further optimization of any of the above embodiments and can be applied to the situation of correlation analysis of hydrogen permeation hydrogen energy and hydrogen charging performance of ring welded joints. The method can be executed by a correlation analysis device for hydrogen permeation performance and hydrogen charging performance, which can be implemented in hardware and / or software.

[0047] like Figure 2 As shown, the method includes:

[0048] S201. Obtain hydrogen permeation performance test data based on hydrogen permeation performance parameters under set constraints.

[0049] S202. Determine the target subsurface hydrogen concentration of the ring weld joint based on the trace density and hydrogen element characteristic spectral line intensity in the hydrogen permeation performance test data.

[0050] In this embodiment, the target subsurface hydrogen concentration can be understood as the subsurface hydrogen concentration of the ring weld joint obtained by combining trace density and the intensity of characteristic spectral lines of hydrogen. The subsurface hydrogen concentration refers to the content of hydrogen atoms or hydrogen molecules in a certain depth range (usually a few nanometers to a few micrometers) below the surface of the material. Due to the diffusion and trapping effect of hydrogen in the material, its concentration may have a significant gradient between the surface and the interior. The subsurface hydrogen concentration is one of the key parameters for assessing hydrogen permeation, hydrogen embrittlement risk and material performance degradation.

[0051] Specifically, to comprehensively evaluate the hydrogen permeation performance of the ring weld joint, key performance indicators were determined based on a series of hydrogen permeation performance test data. First, the corresponding subsurface hydrogen concentration was determined based on the trace density of the hydrogen microprinting reagent after reaction with hydrogen in the hydrogen permeation performance test data. The hydrogen microprinting reagent is a chemical substance that can react with hydrogen and form visible traces. By analyzing the density of these traces, the distribution and concentration level of hydrogen in the material can be inferred. Second, the corresponding subsurface hydrogen concentration was determined based on the intensity of the characteristic spectral lines of hydrogen in the hydrogen permeation performance test data. The intensity of the characteristic spectral lines of hydrogen is proportional to the hydrogen concentration; therefore, by analyzing these spectral intensities, the concentration information of hydrogen in the material can be obtained. Based on these two types of subsurface hydrogen concentrations, the overall subsurface hydrogen concentration of the ring weld joint can be comprehensively evaluated, and the final, more accurate target subsurface hydrogen concentration of the ring weld joint can be calculated.

[0052] Optionally, the target subsurface hydrogen concentration of the ring weld joint can be determined based on the trace density and hydrogen elemental characteristic spectral line intensity in the hydrogen permeation performance test data, including:

[0053] S2021. Determine the hydrogen concentration of the first subsurface based on the trace density in the hydrogen permeation performance test data.

[0054] In this embodiment, the first subsurface hydrogen concentration can be understood as the subsurface hydrogen concentration of the ring weld joint determined based on the trace density after the hydrogen microprinting reagent reacts with hydrogen.

[0055] Specifically, the hydrogen concentration of the first subsurface of the ring weld joint is calculated based on CH(ρ)=aρ+b, where CH(ρ) represents the hydrogen concentration of the first subsurface; ρ represents the trace density after the hydrogen microprinting reagent reacts with hydrogen; and a and b represent constants obtained by calibration using standard samples.

[0056] S2022. Determine the hydrogen concentration of the second subsurface based on the intensity of the characteristic spectral lines of hydrogen in the hydrogen permeation performance test data.

[0057] In this embodiment, the second subsurface hydrogen concentration can be understood as the subsurface hydrogen concentration of the ring weld joint determined based on the intensity of the characteristic spectral lines of hydrogen.

[0058] Specifically, the hydrogen concentration of the second subsurface of the ring weld joint is calculated based on CH(I)=kI+l, where CH(I) represents the hydrogen concentration of the second subsurface, I represents the intensity of the characteristic spectral line of hydrogen, and k and l represent constants obtained by calibration using standard samples.

