A method, device and equipment for inverting hydrogen leakage rate in a confined space

Abstract

The application relates to the field of hydrogen leakage detection, and discloses a method, device and equipment for inverting a hydrogen leakage rate in a confined space, wherein the method comprises the following steps: acquiring a leakage position coordinate and a vertical projection distance of a leakage source in the confined space, wherein the vertical projection distance is a vertical distance from the leakage source to the top of the confined space; determining a target sensor according to the leakage position coordinate and a specified diameter range; acquiring a steady-state concentration value and a relative center distance of the target sensor within a specific time window; acquiring matched target model parameters in a pre-constructed parameter database according to the vertical projection distance; constructing a concentration inversion model based on the target model parameters; and inputting the relative center distance and the steady-state concentration value into the concentration inversion model to obtain the hydrogen leakage rate of the leakage source. The technical scheme provided by the application can quickly and accurately invert the hydrogen leakage rate in the confined space, quantifies the hydrogen leakage intensity, and improves the safety and effectiveness of hydrogen energy management in the confined space.

Description

Technical Field

[0001] This application relates to the field of hydrogen leakage detection, and in particular to a method, apparatus and equipment for inverting the hydrogen leakage rate in a confined space. Background Technology

[0002] In enclosed or semi-enclosed spaces such as underground parking garages and maintenance utility tunnels, hydrogen gas will rise rapidly and accumulate at the top of the space during a hydrogen leak, forming a hidden flammable and explosive layer. Current hydrogen leak detection methods rely on sensing systems placed at the top of the space to acquire instantaneous concentration data around the sensor probes to characterize the leak.

[0003] However, the aforementioned hydrogen leak detection methods have certain limitations: engineers can only know the instantaneous concentration value near the sensor and cannot determine the release intensity of the leak source from it. Different release intensities indicate different levels of urgency in leaks, making it difficult for engineers to quickly and accurately implement appropriate emergency measures based on the actual situation. This limitation can easily lead to delays or misjudgments in emergency response measures, affecting hydrogen safety within confined spaces.

[0004] Therefore, how to quantify the leakage intensity of a leak source within a confined space has become a key research focus in the field of hydrogen leak detection. Summary of the Invention

[0005] This application provides a method, apparatus, and equipment for inverting the hydrogen leakage rate in a confined space, which can quickly and accurately invert the hydrogen leakage rate in a confined space to quantify the leakage intensity of hydrogen.

[0006] The first aspect of this application provides a method for inverting the hydrogen leakage rate in a confined space. The method includes: obtaining the leakage location coordinates and vertical projection distance of the leakage source within the confined space, wherein the vertical projection distance is the vertical distance from the leakage source to the top of the confined space; determining a target sensor based on the leakage location coordinates and a specified diameter range; obtaining the steady-state concentration value and relative center distance of the target sensor within a specific time window; obtaining matching target model parameters from a pre-built parameter database based on the vertical projection distance; constructing a concentration inversion model based on the target model parameters; and inputting the relative center distance and steady-state concentration value into the concentration inversion model to obtain the hydrogen leakage rate of the leakage source, wherein the hydrogen leakage rate is used for risk assessment and graded early warning of the current leakage situation.

[0007] In one implementation, a specific time window begins at the steady-state arrival time of leaked hydrogen within a specified diameter range and ends at the moment when leaked hydrogen reflected from the sidewall of the confined space enters the specified diameter region, wherein the specified diameter range is determined based on the vertical projection distance.

[0008] In one embodiment, the parameter database includes pre-model parameters for multiple pre-confined spaces. The parameter database is constructed as follows: for any pre-confined space, the spatial height of the pre-confined space is obtained, and steady-state operating data of the pre-confined space under multiple operating conditions are obtained, wherein the spatial height is used to match the vertical projection distance; a pre-constructed concentration distribution model is obtained, and the concentration distribution model is fitted according to the steady-state operating data and the spatial height to obtain the pre-model parameters corresponding to any operating condition; the mapping relationship between the spatial height and the pre-model parameters is determined, and the parameter database is constructed based on the mapping relationship.

