Storage medium, structure optimization method, device and equipment of hydrogen detection probe

Abstract

The application discloses a storage medium, a structure optimization method, device and equipment of a hydrogen detection probe, wherein the method comprises the following steps: determining performance influencing factors and performance evaluation indexes of the hydrogen detection probe; the performance influencing factors comprise structure parameter items as direct influencing factors, and diffusion synergy degree and shape diffusivity as indirect influencing factors; the performance evaluation indexes comprise cumulative hydrogen touch volume and hydrogen touch uniformity of the hydrogen detection probe; a plurality of sets of experimental data are obtained through a plurality of simulated hydrogen leakage experiments; a probe performance prediction model is constructed by taking the experimental data as modeling data; and the optimized structure parameter data is obtained through the probe performance prediction model according to the set target performance evaluation index. In the application, the optimized structure parameter data can be obtained according to the set target performance evaluation index, and the structure parameters required by the hydrogen detection probe with high precision can be obtained.

Description

Technical Field

[0001] This invention relates to the field of hydrogen detection probe technology, and particularly to storage media, methods, apparatus and equipment for optimizing the structure of hydrogen detection probes. Background Technology

[0002] Hydrogen energy is the most important industrial raw material and a clean energy source and good energy carrier in the energy transition process. It has the characteristics of being clean and efficient, energy-storable, transportable, and having a wide range of applications. At present, the overall demand for hydrogen continues to grow. However, hydrogen is a toxic, flammable and explosive gas. Leaks can cause great harm to the normal production of enterprises and the health of personnel. Therefore, safety issues in the storage and transportation of hydrogen are particularly important.

[0003] Fiber optic hydrogen detection devices are gaining increasing attention due to their greater sensitivity to gases and immunity to crosstalk from other gases. To ensure adequate contact with leaking hydrogen, fiber optic hydrogen detection probes are typically installed on hydrogen pipelines, near locations prone to leaks.

[0004] The inventors discovered through research that existing fiber optic hydrogen detection devices have at least the following drawbacks:

[0005] Fiber optic hydrogen detection devices have poor accuracy in measuring hydrogen leakage.

[0006] The information disclosed in this background section is intended only to enhance the understanding of the overall background of the invention and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this invention is to improve the accuracy of hydrogen detection probes in measuring hydrogen leakage.

[0008] This invention provides a method for optimizing the structure of a hydrogen detection probe, comprising the following steps:

[0009] S11. Determine the performance influencing factors and performance evaluation indicators of the hydrogen detection probe; the performance influencing factors include: structural parameters as direct influencing factors, and diffusion synergy and shape diffusivity as indirect influencing factors; the performance evaluation indicators include: the cumulative hydrogen contact amount and hydrogen contact uniformity of the hydrogen detection probe.

[0010] S12. Multiple sets of experimental data were obtained through repeated simulated hydrogen leakage experiments; the data items of the experimental data include the direct influencing factors, the indirect influencing factors, and the performance evaluation indicators.

[0011] S13. Using the experimental data as modeling data, construct a probe performance prediction model; the probe performance prediction model is used to generate the cumulative hydrogen touch amount and hydrogen touch uniformity of the hydrogen detection probe through preset structural parameter data.

[0012] S14. Based on the set target performance evaluation index, the optimized structural parameter data are obtained through the probe performance prediction model.

[0013] Preferably, in this embodiment of the invention, solving the diffusion cooperation degree includes:

[0014] The energy conservation equation for the laminar boundary layer is as follows:

[0015]

[0016] Where λ is the thermal conductivity of the fluid medium; ρ is the density; C p y is the specific heat capacity; u is the axial velocity; v is the radial velocity; x is the axial distance; y is the radial distance; T is the temperature.

[0017] Integrating both sides of the energy conservation equation in the domain of discussion yields:

[0018]

[0019] Where, δ t,x This represents the thickness of the thermal boundary layer at location x;

[0020] Rewrite the convection term on the left-hand side of the above equation in vector form:

[0021]

[0022] Introduce another dimensionless variable:

[0023]

[0024] Substituting the dimensionless variable and rearranging, we get:

[0025]

[0026] Among them, Re x Nu x The definition is the same as in typical boundary layer flow analysis; the integrand can be written as...