[0059] S2023. Determine the target subsurface hydrogen concentration of the ring weld joint based on the first subsurface hydrogen concentration and the second subsurface hydrogen concentration.

[0060] In this embodiment, the target subsurface hydrogen concentration of the ring weld joint is calculated based on CH = [CH(ρ) + CH(I)] / 2. A more comprehensive assessment of hydrogen permeation performance is achieved by integrating and analyzing the hydrogen concentration data from both regions.

[0061] S203. Under the constraints of initial and boundary conditions, determine the hydrogen diffusion coefficient of the ring weld joint based on the hydrogen concentration of the target subsurface.

[0062] In this embodiment, the initial condition can be understood as the hydrogen concentration distribution within the sample (ring weld joint). The boundary condition can be understood as the hydrogen concentration on the sample surface. The hydrogen diffusion coefficient is an important parameter for measuring the diffusion rate of hydrogen in a material. It reflects the ease with which hydrogen moves within the material and is used to evaluate the hydrogen diffusion performance of the ring weld joint. By testing the diffusion behavior of hydrogen in the ring weld joint, the hydrogen diffusion coefficient can be obtained, and thus the material's resistance to hydrogen permeation can be evaluated.

[0063] Specifically, the relationship between the hydrogen diffusion coefficient and the subsurface hydrogen concentration is as follows: In the formula, Let represent the target subsurface hydrogen concentration at time t and position (i, j), D represent the hydrogen diffusion coefficient, Δt represent the time step, and Δx represent the spatial step. Based on this relationship, the initial hydrogen diffusion coefficient can be determined. Initial conditions are determined as follows: At the start of the experiment, the hydrogen concentration distribution within the sample is... (i = 1, 2, ..., n; j = 1, 2, ..., m). Determine the boundary conditions under constant concentration: Based on Fick's first law, in the hydrogen diffusion scenario within the material, the hydrogen diffusion flux J (the number of hydrogen atoms passing through a unit area per unit time) and the rate of change of hydrogen concentration C along spatial position x (i.e., the concentration gradient) are related. The hydrogen concentration is directly proportional to the hydrogen diffusion coefficient D. For boundary nodes (including surface nodes), the relevant equation for the hydrogen concentration needs to be determined based on the boundary conditions. If the hydrogen concentration on the sample surface is constant at C0, then for surface nodes, the equation is: (j=1,2,...,m), when the boundary meets the flux condition and the surface flux is known to be J, determine the boundary conditions that satisfy the flux condition under Fick's first law, derive the discrete equation of the boundary node that satisfies Fick's first law based on the surface flux J, and use the discrete equation as the boundary condition.

[0064] Specifically, the derivation process of the discrete equation includes: converting the continuous concentration gradient... The concentration gradient is approximated by discrete node concentrations using finite differences. For example, in the one-dimensional case, if the boundary node is x0 and its adjacent internal nodes are x1, then the concentration gradient... It can be approximately expressed as (C1-C0) / Δx (C0 is the concentration of the boundary node, C1 is the concentration of the adjacent internal node, and Δx is the distance between nodes). Substituting this into Fick's first law J=-DC1-C0 / Δx, and then through operations such as rearranging and transforming, we can obtain the discrete equation for the concentration of the boundary node C0 (or C1).

[0065] Based on the initial and boundary conditions, the relationship between the hydrogen diffusion coefficient and the subsurface hydrogen concentration is solved iteratively to obtain the final hydrogen diffusion coefficient of the ring weld joint.

[0066] By following the steps above, the hydrogen permeation performance index of the ring weld joint can be accurately determined, providing a scientific basis for material selection and welding process optimization.

[0067] S204. Obtain hydrogen charging performance test data based on hydrogen charging performance parameters under set constraints.

[0068] S205. Determine the target diffusible hydrogen content of the ring weld joint based on the hydrogen desorption peak area and hydrogen volume in the hydrogen charging performance test data.