[0009] In one embodiment, the concentration distribution model includes a distribution baseline term, a distribution peak term, and a distribution standard deviation term; wherein: the distribution baseline term is used to characterize the steady-state concentration of leaked hydrogen at the edge of a specified diameter range, the distribution peak term is used to characterize the leakage intensity of the target leakage source, and the distribution standard deviation term is used to characterize the distribution of leaked hydrogen in the horizontal direction at the top of the confined space.

[0010] In one implementation, the concentration inversion model is constructed based on a concentration baseline term, a concentration peak term, and a concentration standard deviation term. The concentration baseline term and the concentration peak term are constructed based on the target model parameters. Specifically, the concentration baseline term is used to characterize the steady-state concentration of leaked hydrogen at the edge of a specified diameter range after steady-state diffusion, the concentration peak term is used to characterize the leakage intensity of the leakage source, and the concentration standard deviation term is used to characterize the distribution of leaked hydrogen in the horizontal direction at the top of the confined space.

[0011] In one implementation, the concentration inversion model includes a residual function and an objective function, the residual function being constructed based on the objective model parameters; inputting the relative center distance and steady-state concentration value into the concentration inversion model to obtain the hydrogen leakage rate of the current leakage source includes: updating the residual function corresponding to each sensor according to the relative center distance and steady-state concentration value; updating the objective function according to the residual function; and iteratively optimizing the objective function to determine the hydrogen leakage rate of the current leakage source.

[0012] In one implementation, iteratively optimizing the objective function to determine the hydrogen leakage rate of the current leakage source includes: obtaining a reference leakage rate in any iteration of the iterative optimization; determining the Jacobian of the objective function based on the reference leakage rate; determining a target correction based on the Jacobian; updating the reference leakage rate in the current iteration based on the target correction; and using the updated reference leakage rate from the last iteration as the hydrogen leakage rate of the current leakage source.

[0013] In one implementation, determining the target correction amount based on the Jacobian includes: obtaining reference model parameters corresponding to the reference leakage rate; determining the residuals of each target sensor based on the reference model parameters; determining the Jacobian of the target sensor based on the residuals; and solving a pre-constructed set of correction variances based on the residuals and the Jacobian to obtain the target correction amount for the reference leakage rate.

[0014] A second aspect of this application provides an inversion device for hydrogen leakage rate in a confined space. The device includes: a location determination unit for acquiring the leakage location coordinates of a leakage source within the confined space; a data acquisition unit for determining a target sensor based on the leakage location coordinates and a specified diameter range, and acquiring the steady-state concentration value and relative center distance of the target sensor within a specific time window; a model determination unit for acquiring matching target model parameters from a pre-built parameter database based on the vertical projection distance from the leakage source to the top of the confined space, and constructing a concentration inversion model based on the target model parameters; and a data determination unit for inputting the relative center distance and steady-state concentration value into the concentration inversion model to obtain the hydrogen leakage rate of the leakage source, wherein the hydrogen leakage rate is used for risk assessment and graded early warning of the current leakage situation.

[0015] A third aspect of this application provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the inversion method for hydrogen leakage rate in a confined space as described in the first aspect.

[0016] Based on the above ideas, the technical solution provided in this embodiment of the application optimizes and inverts the steady-state concentration value of a confined space online based on a constructed concentration inversion model, which can quickly and accurately determine the hydrogen leakage rate in the confined space. Specifically, the location coordinates of the leakage source in the confined space and its vertical projection distance to the top are obtained to delineate the target sensors in the sensor array. Within a specific time window, the steady-state concentration value of the target sensor is determined using the steady-state concentration distribution characteristics of the confined space. Based on the parameter database and concentration inversion model built offline, online inversion is performed according to the steady-state concentration value. This allows for the rapid and accurate determination of the hydrogen leakage rate in the confined space without the need for high-density sensor deployment, providing a quantitative decision-making basis for graded early warning and differentiated emergency response, and significantly improving the effectiveness of hydrogen leakage monitoring and emergency response management in confined spaces.