[0027]

[0028] Where β is the angle between the velocity vector and the temperature gradient vector.

[0029] Preferably, in this embodiment of the invention, it includes:

[0030] The shape diffusivity is a characteristic quantity of the angle between the edge of the hydrogen diffusion cloud and the diffusion line at the center of the cloud, used to characterize the diffusivity of the shape.

[0031] Preferably, in this embodiment of the invention, a hydrogen detection probe suitable for micro / nano optical fibers is used.

[0032] Preferably, in this embodiment of the invention, the selection range of the structural parameter items includes:

[0033] The inlet and outlet shapes of the hydrogen detection probe, the inlet and outlet diameters of the hydrogen detection probe, the inlet and outlet distance of the hydrogen detection probe, the gas flow rate, the shape of the hydrogen detection probe, the specifications of the hydrogen detection probe, and the position of the micro-nano optical fiber.

[0034] Preferably, in this embodiment of the invention, the calculation of the cumulative hydrogen touch amount includes:

[0035] The mass of hydrogen absorbed by the micro-nano optical fiber is calculated based on the degree of color change of the hydrogen detection probe.

[0036] The cumulative hydrogen touch volume is obtained by calculating the ratio of the absorbed hydrogen mass to the hydrogen detection probe volume.

[0037] Preferably, in this embodiment of the invention, the hydrogen touch uniformity includes:

[0038] Time-based hydrogen touch uniformity and length-based hydrogen touch uniformity.

[0039] Preferably, in this embodiment of the invention, the optimized structural parameter data includes:

[0040] Structural parameter data corresponding to the target performance evaluation index.

[0041] In another aspect of the present invention, a structural optimization device for a hydrogen detection probe is also provided, comprising:

[0042] The modeling parameter determination unit is used to determine the performance influencing factors and performance evaluation indicators of the hydrogen detection probe; the performance influencing factors include: structural parameters as direct influencing factors, and diffusion synergy and shape diffusivity as indirect influencing factors; the performance evaluation indicators include: the cumulative hydrogen contact amount and hydrogen contact uniformity of the hydrogen detection probe.

[0043] The modeling data generation unit is used to obtain multiple sets of experimental data through multiple simulated hydrogen leakage experiments; the data items of the experimental data include the direct influencing factors, the indirect influencing factors, and the performance evaluation indicators.

[0044] The modeling unit is used to construct a probe performance prediction model using the experimental data as modeling data; the probe performance prediction model is used to generate the cumulative hydrogen touch amount and hydrogen touch uniformity of the hydrogen detection probe through preset structural parameter data.

[0045] The structural parameter data generation unit is used to obtain optimized structural parameter data through the probe performance prediction model based on the set target performance evaluation index.

[0046] Preferably, in this embodiment of the invention, solving the diffusion cooperation degree includes:

[0047] The energy conservation equation for the laminar boundary layer is as follows:

[0048]

[0049] Where λ is the thermal conductivity of the fluid medium; ρ is the density; C p y is the specific heat capacity; u is the axial velocity; v is the radial velocity; x is the axial distance; y is the radial distance; T is the temperature.

[0050] Integrating both sides of the energy conservation equation in the domain of discussion yields:

[0051]

[0052] Where, δ t,x This represents the thickness of the thermal boundary layer at location x;

[0053] Rewrite the convection term on the left-hand side of the above equation in vector form:

[0054]

[0055] Introduce another dimensionless variable:

[0056]

[0057] Substituting the dimensionless variable and rearranging, we get:

[0058]

[0059] Among them, Re x Nu x The definition is the same as in typical boundary layer flow analysis; the integrand can be written as...

[0060]

[0061] Where β is the angle between the velocity vector and the temperature gradient vector.

[0062] In another aspect of this invention, a structure optimization device for a hydrogen detection probe is also provided; the structure optimization device for the hydrogen detection probe includes a computer program stored on a medium, the computer program including program instructions, which, when executed by a computer, cause the computer to perform the methods described in the above aspects and achieve the same technical effect.

[0063] In another aspect of the present invention, a storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the various steps of the structural optimization method for the hydrogen detection probe as described in any of the preceding claims.