[0069] In this embodiment, the target diffusible hydrogen content can be understood as the diffusible hydrogen content of the ring weld joint obtained by combining the hydrogen desorption peak area and the hydrogen volume. The diffusible hydrogen content refers to the total amount of hydrogen atoms or molecules in the material that can move (diffuse) freely under specific temperature or stress conditions. This part of hydrogen has the greatest impact on the mechanical properties of the material (such as hydrogen embrittlement and hydrogen-induced cracking) and is an important parameter in engineering and materials science.

[0070] Specifically, to ensure the reliability of ring-welded joints in hydrogen-embrittlement-sensitive environments, their hydrogen charging performance must be accurately evaluated. The hydrogen desorption peak area detected by thermal desorption spectroscopy in the hydrogen charging performance test data directly reflects the content of diffusible hydrogen in the material. By comparing with a standard curve, the peak area can be converted into a numerical value of hydrogen content, which can then be expressed using C... d1 =mA+n determines the corresponding first diffusible hydrogen content, where C d1The first diffusible hydrogen content is represented by A, where A represents the hydrogen desorption peak area detected by the thermal desorption spectrometer, and m and n represent constants obtained through calibration with standard samples. During gas analysis, the sample is heated to a certain temperature, causing hydrogen to be released from the material. The hydrogen volume is measured using a gas analyzer, and the second diffusible hydrogen content can be calculated. Based on the hydrogen volume during gas analysis in the hydrogen charging performance test data, C... d2 =k v V determines the corresponding second diffusible hydrogen content, where C is the formula. d2 This indicates the second diffusible hydrogen content, where V represents the hydrogen volume during gas analysis, and k represents the hydrogen content. v This represents the conversion factor for hydrogen content per milliliter of hydrogen gas. Considering the measurement errors and applicability of the two diffusible hydrogen contents, to ensure the accuracy of the final result, based on the first and second diffusible hydrogen contents, the conversion factor is determined by C. d =(C d1 +C d2 ) / 2 Determine the target diffusible hydrogen content C of the ring weld joint d .

[0071] S206. Determine the target trap hydrogen content of the ring weld joint based on the extracted hydrogen content obtained after extracting the target diffusible hydrogen content and the mass change data in the hydrogen charging performance test data.

[0072] In this embodiment, the extracted hydrogen content can be understood as the hydrogen content obtained after chemically extracting the target diffusible hydrogen content. The target trapped hydrogen content can be understood as the trapped hydrogen content of the ring weld joint obtained by combining the extracted hydrogen content and mass change data. Trapped hydrogen refers to hydrogen atoms or molecules that are trapped by crystal defects in the material (such as dislocations, grain boundaries, vacancies, second-phase particles, etc.) and cannot diffuse freely at room temperature. Its content directly affects the hydrogen embrittlement sensitivity, mechanical properties, and durability of the material.

[0073] Specifically, hydrogen can be extracted from the ring-welded joint using chemical extraction methods to obtain the extracted hydrogen content. This can also be understood as extracting the target diffusible hydrogen content to obtain the extracted hydrogen content. Based on the extracted hydrogen content, corresponding hydrogen content analysis is performed to obtain the corresponding trapped hydrogen content. This process involves dissolving the sample in a suitable chemical solvent to release the hydrogen trapped within the material. In physical adsorption experiments, the trapped hydrogen content in the material can be inferred by measuring the mass change of the sample under specific conditions (such as heating or cooling). The increase or decrease in mass reflects the adsorption or release of hydrogen, and the corresponding trapped hydrogen content can be calculated based on the mass change during physical adsorption. Combining the two types of trapped hydrogen content, the total amount of trapped hydrogen in the ring-welded joint can be assessed to obtain the target trapped hydrogen content of the ring-welded joint. This helps to understand the distribution and capacity of hydrogen traps in the material, which is crucial for assessing hydrogen embrittlement risk and the long-term stability of the material.

[0074] The above steps can comprehensively evaluate the hydrogen charging performance of the ring weld joint, providing a scientific basis for material selection and welding process optimization.