[0017] As can be seen, the technical solution provided in this application can quickly and accurately invert the hydrogen leakage rate in a confined space, so as to quantify the leakage intensity of hydrogen leakage and provide a basis for emergency decision-making. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 A schematic diagram illustrating the steps of a method for inverting hydrogen leakage rate in a confined space, provided for an embodiment of this application; Figure 2 A schematic diagram of the concentration distribution at the top of a confined space at different times, provided as an embodiment of this application; Figure 3 This is a schematic diagram illustrating the steps of constructing a parameter database according to one embodiment of this application; Figure 4(a) is a schematic diagram of steady-state concentration distribution under different operating conditions provided in an embodiment of this application; Figure 4(b) is a schematic diagram of the linear relationship between standard deviation and vertical projection distance provided in an embodiment of this application; Figure 4(c) is a schematic diagram of the power-law function relationship curves of the concentration reference term and the concentration peak term with respect to the leakage flow under various operating conditions provided in an embodiment of this application; Figure 4(d) is a schematic diagram of the power-law function relationship curves of the concentration reference term and the concentration peak term with respect to the vertical projection distance provided in an embodiment of this application; Figure 5 A schematic diagram of the structure of a device for inverting hydrogen leakage rate in a confined space, provided as one embodiment of this application; Figure 6 This is a schematic diagram of the structure of a computer device provided in one embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] Furthermore, the use of terms such as "first," "second," etc., in this application is for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of embodiments in this application, unless otherwise stated, "multiple" means two or more. Additionally, the use of "based on" or "according to" implies openness and inclusiveness, because processes, steps, calculations, or other actions "based on" or "according to" one or more of the stated conditions or values ​​may in practice be based on additional conditions or beyond the stated values.

[0022] With the rapid development of hydrogen fuel cell vehicles and the hydrogen energy storage and transportation industry, the application of hydrogen in enclosed or semi-enclosed confined spaces such as underground parking garages, maintenance tunnels, and hydrogen refueling stations is becoming increasingly frequent. Because hydrogen's density is much lower than air and its diffusion coefficient is extremely high, in the event of a leak, the gas will rise rapidly and accumulate at the top of the space, forming a highly concealed flammable and explosive layer. Therefore, real-time and accurate leak monitoring has become a crucial link in ensuring hydrogen energy safety.

[0023] In related technologies, hydrogen monitoring in confined spaces primarily relies on sensor alarms deployed at critical locations. In recent years, hydrogen leak source location technology has made some progress, enabling preliminary determination of the leak location after it occurs. However, it can only provide instantaneous concentration information within a very small area around the sensor, and cannot quantify the release intensity and severity of the leak source. For example, it cannot distinguish whether the current leak is a trace seepage on the pipe surface or a rupture at the flange interface. Even at the same leak point, different leakage rates will result in significantly different concentration fields. Small leaks only affect a local area with a low diffusion rate, while large leaks will rapidly spread, making timely intervention with large-scale emergency measures difficult. This limitation easily leads to delays or misjudgments in emergency response measures, causing safety management to remain at a passive response level for a long time.

[0024] In view of the above, one or more embodiments of this application provide a method, apparatus and equipment for inverting the hydrogen leakage rate in a confined space, which can solve the above problems, realize the rapid and accurate inversion of the hydrogen leakage rate in a confined space, quantify the leakage intensity of hydrogen leakage through the hydrogen leakage rate, and significantly improve the safety and effectiveness of hydrogen energy safety management in confined spaces.

[0025] Please see Figure 1 This application provides a method for inverting the hydrogen leakage rate within a confined space, one embodiment of which is applicable to different confined spaces. The confined space has a regularly arranged sensor array at its top for real-time acquisition of the instantaneous concentration values ​​around each sensor. Specifically, the method may include the following steps: S1: Obtain the location coordinates and vertical projection distance of the leak source within the confined space. The vertical projection distance is the vertical distance from the leak source to the top of the confined space.