[0064] Compared with the prior art, the present invention has the following beneficial effects:

[0065] In existing technologies, to improve measurement accuracy, attention is generally paid to the installation position of the fiber optic hydrogen detection probe. This is achieved by installing the probe as close as possible to a location in the hydrogen pipeline where hydrogen is prone to leakage, ensuring sufficient contact between the probe and the leaking hydrogen. However, the inventors discovered that the measurement accuracy of the hydrogen detection probe is not only related to its installation position but also to its own structure. Therefore, in this invention, the structural parameters of the hydrogen detection probe have been optimized, resulting in a hydrogen detection probe with higher measurement accuracy. Specifically:

[0066] In this invention, on the one hand, some conventional structural parameters that are direct influencing factors are considered as performance influencing factors. On the other hand, diffusion coherence and shape diffusivity are also considered as indirect influencing factors affecting the accuracy of hydrogen detection; that is, diffusion coherence and shape diffusivity are also considered as influencing factors on the measurement accuracy of the hydrogen detection probe. Next, this invention obtains multiple sets of experimental data including various influencing factors and corresponding performance evaluation indicators through multiple simulated hydrogen leakage experiments. Then, using the experimental data as modeling data, a machine learning-based probe performance prediction model can be constructed through data training. Since the probe performance prediction model in this invention can generate corresponding cumulative hydrogen touch volume and hydrogen touch uniformity from the structural parameter data, the optimized structural parameter data can be obtained according to the set target performance evaluation indicators, thereby obtaining the structural parameters required for a high-precision hydrogen detection probe.

[0067] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it according to the contents of the specification, and to make the above and other objects, technical features and advantages of the present invention easier to understand, one or more preferred embodiments are listed below and described in detail with reference to the accompanying drawings. Attached Figure Description

[0068] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the 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.

[0069] Figure 1 This is a step diagram of the structural optimization method for the hydrogen detection probe described in this invention;

[0070] Figure 2 This is a schematic diagram of the structure of the hydrogen detection experimental platform described in this invention;

[0071] Figure 3 A schematic diagram of the internal structure of the hydrogen detection experimental platform described in this invention;

[0072] Figure 4 This is a schematic diagram of the structure optimization device for the hydrogen detection probe described in this invention;

[0073] Figure 5 This is a schematic diagram of the structure of the optimized hydrogen detection probe device described in this invention. Detailed Implementation

[0074] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings, but it should be understood that the scope of protection of the present invention is not limited to the specific embodiments.

[0075] Unless otherwise expressly stated, throughout the specification and claims, the term "comprising" or its variations such as "including" or "comprises" shall be understood to include the stated elements or components without excluding other elements or other components.

[0076] In this document, the terms "first," "second," etc., are used to distinguish two different elements or parts, and are not used to define specific positions or relative relationships. In other words, in some embodiments, the terms "first," "second," etc., can also be used interchangeably.

[0077] Example 1

[0078] To improve the measurement accuracy of hydrogen detection probes, such as Figure 1 As shown, this embodiment of the invention provides a method for optimizing the structure of a hydrogen detection probe, including the following steps:

[0079] S11. Determine the performance influencing factors and performance evaluation indicators of the hydrogen detection probe; the performance influencing factors include: structural parameters as direct influencing factors, and diffusion synergy and shape diffusivity as indirect influencing factors; the performance evaluation indicators include: the cumulative hydrogen contact amount and hydrogen contact uniformity of the hydrogen detection probe.

[0080] Through research, the inventors discovered that the measurement accuracy of a hydrogen detection probe is related not only to its installation location but also to its own structure. Therefore, in this embodiment of the invention, on the one hand, some conventional structural parameters that are direct influencing factors are considered as performance influencing factors; on the other hand, the inventors found that some specific physical quantities also synergistically affect the hydrogen detection effect. Therefore, diffusion synergy and shape diffusivity are also considered as indirect influencing factors affecting the accuracy of hydrogen detection. In other words, diffusion synergy and shape diffusivity are also considered as influencing factors on the measurement accuracy of the hydrogen detection probe.

[0081] When hydrogen enters the hydrogen detection probe, it moves randomly and touches the probe. The inventors discovered that the frequency of contact between the hydrogen and the probe under this random movement is not only related to the speed and direction of the probe's entry, but also to the change in the hydrogen's density due to temperature changes caused by heat transfer, which affects its upward trajectory. Therefore, in this embodiment of the invention, diffusion cooperability is also considered as one of the factors affecting the measurement accuracy of the hydrogen detection probe.