[0075] Optionally, the target trap hydrogen content of the ring weld joint is determined based on the extracted hydrogen content obtained after extraction of the target diffusible hydrogen content and the mass change data in the hydrogen charging performance test data, including:

[0076] S2061. Extract the target diffusible hydrogen content to obtain the extracted hydrogen content.

[0077] In this embodiment, hydrogen is extracted from the ring weld joint, that is, the target diffusible hydrogen content is chemically extracted to obtain the extracted hydrogen content.

[0078] S2062. Determine the hydrogen content of the first trap based on the extracted hydrogen content.

[0079] In this embodiment, the first trap hydrogen content can be understood as the trap hydrogen content of the ring weld joint determined based on the extracted hydrogen content.

[0080] Specifically, through C t1 =C e / η is used to calculate the first trap hydrogen content of the ring weld joint, where C t1 C represents the hydrogen content of the first trap. e η represents the hydrogen content after chemical extraction, and η represents the extraction efficiency.

[0081] S2063. Determine the hydrogen content of the second trap based on the mass change data in the hydrogen charging performance test data.

[0082] In this embodiment, the second trapped hydrogen content can be understood as the trapped hydrogen content of the ring weld joint determined based on the mass change during physical adsorption.

[0083] Specifically, through C t2 =(Δm·N) A ·M H The hydrogen content of the second trap in the ring weld joint is calculated by C / S, where C t2 The value of N represents the hydrogen content in the second trap, Δm represents the mass change during physical adsorption, and N represents the mass content of the second trap. A M represents Avogadro's constant. H The molar mass of hydrogen is represented by , and S represents the adsorption surface area.

[0084] S2064. Determine the target trap hydrogen content of the ring weld joint based on the hydrogen content of the first trap and the hydrogen content of the second trap.

[0085] In this embodiment, through C t =(C t1 +Ct2 The target trap hydrogen content C of the ring weld joint is calculated by ) / 2. t .

[0086] S207. Preprocess the material parameters, set constraints, hydrogen permeation performance indicators, and hydrogen charging performance indicators.

[0087] In this embodiment, to establish a correlation model between the hydrogen permeation performance and hydrogen charging performance of the ring-welded joint, preprocessing of material parameters, constraints, hydrogen permeation performance indices, and hydrogen charging performance indices is first required. Preprocessing steps include data cleaning and outlier removal to ensure data quality and accuracy. Data cleaning involves removing duplicate records, correcting input errors, and filling in missing values. Outlier identification and removal are performed using statistical analysis methods, such as box plots, Z-scores, or interquartile range (IQR) methods, to exclude data points that may negatively impact model training.

[0088] S208. Convert the preprocessed material parameters and set constraints into feature vectors.

[0089] In this embodiment, the preprocessed material parameters and set constraints are transformed into feature vectors that can be processed by machine learning algorithms. The processing method includes at least standardization or normalization, and may also include feature selection techniques or dimensionality reduction techniques, such as Principal Component Analysis (PCA), to reduce the dimensionality of the data and extract the most important features.

[0090] S209. Establish a machine learning model. Based on the pre-processed hydrogen permeation performance indicators and hydrogen filling performance indicators, as well as the feature vector, train and test the machine learning model to obtain a complete target model.

[0091] In this embodiment, the machine learning model can be understood as a model built based on machine learning algorithms, including at least one of the following: linear regression, decision tree, random forest, support vector machine (SVM), and neural network. The preprocessed hydrogen permeation performance indicators and hydrogen filling performance indicators, along with the feature vectors, are divided into training, validation, and test sets to evaluate the model's generalization ability. The machine learning model is iteratively optimized and trained through cross-validation and parameter adjustment. Finally, the model's performance is evaluated using test set data to ensure that the model can accurately predict the correlation between hydrogen permeation and hydrogen filling performance. The machine learning model whose accuracy meets the requirements after testing on the test set is determined as the target model. This complete target model is used to predict the hydrogen permeation and hydrogen filling performance of new samples, providing a scientific basis for the design and optimization of the ring-welded joint.