[0026] The above-mentioned leak location coordinates represent the location information of the leak source in a confined space, and are usually expressed in three-dimensional coordinates. This indicates that the aforementioned leak location coordinates are predetermined when the leak source is detected in the early stages of the leak, serving as a spatial reference for the relative position of the sensor and the leak source. For example, these leak location coordinates can be determined by matching a pre-set positioning model based on flow field characteristics, or by analyzing the gradient change characteristics or detection time difference change characteristics of the instantaneous hydrogen concentration read by the sensor array. The aforementioned vertical projection distance is the vertical distance between the leak source and the top projection point (vertical projection point) of the confined space. It can be understood that the aforementioned vertical projection distance is determined based on the leak location coordinates and spatial geometric coordinates.

[0027] In this embodiment, a steady-state concentration region exists around the vertical projection point at the top of the confined space where the leakage source is located. Within this region, the hydrogen concentration maintains a steady-state distribution within a specific time window. Specifically, after diffusing at the top of the confined space for a period of time, the hydrogen exhibits a stable concentration within a certain range and for a certain period of time. Understandably, the hydrogen does not diffuse uniformly in all directions, but rather moves upwards under buoyancy and diffuses radially around the vertical projection point at the top of the confined space, thus forming a steady-state concentration region at the top that is unaffected by boundary reflections. Preferably, the specified diameter range is centered on the vertical projection point, with the vertical projection distance as the diameter. In the subsequent prediction of the hydrogen leakage rate, only the instantaneous concentration value of the sensor within this steady-state concentration region needs to be obtained, thereby accurately and quickly inverting the hydrogen leakage rate.

[0028] S3: Determine the target sensor based on the leak location coordinates and a specified diameter range, and obtain the steady-state concentration value and relative center distance of the target sensor within a specific time window.

[0029] Specifically, taking the vertical projection point pointed to by the leak location coordinates as the center, multiple sensors within a specified diameter range are designated as target sensors. The aforementioned relative center distance is the distance between the target sensor and the vertical projection point. Since the steady-state concentration field of hydrogen diffusion at the top has a finite spatial range, the instantaneous concentration values ​​of sensors outside the specified diameter range in a complexly distributed sensor array typically do not contain valid information. By selecting target sensors, systematic errors can be avoided during the inversion process, improving inversion accuracy and reducing the computational cost of subsequent optimization iterations.

[0030] The aforementioned specific time window can be defined as the period from the moment when the hydrogen concentration at each point within the specified diameter area reaches a steady state until the leaked hydrogen is reflected back to the specified diameter area by the sidewall. This ensures that the leaked hydrogen exhibits a steady-state distribution within this time window and the specified diameter area, avoiding an unsteady distribution caused by the superposition of reflected hydrogen with incident hydrogen after entering the area. Therefore, the aforementioned steady-state concentration value is obtained within the specific time window, meaning the target sensor reading fluctuates less and tends to be stable within this specific time window. Understandably, the size of the aforementioned specific time window is dynamically influenced by the leakage rate, the geometry of the confined space, and the coordinates of the leakage location, thus adapting to confined spaces of different scales.

[0031] S5: Based on the vertical projection distance, obtain the matching target model parameters from the pre-built parameter database, and construct the concentration inversion model based on the target model parameters.

[0032] The concentration inversion model described above can be understood as mapping the steady-state concentration values ​​measured by sensors back to a parameterized model of the hydrogen leakage rate. The target model parameters are the preliminary model parameters that best match the current leakage scenario. Substituting these target model parameters into the concentration inversion model can provide environmental constraints characterizing the confined space and the location of the leakage source for predicting the hydrogen leakage rate under the current leakage scenario. Specifically, the parameter database uses the height data of the confined space as an index to search for height data matching the vertical projection distance in the parameter database, thereby retrieving the matching target model parameters.