[0082] Since the diffusion mode of hydrogen gas is related to the inlet shape and inlet velocity when it enters the hydrogen detection probe with different shaped inlets (the same applies when hydrogen gas is discharged), in this embodiment of the invention, shape diffusivity is also considered as an influencing factor on the measurement accuracy of the hydrogen detection probe.

[0083] Specifically, in this embodiment of the invention, the formula for solving the diffusion cooperation degree may include:

[0084] The energy conservation equation for the laminar boundary layer is as follows:

[0085]

[0086] Where λ is the thermal conductivity of the fluid medium; ρ is the density; C p y is the specific heat capacity; u is the axial velocity; v is the radial velocity; x is the axial distance; y is the radial distance; T is the temperature.

[0087] Integrating both sides of the energy conservation equation in the domain of discussion yields:

[0088]

[0089] Where, δt,x This represents the thickness of the thermal boundary layer at location x;

[0090] Rewrite the convection term on the left-hand side of the above equation in vector form:

[0091]

[0092] Introduce another dimensionless variable:

[0093]

[0094] Substituting the dimensionless variable and rearranging, we get:

[0095]

[0096] Among them, Re x Nu x The definition is the same as in typical boundary layer flow analysis; the integrand can be written as...

[0097]

[0098] Where β is the angle between the velocity vector and the temperature gradient vector, which can be derived from formulas (5) and (6) to improve the dimensionless integral value. This can effectively enhance heat transfer. The physical meaning of this dimensionless integral lies in the sum of the intensity of dimensionless heat sources within the thermal boundary layer thickness at point x. Generally speaking, increasing the integrand... The numerical value can effectively enhance heat transfer. Under the condition that the velocity and temperature gradients are constant (or Re and Pr remain unchanged), reducing the angle between them can effectively increase the dimensionless integral value, thereby increasing the Nu value. x Increasing the angle between the velocity vector and the temperature gradient vector can enhance heat transfer. Therefore, during the heating process, the angle β between the velocity vector and the temperature gradient vector can be used to characterize the heat transfer effect, which is called the synergistic angle. According to formula (6), the size of the synergistic angle is inversely proportional to the heat transfer efficiency during jet heating.

[0099] In this embodiment of the invention, shape diffusivity is a characteristic quantity of the angle between the edge of the hydrogen diffusing cloud and the diffusion line at the center of the cloud, used to characterize the diffusivity of its shape. That is, the angle ε between the edge of the hydrogen diffusing cloud and the diffusion line at the center of the cloud is used as a characteristic quantity characterizing its shape diffusivity. It should be noted that the edge of the hydrogen diffusing cloud is a cone-like surface, and the angle ε is the average angle between the edge of the diffusing cloud and the diffusion line at the center of the cloud over a given period, and the magnitude of this angle ε changes over time.

[0100] In practical applications, the hydrogen detection probe in this embodiment of the invention can specifically be a hydrogen detection probe based on micro-nano optical fibers; the selection range of structural parameters of the hydrogen detection probe can include: the shape of the inlet and outlet of the hydrogen detection probe, the diameter of the inlet and outlet of the hydrogen detection probe, the distance between the inlet and outlet of the hydrogen detection probe, the gas flow rate, the shape of the hydrogen detection probe, the specifications of the hydrogen detection probe, and the position of the micro-nano optical fibers.

[0101] Furthermore, in this embodiment of the invention, the hydrogen touch uniformity may include: time-based hydrogen touch uniformity and length-based hydrogen touch uniformity; time-based hydrogen touch uniformity refers to the amount of hydrogen touched per unit time during the calculation of the cumulative hydrogen touch amount, from the time hydrogen begins to enter the hydrogen detection probe until the velocity field inside the hydrogen detection probe becomes uniform and the hydrogen concentration no longer changes, denoted as time-based hydrogen touch uniformity ρ. t The unit is g / L·s.

[0102] Length-based hydrogen touch uniformity refers to the amount of hydrogen touch per unit length of micro / nano fiber in the process of calculating the cumulative hydrogen touch amount, with the length of the micro / nano fiber in contact with hydrogen as the total length. This amount is denoted as ρ, the length-based hydrogen touch uniformity. L The unit is g / L·m.