[0092] This invention provides a method for analyzing the correlation between hydrogen permeation performance and hydrogen charging performance. The above technical solution, by setting detailed constraints, ensures the comprehensiveness and systematic nature of the test conditions, which helps to more accurately simulate actual working conditions and improve the reliability and applicability of test results. By setting hydrogen permeation performance test parameters and hydrogen charging performance test parameters, and determining the corresponding performance indicators, the hydrogen permeation and hydrogen charging performance of the ring weld joint can be evaluated more accurately, which is crucial for predicting and controlling the hydrogen embrittlement risk of the ring weld joint in actual use. In-depth analysis of the material parameters of the ring weld joint helps to reveal the relationship between hydrogen permeation and hydrogen charging performance and the essential properties of the material, providing a scientific basis for optimizing welding material selection and improving welding processes. Based on machine learning algorithms, the set constraints, hydrogen permeation performance indicators, hydrogen charging performance indicators, and material parameters are comprehensively preprocessed, and a correlation analysis model for the hydrogen permeation and hydrogen charging performance of the ring weld joint is established, realizing intelligent prediction of the hydrogen permeation and hydrogen charging performance of the ring weld joint, providing strong support for engineering design, material selection, and process optimization. The analytical method provided by this invention allows for a more accurate assessment of the hydrogen permeation and hydrogen bridging performance of ring welded joints, thereby predicting their safety performance in practical use. This helps to avoid engineering accidents caused by hydrogen embrittlement and improves the safety and reliability of engineering projects. Furthermore, by optimizing welding materials and processes, production costs can be reduced, increasing economic efficiency.

[0093] Example 3

[0094] Figure 3 This is a schematic diagram of the structure of a correlation analysis device for hydrogen permeation performance and hydrogen charging performance provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes:

[0095] The hydrogen permeation performance analysis module 31 is used to obtain hydrogen permeation performance test data based on hydrogen permeation performance parameters under set constraints, and to determine the hydrogen permeation performance index of the ring weld joint based on the hydrogen permeation performance test data.

[0096] The hydrogen charging performance analysis module 32 is used to obtain hydrogen charging performance test data based on hydrogen charging performance parameters under set constraints, and to determine the hydrogen charging performance index of the ring weld joint based on the hydrogen charging performance test data.

[0097] The correlation analysis module 33 is used to obtain the material parameters of the ring weld joint, establish a target model based on the material parameters, set constraints, hydrogen permeation performance index and hydrogen filling performance index, and then realize the correlation analysis of hydrogen permeation performance and hydrogen filling performance of the ring weld joint based on the target model.

[0098] The technical solution employs a correlation analysis device for hydrogen permeation performance and hydrogen charging performance to achieve accurate evaluation and analysis of the hydrogen permeation performance and hydrogen charging performance of the ring weld joint.

[0099] Optional, the hydrogen permeation performance analysis module 31 includes:

[0100] The subsurface hydrogen concentration determination unit is used to determine the target subsurface hydrogen concentration of the ring weld joint based on the trace density and hydrogen element characteristic spectral line intensity in the hydrogen permeation performance test data.

[0101] The hydrogen diffusion coefficient determination unit is used to determine the hydrogen diffusion coefficient of the ring weld joint based on the hydrogen concentration of the target subsurface under initial and boundary condition constraints.

[0102] Optional, a subsurface hydrogen concentration determination unit, specifically used for:

[0103] The hydrogen concentration of the first subsurface is determined based on the trace density in the hydrogen permeation performance test data.

[0104] The hydrogen concentration of the second subsurface is determined based on the intensity of the characteristic spectral lines of hydrogen in the hydrogen permeation performance test data.

[0105] The target subsurface hydrogen concentration of the ring weld joint is determined based on the first subsurface hydrogen concentration and the second subsurface hydrogen concentration.