[0033] The aforementioned parameter database is pre-constructed based on operating condition data for different confined spaces. Optionally, when the leakage source height is fixed at the ground level, the operating condition data includes the height data of the confined space (including the confined space height), steady-state concentration value, and hydrogen leakage rate. Model fitting mapping is performed on each confined space according to different operating conditions to determine the model parameters matching each operating condition that conforms to the concentration inversion model. Optionally, when the leakage source height is not fixed, the aforementioned high-speed data also includes the simulated leakage height at different height positions within each confined space. Optionally, during the pre-construction of the parameter database, a three-dimensional virtual model is established for each confined space to simulate different hydrogen leakage rates using fluid dynamics software.

[0034] S7: Input the relative center distance and steady-state concentration value into the concentration inversion model to obtain the hydrogen leakage rate of the leakage source. The hydrogen leakage rate is used to conduct risk assessment and graded early warning of the current leakage situation.

[0035] The aforementioned relative center distance is used to provide spatial location information for the concentration inversion model, while the aforementioned steady-state concentration value is used to provide physical measurement information for the concentration inversion model. By introducing the relative center distance, the steady-state concentration value read by each sensor is anchored on spatial coordinates to form a steady-state spatial distribution of leaked hydrogen within a specified diameter range. This eliminates the ambiguity of single-point measurements, making the inverted hydrogen leakage rate tend to be unique, thereby quickly and accurately obtaining the hydrogen leakage rate under the current leakage scenario. Optionally, the aforementioned concentration inversion model can be solved using optimization algorithms such as the Gauss-Newton method and the least squares method. The aforementioned hydrogen leakage rate, i.e., the volume of hydrogen released from the leakage source per unit time, can be used to quantitatively characterize the leakage intensity of the leakage source.

[0036] Traditional monitoring technologies, such as point-based alarm systems, output Boolean values ​​(indicating whether the leakage exceeds or does not exceed the limit), which cannot distinguish the severity of the leak. In this embodiment, risk assessment and graded early warning are performed based on the hydrogen leakage rate. Specifically, different hydrogen leakage rates are classified into levels according to the leakage intensity to conduct different levels of risk assessment. The continuous risk assessment results are discretized into actionable level signals for graded early warning. Furthermore, corresponding response measures are executed according to the graded early warning signals, achieving precise resource allocation. For example, a minor leak may only require increased ventilation, a moderate leak requires activating an emergency plan and investigating the cause, while a large-volume leak may trigger emergency shutdown and personnel evacuation.

[0037] Based on the above ideas, the technical solution provided in this embodiment of the application optimizes and inverts the steady-state concentration value of a confined space online based on a constructed concentration inversion model, which can quickly and accurately determine the hydrogen leakage rate in the confined space. Specifically, the location coordinates of the leakage source in the confined space and its vertical projection distance to the top are obtained to delineate the target sensors in the sensor array. Within a specific time window, the steady-state concentration value of the target sensor is determined using the steady-state concentration distribution characteristics of the confined space. Based on the parameter database and concentration inversion model built offline, online inversion is performed according to the steady-state concentration value. This allows for the rapid and accurate determination of the hydrogen leakage rate in the confined space without the need for high-density sensor deployment, providing a quantitative decision-making basis for graded early warning and differentiated emergency response, and significantly improving the effectiveness of hydrogen leakage monitoring in confined spaces and the real-time nature of emergency response management.

[0038] In one embodiment, in step S3 above, the specific time window begins at the steady-state arrival time of the leaked hydrogen within a specified diameter range and ends at the moment when the leaked hydrogen reflected from the sidewall of the confined space enters the specified diameter region. The specified diameter range is determined based on the vertical projection distance, that is, the vertical projection distance is used as the diameter of the specified diameter range, and the vertical projection point is used as the center of the specified diameter range.

[0039] The aforementioned steady-state arrival time can be understood as the moment when the hydrogen concentration detected by each target sensor within a specified diameter range reaches a stable state. For example, by real-time monitoring of the instantaneous concentration values ​​at the start and end times of any specified time step of the target sensor, if the instantaneous concentration difference of the target sensor within a specified time step reaches a preset threshold, then the end time of the current specified time step is considered the aforementioned steady-state arrival time.