[0103] S12. Multiple sets of experimental data were obtained through repeated simulated hydrogen leakage experiments; the data items of the experimental data include the direct influencing factors, the indirect influencing factors, and the performance evaluation indicators.

[0104] In this embodiment of the invention, multiple sets of experimental data including various influencing factors and corresponding performance evaluation indexes can be obtained through multiple simulated hydrogen leakage experiments.

[0105] In this embodiment of the invention, the calculation of the cumulative hydrogen touch amount may include the following specific process:

[0106] A layer of hydrogen-sensitive color-changing material is coated on the micro-nano optical fiber of the hydrogen detection probe. The mass of hydrogen absorbed by the micro-nano optical fiber, m, is calculated based on the degree of color change of the hydrogen-sensitive color-changing material; the volume of the hydrogen detection probe, V, is calculated based on the volume of the hydrogen detection probe. The cumulative amount of hydrogen touched is obtained by calculating the ratio of the mass of hydrogen absorbed to the volume of the hydrogen detection probe.

[0107] In this embodiment of the invention, hydrogen touch uniformity is divided into time-based hydrogen touch uniformity and length-based hydrogen touch uniformity. Time-based hydrogen touch uniformity refers to the amount of hydrogen touched per unit time during the calculation of cumulative hydrogen touch volume, from the moment hydrogen begins to enter the detection probe until the velocity field inside the probe becomes uniform and the hydrogen concentration no longer changes. This is called the time-based hydrogen touch uniformity ρ. t The unit is g / L·s.

[0108] Length-based hydrogen touch uniformity refers to the amount of hydrogen touch per unit length of micro / nano fiber during the calculation of cumulative hydrogen touch volume, taking the length of the micro / nano fiber in contact with hydrogen as the total length. This amount is called the length-based hydrogen touch uniformity ρ. L The unit is g / L·m.

[0109] In practical applications, a micro / nano optical fiber can be placed inside a hydrogen detection probe. When a hydrogen leak occurs, the leaking hydrogen will slowly enter the probe at a certain flow rate from the inlet, and the probe, once filled with hydrogen, will gradually discharge from the outlet. During this process, the micro / nano optical fiber gradually comes into contact with the hydrogen, and because the hydrogen distribution inside the probe is uneven, the concentration of hydrogen in contact with the micro / nano optical fiber also gradually changes. Therefore, the total amount of hydrogen that the micro / nano optical fiber comes into contact with during the period from when hydrogen begins to enter the probe until the velocity field inside the probe becomes uniform and the hydrogen concentration no longer changes is the cumulative hydrogen contact amount.

[0110] In this embodiment of the invention, the hydrogen detection experimental platform used to obtain corresponding experimental data references from the simulated hydrogen leakage experiment can... Figure 2 and Figure 3 Specifically, the hydrogen detection experimental platform may include: fume hood 1, explosion-proof gas cylinder cabinet 2, explosion-proof gas cylinder cabinet 3, explosion-proof gas cylinder cabinet 4, hydrogen cylinder 5, nitrogen cylinder 6, gas pipeline 7, switch valve 8, flow valve 9, pressure gauge 10, flow meter 11, gas alarm 12, exhaust port 13, gas pump 14, gas outlet 15, converter 16, gas rubber hose 17, gas inlet 18, and hydrogen detection probe 19.

[0111] S13. Using the experimental data as modeling data, construct a probe performance prediction model; the probe performance prediction model is used to generate the cumulative hydrogen touch amount and hydrogen touch uniformity of the hydrogen detection probe through preset structural parameter data.

[0112] In this embodiment of the invention, experimental data of each influencing factor and experimental data of the corresponding performance evaluation index are used as modeling data to construct a probe performance prediction model based on machine learning. In the process of constructing the probe performance prediction model, experimental data of several sets of influencing factors and experimental data of the corresponding performance evaluation index are put into the model, and the model can be appropriately modified according to the results to improve the adaptability, and finally the functional relationship between influencing factors and performance evaluation indexes based on the current data is obtained.

[0113] The probe performance prediction model in this embodiment of the invention can generate the corresponding cumulative hydrogen touch amount and hydrogen touch uniformity through structural parameter data.