[0106] Optional hydrogen charging performance analysis module 32 includes:

[0107] A diffusible hydrogen content determination unit is used to determine the target diffusible hydrogen content of the ring weld joint based on the hydrogen desorption peak area and hydrogen volume in the hydrogen charging performance test data.

[0108] The trap hydrogen content determination unit is used to determine the target trap hydrogen content of the ring weld joint based on the extracted hydrogen content obtained after extracting the target diffusible hydrogen content and the mass change data in the hydrogen charging performance test data.

[0109] Optionally, a trap hydrogen content determination unit is used specifically for:

[0110] The target diffusible hydrogen content is extracted to obtain the extracted hydrogen content;

[0111] The hydrogen content of the first trap is determined based on the extracted hydrogen content;

[0112] The hydrogen content of the second trap is determined based on the mass change data in the hydrogen charging performance test data.

[0113] The target trap hydrogen content of the ring weld joint is determined based on the first trap hydrogen content and the second trap hydrogen content.

[0114] Optional, the association analysis module 33 is specifically used for:

[0115] The material parameters, constraints, hydrogen permeability performance indicators, and hydrogen charging performance indicators are preprocessed.

[0116] The preprocessed material parameters and set constraints are transformed into feature vectors;

[0117] A machine learning model is established, and based on the preprocessed hydrogen permeation performance index and hydrogen filling performance index, as well as the feature vector, the machine learning model is trained and tested to obtain a complete target model.

[0118] The correlation analysis device for hydrogen permeation performance and hydrogen charging performance provided in the embodiments of the present invention can execute the correlation analysis method for hydrogen permeation performance and hydrogen charging performance provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0119] Example 4

[0120] Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0121] like Figure 4 As shown, the electronic device 40 includes at least one processor 41 and a memory, such as a read-only memory (ROM) 42 or a random access memory (RAM) 43, communicatively connected to the at least one processor 41. The memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes based on the computer program stored in the ROM 42 or loaded into the RAM 43 from storage unit 48. The RAM 43 may also store various programs and data required for the operation of the electronic device 40. The processor 41, ROM 42, and RAM 43 are interconnected via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0122] Multiple components in electronic device 40 are connected to I / O interface 45, including: input unit 46, such as keyboard, mouse, etc.; output unit 47, such as various types of monitors, speakers, etc.; storage unit 48, such as disk, optical disk, etc.; and communication unit 49, such as network card, modem, wireless transceiver, etc. Communication unit 49 allows electronic device 40 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0123] Processor 41 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 41 performs the various methods and processes described above, such as the correlation analysis method between hydrogen permeation performance and hydrogen filling performance.

[0124] In some embodiments, the method for correlation analysis of hydrogen permeation performance and hydrogen charging performance can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 40 via ROM 42 and / or communication unit 49. When the computer program is loaded into RAM 43 and executed by processor 41, one or more steps of the method for correlation analysis of hydrogen permeation performance and hydrogen charging performance described above can be performed. Alternatively, in other embodiments, processor 41 can be configured to perform the method for correlation analysis of hydrogen permeation performance and hydrogen charging performance by any other suitable means (e.g., by means of firmware).

[0125] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0126] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0127] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0128] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0129] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0130] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0131] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0132] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for analyzing the correlation between hydrogen permeation performance and hydrogen charging performance, characterized in that, include: Under set constraints, hydrogen permeation performance test data is obtained based on hydrogen permeation performance parameters, and hydrogen permeation performance index of the ring weld joint is determined based on the hydrogen permeation performance test data. Under set constraints, hydrogen charging performance test data is obtained based on hydrogen charging performance parameters, and hydrogen charging performance indicators of the ring weld joint are determined based on the hydrogen charging performance test data. The material parameters of the ring welded joint are obtained. Based on the material parameters, set constraints, hydrogen permeation performance index and hydrogen filling performance index, a target model is established. Then, based on the target model, a correlation analysis of the hydrogen permeation performance and hydrogen filling performance of the ring welded joint is carried out.