[0040] In one embodiment, see Figure 2 , Figure 2 This represents the concentration distribution at the top of the confined space at different times. The horizontal axis represents the relative distance between each target sensor and the vertical projection point, and multiple curves correspond to the top concentration distribution at different times after the leak occurs. Understandably, in this embodiment, the curves at the initial stage of the leak (e.g., 40, 100, 140 seconds) indicate that hydrogen has just reached the top of the confined space, and the concentration field has not yet reached a steady state. As time progresses, the curves within a specific time window (e.g., 200 to 600 seconds) highly overlap within a finite range around the origin (i.e., representing a specified diameter range, such as from -1.2 meters to +1.2 meters), exhibiting an approximate concentration distribution shape, indicating that the concentration field has reached a temporally stable state. Within the aforementioned specific time window, the instantaneous concentration values ​​of the target sensors within the specified diameter range are collected as the steady-state concentration values.

[0041] The technical solution provided in this embodiment refines the method for determining a specific time window. Specifically, the specific time window is defined as the period from the moment when the hydrogen concentration within a specified diameter range first reaches a steady state until the moment before the reflected airflow from the sidewall of the confined space re-enters the region. By real-time monitoring of the concentration fluctuations of the target sensors within a continuous time step, a steady state is determined to have been reached when the concentration changes of each sensor are all below a preset threshold, thus locking in the specific time window. This technical solution ensures that the collected concentration data meets the steady-state distribution, effectively avoiding monitoring errors caused by airflow reflection, thereby ensuring the accuracy and reliability of the hydrogen leakage rate obtained through inversion.

[0042] In one implementation, in step S5 above, the parameter database includes multiple pre-model parameters for pre-constrained spaces; please refer to [link to relevant documentation]. Figure 3 The parameter database is constructed according to the following steps: S31: For any pre-confined space, obtain the spatial height of the pre-confined space, and obtain the steady-state operating data of the pre-confined space under multiple operating conditions; S33: Obtain the pre-built concentration distribution model, and fit the concentration distribution model according to the steady-state operating condition data and spatial height to obtain the pre-model parameters corresponding to any operating condition; S35: Determine the mapping relationship between spatial height and preliminary model parameters, and construct a parameter database based on the mapping relationship.

[0043] In one embodiment, for a leakage scenario where the leakage source is on the ground, the aforementioned steady-state operating condition data includes steady-state concentration data and hydrogen leakage rate at any pre-confined space location on the ground. Specifically, for any pre-confined space, different leakage rates are set for operating condition simulation, and steady-state concentration data obtained under each operating condition are extracted. Based on the leakage rate, the corresponding steady-state concentration value, and the space height, the concentration distribution model is fitted to obtain the pre-model parameters for the corresponding operating condition.

[0044] In another embodiment, for a leakage scenario where the leakage source is at any height, the aforementioned steady-state operating condition data includes steady-state concentration data and hydrogen leakage rate at different heights of any pre-confined space. Specifically, for any pre-confined space, different leakage heights are set, and different leakage rates are set at any leakage height for operating condition simulation. The steady-state concentration data obtained under each operating condition is extracted, and the concentration distribution model is fitted based on the leakage height, leakage rate, and corresponding steady-state concentration value to obtain the pre-model parameters for the corresponding operating condition.

[0045] In this embodiment, since the hydrogen concentration distribution at the top of the space exhibits a centrosymmetric distribution centered on the vertical projection point, any steady-state concentration profile approximately follows a Gaussian distribution within a specified diameter range. The Gaussian distribution can be used to describe the diffusion of hydrogen in an infinitely large, unobstructed space. Therefore, the aforementioned concentration distribution model is preferably determined based on a Gaussian model. This can be understood as a Gaussian model obtained by applying boundary physical constraints to the steady-state hydrogen distribution characteristics within a confined space.