[0114] S14. Based on the set target performance evaluation index, the optimized structural parameter data are obtained through the probe performance prediction model.

[0115] In this embodiment of the invention, optimized structural parameter data can be obtained through a probe performance prediction model based on the set target performance evaluation index, thereby obtaining the structural parameters required for a high-precision hydrogen detection probe.

[0116] Furthermore, in this embodiment of the invention, the optimized structural parameter data may include: structural parameter data corresponding to the target performance evaluation index; that is, the optimal structural parameter data of the hydrogen detection probe is obtained, thereby improving the detection accuracy of the hydrogen detection probe.

[0117] In summary, in this embodiment of the invention, a hydrogen detection probe with higher measurement accuracy is obtained by optimizing the structural parameters of the hydrogen detection probe. Specifically, this embodiment considers some conventional structural parameters as direct influencing factors, and also considers diffusion coherence and shape diffusivity as indirect influencing factors affecting hydrogen detection accuracy; that is, diffusion coherence and shape diffusivity are also considered as influencing factors on the measurement accuracy of the hydrogen detection probe. Next, this embodiment obtains multiple sets of experimental data including various influencing factors and corresponding performance evaluation indicators through multiple simulated hydrogen leakage experiments. Then, using the experimental data as modeling data, a probe performance prediction model based on machine learning can be constructed through data training. Since the probe performance prediction model in this embodiment can generate corresponding cumulative hydrogen touch volume and hydrogen touch uniformity from the structural parameter data, the optimized structural parameter data can be obtained based on the set target performance evaluation indicators through the probe performance prediction model, thereby obtaining the structural parameters required for a high-precision hydrogen detection probe.

[0118] Example 2

[0119] Corresponding to the method embodiment, another aspect of the present invention provides a structural optimization device for a hydrogen detection probe. Figure 4 This diagram illustrates the structure of a hydrogen detection probe optimization device provided in an embodiment of the present invention. The hydrogen detection probe optimization device is... Figure 1 The device corresponding to the structural optimization method of the hydrogen detection probe in the corresponding embodiment is implemented through a virtual device. Figure 1 The structural optimization method for the hydrogen detection probe in the corresponding embodiment allows each virtual module constituting the structural optimization device for the hydrogen detection probe to be executed by an electronic device, such as a network device, terminal device, or server. Specifically, the structural optimization device for the hydrogen detection probe in this embodiment includes:

[0120] Modeling parameter determination unit 01 is used to determine the performance influencing factors and performance evaluation indicators of the hydrogen detection probe; the performance influencing factors include: structural parameters as direct influencing factors, and diffusion synergy and shape diffusivity as indirect influencing factors; the performance evaluation indicators include: the cumulative hydrogen contact amount and hydrogen contact uniformity of the hydrogen detection probe.

[0121] Modeling data generation unit 02 is used to obtain multiple sets of experimental data through multiple simulated hydrogen leakage experiments; the data items of the experimental data include the direct influencing factors, the indirect influencing factors, and the performance evaluation indicators.

[0122] Modeling unit 03 is used to construct a probe performance prediction model using the experimental data as modeling data; the probe performance prediction model is used to generate the cumulative hydrogen touch amount and hydrogen touch uniformity of the hydrogen detection probe through preset structural parameter data.

[0123] The structural parameter data generation unit 04 is used to obtain optimized structural parameter data through the probe performance prediction model based on the set target performance evaluation index.

[0124] It should be noted that the specific implementation method and technical effects of the hydrogen detection probe structure optimization device in the embodiments of the present invention can be referred to Figure 1 The structural optimization method for the corresponding hydrogen detection probe will not be elaborated here.

[0125] Example 3

[0126] Corresponding to the method embodiments, this invention also provides a structural optimization device for a hydrogen detection probe, such as a terminal or server. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The terminal can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these.

[0127] An example diagram of the hardware structure block diagram of the hydrogen detection probe structure optimization device provided in this embodiment of the invention is shown below. Figure 5 As shown, it may include:

[0128] Processor 1, communication interface 2, memory 3, and communication bus 4;

[0129] The processor 1, communication interface 2, and memory 3 communicate with each other via communication bus 4.

[0130] Optionally, communication interface 2 can be an interface of a communication module, such as the interface of a GSM module;

[0131] Processor 1 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0132] Memory 3 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk drive.