2. The method according to claim 1, characterized in that, The determination of hydrogen permeation performance indicators of the ring weld joint based on the hydrogen permeation performance test data includes: The target subsurface hydrogen concentration of the ring weld joint is determined based on the trace density and hydrogen element characteristic spectral line intensity in the hydrogen permeation performance test data. Under initial and boundary conditions, the hydrogen diffusion coefficient of the ring weld joint is determined based on the hydrogen concentration of the target subsurface.

3. The method according to claim 2, characterized in that, Determining the target subsurface hydrogen concentration of the ring weld joint based on the trace density and hydrogen element characteristic spectral line intensity in the hydrogen permeability test data includes: The hydrogen concentration of the first subsurface is determined based on the trace density in the hydrogen permeation performance test data. The hydrogen concentration of the second subsurface is determined based on the intensity of the characteristic spectral lines of hydrogen in the hydrogen permeation performance test data. The target subsurface hydrogen concentration of the ring weld joint is determined based on the first subsurface hydrogen concentration and the second subsurface hydrogen concentration.

4. The method according to claim 1, characterized in that, The determination of the hydrogen charging performance index of the ring weld joint based on the hydrogen charging performance test data includes: The target diffusible hydrogen content of the ring weld joint is determined based on the hydrogen desorption peak area and hydrogen volume in the hydrogen charging performance test data. The target trap hydrogen content of the ring weld joint is determined based on the extracted hydrogen content obtained after extracting the target diffusible hydrogen content and the mass change data in the hydrogen charging performance test data.

5. The method according to claim 4, characterized in that, The determination of the target trap hydrogen content of the ring weld joint based on the extracted hydrogen content obtained after extracting the target diffusible hydrogen content and the mass change data in the hydrogen charging performance test data includes: The target diffusible hydrogen content is extracted to obtain the extracted hydrogen content; The hydrogen content of the first trap is determined based on the extracted hydrogen content; The hydrogen content of the second trap is determined based on the mass change data in the hydrogen charging performance test data. The target trap hydrogen content of the ring weld joint is determined based on the first trap hydrogen content and the second trap hydrogen content.

6. The method according to claim 1, characterized in that, The establishment of the target model based on the material parameters, set constraints, hydrogen permeability performance indicators, and hydrogen charging performance indicators includes: The material parameters, constraints, hydrogen permeability performance indicators, and hydrogen charging performance indicators are preprocessed. The preprocessed material parameters and set constraints are transformed into feature vectors; A machine learning model is established, and based on the preprocessed hydrogen permeation performance index and hydrogen filling performance index, as well as the feature vector, the machine learning model is trained and tested to obtain a complete target model.

7. A device for analyzing the correlation between hydrogen permeation performance and hydrogen charging performance, characterized in that, include: The hydrogen permeation performance analysis module is used to obtain hydrogen permeation performance test data based on hydrogen permeation performance parameters under set constraints, and to determine the hydrogen permeation performance index of the ring weld joint based on the hydrogen permeation performance test data. The hydrogen charging performance analysis module is used to obtain hydrogen charging performance test data based on hydrogen charging performance parameters under set constraints, and to determine the hydrogen charging performance index of the ring weld joint based on the hydrogen charging performance test data. The correlation analysis module is used to obtain the material parameters of the ring weld joint, establish a target model based on the material parameters, set constraints, hydrogen permeation performance index and hydrogen filling performance index, and then perform correlation analysis on the hydrogen permeation performance and hydrogen filling performance of the ring weld joint based on the target model.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform a correlation analysis method for hydrogen permeation performance and hydrogen charging performance according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute a method for analyzing the correlation between hydrogen permeation performance and hydrogen charging performance as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements a correlation analysis method for hydrogen permeation performance and hydrogen charging performance according to any one of claims 1-6.

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