[0046] The technical solution provided in this embodiment refines the offline construction method of the parameter database. Specifically, by collecting steady-state operating data corresponding to different spatial heights of the pre-confined spaces and the location of the leakage source at ground level or arbitrary height, and different leakage rates, a Gaussian concentration distribution model corrected for the physical boundaries of the confined spaces is fitted to establish a mapping relationship between spatial height and pre-confined model parameters, and a parameter database is constructed. This technical solution can adapt to different leakage heights and leakage conditions, achieve accurate matching and calling of target model parameters, and effectively improve the adaptability and accuracy of the concentration inversion model.

[0047] In one implementation, a concentration distribution model is established based on a Gaussian distribution and a specified diameter range. The concentration distribution model includes a distribution baseline term, a distribution peak term, and a distribution standard deviation term. The distribution baseline term is used to characterize the steady-state concentration at the edge of the specified diameter range, the distribution peak term is used to characterize the leakage intensity of the target leakage source, and the distribution standard deviation term is used to characterize the distribution of leaked hydrogen in the horizontal direction at the top of the confined space.

[0048] In one embodiment, the above concentration distribution model is expressed as: .in, As the distribution benchmark term, For the peak term of the distribution, The standard deviation term of the distribution. Characterizing the distance from the vertical projection point The steady-state hydrogen concentration at a distance of meters. This indicates the leakage rate. Specifically, The concentration of leaked hydrogen at the edge far from the source point after steady-state diffusion is geometrically represented as the vertical offset of a Gaussian curve relative to the horizontal axis. It is expressed as the amplitude of the concentration peak, specifically characterizing the order of magnitude of the leakage intensity. The standard deviation of the concentration distribution reflects the horizontal diffusion range of hydrogen gas. The Gaussian distribution is specifically reflected in the standard deviation term. The distance between the standard deviation term and the vertical projection is... They exhibit a linear positive correlation, which is expressed as... , These are dimensionless fitting coefficients.

[0049] In this embodiment, the distribution benchmark term can be expressed as a power-law function: The peak term of the above distribution can be expressed in the form of a power-law function: Among them, the above , , , , , These are dimensionless fitting coefficients. Optionally, the dimensionless fitting coefficients obtained from the fitting can be used as preliminary model parameters and pre-stored in the parameter database of the edge computing device on site.

[0050] In one embodiment, the concentration distribution model is fitted in the following manner to obtain preliminary model parameters for the corresponding operating conditions: the concentration distribution model is fitted based on steady-state operating condition data and spatial height to obtain a series of parameters corresponding to different operating conditions. , Below (representing different working conditions) , The value is used to fit a power-law function. , in, Merging , Merging Further, the standard deviation is calculated based on the height data (space height or leakage height). Furthermore, the above-obtained fitting result... , , These parameters are pre-stored in the parameter database as preliminary model parameters. For example, under a certain operating condition, the following is obtained: , , .

[0051] The technical solution provided in this embodiment addresses the physical boundary constraints of confined spaces by constructing a concentration distribution model based on a Gaussian distribution, which includes multiple terms, for the construction of a parameter database. Specifically, the concentration distribution model includes a baseline term, a peak term, and a standard deviation term. The baseline term and concentration term are decomposed using a power-law approach, and representative preliminary model parameters are obtained by fitting steady-state operating data and spatial height, and stored in the parameter database. This determines the mapping relationship between the steady-state hydrogen concentration and the leakage rate and vertical projection distance, improving the accuracy of subsequent inversion calculations of the hydrogen leakage rate. Furthermore, the fitted parameters can be directly deployed in edge computing devices, facilitating rapid online computation on-site.

[0052] In one implementation, the concentration inversion model includes a residual function and an objective function. The residual function quantifies the deviation between measured and predicted values ​​from different target sensors, and the objective function integrates the residuals from all target sensors to solve for the hydrogen leakage rate. Specifically, the relative center distance and steady-state concentration value are input into the concentration inversion model to obtain the hydrogen leakage rate of the current leakage source, following these steps: S61: Update the residual function corresponding to each sensor based on the relative center distance and steady-state concentration value; S63: Update the objective function based on the residual function, and iteratively optimize the objective function to determine the hydrogen leakage rate of the current leakage source.