[0133] Specifically, processor 1 is used to execute the computer program stored in memory 3 to perform the following steps:

[0134] S11. Determine the performance influencing factors and performance evaluation indicators of the hydrogen detection probe; the performance influencing factors include: structural parameters as direct influencing factors, and diffusion synergy and shape diffusivity as indirect influencing factors; the performance evaluation indicators include: the cumulative hydrogen contact amount and hydrogen contact uniformity of the hydrogen detection probe.

[0135] S12. Multiple sets of experimental data were obtained through repeated simulated hydrogen leakage experiments; the data items of the experimental data include the direct influencing factors, the indirect influencing factors, and the performance evaluation indicators.

[0136] S13. Using the experimental data as modeling data, construct a probe performance prediction model; the probe performance prediction model is used to generate the cumulative hydrogen touch amount and hydrogen touch uniformity of the hydrogen detection probe through preset structural parameter data.

[0137] S14. Based on the set target performance evaluation index, the optimized structural parameter data are obtained through the probe performance prediction model.

[0138] The above-described product can execute the method provided in the embodiments of the present invention, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in this embodiment can be found in the structural optimization method for the hydrogen detection probe provided in the embodiments of the present invention.

[0139] Example 4

[0140] In this embodiment of the invention, a storage medium is also provided, which can store a program suitable for execution by a processor, the program being used for:

[0141] S11. Determine the performance influencing factors and performance evaluation indicators of the hydrogen detection probe; the performance influencing factors include: structural parameters as direct influencing factors, and diffusion synergy and shape diffusivity as indirect influencing factors; the performance evaluation indicators include: the cumulative hydrogen contact amount and hydrogen contact uniformity of the hydrogen detection probe.

[0142] S12. Multiple sets of experimental data were obtained through repeated simulated hydrogen leakage experiments; the data items of the experimental data include the direct influencing factors, the indirect influencing factors, and the performance evaluation indicators.

[0143] S13. Using the experimental data as modeling data, construct a probe performance prediction model; the probe performance prediction model is used to generate the cumulative hydrogen touch amount and hydrogen touch uniformity of the hydrogen detection probe through preset structural parameter data.

[0144] S14. Based on the set target performance evaluation index, the optimized structural parameter data are obtained through the probe performance prediction model.

[0145] Optionally, the refined and extended functions of the program can be found in the description above.

[0146] The above-described product can execute the methods provided in the embodiments of the present invention, and has the corresponding functional modules and beneficial effects for executing the methods. Technical details not described in detail in this embodiment can be found in the methods provided in other embodiments of the present invention.

[0147] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0148] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. Furthermore, the couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0149] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0150] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0151] It should be understood that in the embodiments of this application, the claims, various embodiments, and features can be combined with each other to solve the aforementioned technical problems.

[0152] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0153] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for optimizing the structure of a hydrogen detection probe, characterized in that, Including the following steps: S11. Determine the performance influencing factors and performance evaluation indicators of the hydrogen detection probe; the performance influencing factors include: structural parameters as direct influencing factors, and diffusion synergy and shape diffusivity as indirect influencing factors; the performance evaluation indicators include: the cumulative hydrogen contact amount and hydrogen contact uniformity of the hydrogen detection probe. S12. Multiple sets of experimental data were obtained through repeated simulated hydrogen leakage experiments; the data items of the experimental data include the direct influencing factors, the indirect influencing factors, and the performance evaluation indicators. S13. Using the experimental data as modeling data, construct a probe performance prediction model; the probe performance prediction model is used to generate the cumulative hydrogen touch amount and hydrogen touch uniformity of the hydrogen detection probe through preset structural parameter data. S14. Based on the set target performance evaluation index, the optimized structural parameter data are obtained through the probe performance prediction model.

2. The structural optimization method for the hydrogen detection probe according to claim 1, characterized in that, Solving for the diffusion cooperation degree includes: The energy conservation equation for the laminar boundary layer is as follows: Where λ is the thermal conductivity of the fluid medium; ρ is the density; C p y is the specific heat capacity; u is the axial velocity; v is the radial velocity; x is the axial distance; y is the radial distance; T is the temperature. Integrating both sides of the energy conservation equation in the domain of discussion yields: Where, δ t,x This represents the thickness of the thermal boundary layer at location x; Rewrite the convection term on the left-hand side of the above equation in vector form: Introduce another dimensionless variable: Substituting the dimensionless variable and rearranging, we get: Among them, Re x Nu x The definition is the same as in typical boundary layer flow analysis; the integrand can be written as... Where β is the angle between the velocity vector and the temperature gradient vector.

3. The structural optimization method for the hydrogen detection probe according to claim 1, characterized in that, include: The shape diffusivity is a characteristic quantity of the angle between the edge of the hydrogen diffusion cloud and the diffusion line at the center of the cloud, used to characterize the diffusivity of the shape.

4. The structural optimization method for the hydrogen detection probe according to claim 1, characterized in that, Hydrogen detection probe suitable for micro / nano optical fibers.

5. The structural optimization method for the hydrogen detection probe according to claim 4, characterized in that, The selection range of the structural parameter items includes: The inlet and outlet shapes of the hydrogen detection probe, the inlet and outlet diameters of the hydrogen detection probe, the inlet and outlet distance of the hydrogen detection probe, the gas flow rate, the shape of the hydrogen detection probe, the specifications of the hydrogen detection probe, and the position of the micro-nano optical fiber.

6. The structural optimization method for the hydrogen detection probe according to claim 4, characterized in that, The calculation of the cumulative hydrogen touch volume includes: The mass of hydrogen absorbed by the micro-nano optical fiber is calculated based on the degree of color change of the hydrogen detection probe. The cumulative hydrogen touch volume is obtained by calculating the ratio of the absorbed hydrogen mass to the hydrogen detection probe volume.

7. The structural optimization method for the hydrogen detection probe according to claim 1, characterized in that, The hydrogen touch uniformity includes: Time-based hydrogen touch uniformity and length-based hydrogen touch uniformity.

8. The method for optimizing the structure of a hydrogen detection probe according to claim 1, characterized in that, The optimized structural parameter data includes: Structural parameter data corresponding to the target performance evaluation index.

9. A structural optimization device for a hydrogen detection probe, characterized in that, include: The modeling parameter determination unit is used to determine the performance influencing factors and performance evaluation indicators of the hydrogen detection probe; The performance influencing factors include: structural parameters as direct influencing factors, and diffusion synergy and shape diffusivity as indirect influencing factors; the performance evaluation indicators include: the cumulative hydrogen contact amount and hydrogen contact uniformity of the hydrogen detection probe. The modeling data generation unit is used to obtain multiple sets of experimental data through multiple simulated hydrogen leakage experiments; the data items of the experimental data include the direct influencing factors, the indirect influencing factors, and the performance evaluation indicators. The modeling unit is used to construct a probe performance prediction model using the experimental data as modeling data; the probe performance prediction model is used to generate the cumulative hydrogen touch amount and hydrogen touch uniformity of the hydrogen detection probe through preset structural parameter data. The structural parameter data generation unit is used to obtain optimized structural parameter data through the probe performance prediction model based on the set target performance evaluation index.

10. The structural optimization device for the hydrogen detection probe according to claim 9, characterized in that, Solving for the diffusion cooperation degree includes: The energy conservation equation for the laminar boundary layer is as follows: Where λ is the thermal conductivity of the fluid medium; ρ is the density; C p y is the specific heat capacity; u is the axial velocity; v is the radial velocity; x is the axial distance; y is the radial distance; T is the temperature. Integrating both sides of the energy conservation equation in the domain of discussion yields: Where, δ t,x This represents the thickness of the thermal boundary layer at location x; Rewrite the convection term on the left-hand side of the above equation in vector form: Introduce another dimensionless variable: Substituting the dimensionless variable and rearranging, we get: Among them, Re x Nu x The definition is the same as in typical boundary layer flow analysis; the integrand can be written as... Where β is the angle between the velocity vector and the temperature gradient vector.

11. A device for optimizing the structure of a hydrogen detection probe, characterized in that, include: Memory, used to store computer programs; A processor is configured to invoke and execute the computer program to implement the steps of the structural optimization method for the hydrogen detection probe as described in any one of claims 1-8.

12. A storage medium, characterized in that, Includes a software program adapted for execution by a processor of the steps of the structural optimization method for the hydrogen detection probe as described in any one of claims 1-8.

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