[0053] The residual function is constructed based on the target model parameters, which are extracted from a parameter database. This database is based on a concentration distribution model, which in turn is based on a Gaussian model. Since the concentration distribution model is nonlinear and lacks an analytical solution, it is unsuitable for scenarios with multiple target sensors. Therefore, a concentration inversion model is constructed to transform the nonlinear problem into linear optimization and noise suppression. Based on the concentration distribution model and the target model parameters, a residual function is constructed, obtaining the sum of squared residuals from all target sensors within a specified diameter range. This results in an objective function with the leakage rate as the unknown quantity. During the actual measurement, a built-in numerical optimization algorithm (such as the Gauss-Newton method or the Levenberg-Marquardt method) is further invoked to find the leakage rate that minimizes the objective function. This leakage rate is then used as the hydrogen leakage rate of the current leakage source for risk assessment and graded early warning.

[0054] In one embodiment, the concentration inversion model is constructed based on a concentration baseline term, a concentration peak term, and a concentration standard deviation term. The concentration baseline term and the concentration peak term are constructed based on target model parameters. The concentration baseline term is used to characterize the steady-state concentration of leaked hydrogen at the edge of a specified diameter range, the concentration peak term is used to characterize the leakage intensity of the leakage source, and the concentration standard deviation term is used to characterize the distribution of leaked hydrogen in the horizontal direction at the top of the confined space.

[0055] In one embodiment, the above concentration inversion model is expressed as: ,in, For the residual function, Let be the objective function. Where, This represents the relative center distance between the target sensor i and the vertical projection point. This represents the steady-state concentration value detected by target sensor i. This indicates the current hydrogen leakage rate from the leak source. Among them, , , These are the parameters of the target model.

[0056] In this embodiment, Characterizing the concentration benchmark term, Characterizing the peak concentration term, The concentration standard deviation term is characterized. Among them, the above... , , These are the parameters of the target model.

[0057] The technical solution provided in this embodiment constructs a concentration inversion model containing residual functions and objective functions based on target model parameters extracted from a parameter database. Specifically, by inputting the relative center distance and steady-state concentration values ​​of each target sensor into the model, the residual functions of each sensor are first updated to quantify the logarithmic domain deviation between measured values ​​and model predictions. Then, the objective function is obtained by summing these parameters, and an optimization algorithm is used to iteratively solve for the hydrogen leakage rate. This technical solution effectively suppresses sensor noise and model errors by taking the logarithm of the concentration distribution model and rearranging terms to construct residuals. Simultaneously, by using a squared sum-of-squares objective function to fuse the residual information from multiple target sensors, it achieves a rapid and accurate inversion from discrete concentration readings to the hydrogen leakage rate mapping.

[0058] In one implementation, iteratively optimizing the objective function to determine the hydrogen leakage rate of the current leakage source includes: obtaining a reference leakage rate in any iteration of the iterative optimization; determining the Jacobian of the objective function based on the reference leakage rate; determining a target correction amount based on the Jacobian; updating the reference leakage rate in the current iteration based on the target correction amount; and using the updated reference leakage rate in the last iteration as the hydrogen leakage rate of the current leakage source.

[0059] In this embodiment, if the current iteration is not the first iteration, the reference leakage rate updated in the previous iteration is used as the initial reference leakage rate for the current iteration.

[0060] In this embodiment, if the current iteration is the first iteration, a coarse search is performed within a preset leakage rate range to determine the initial reference leakage rate. Specifically, within the preset leakage rate range (e.g., ... Several candidate values ​​are selected at a certain step size, and the objective function value is calculated for each candidate value. The candidate value with the smallest objective function value is selected as the initial reference leakage rate.

[0061] In this embodiment, the Jacobian can be understood as the first derivative of the residual with respect to the leakage rate, and the residual is determined based on the residual function. Specifically, the current reference leakage rate is obtained. The corresponding reference model parameters include , , Based on the reference model parameters mentioned above, the residuals of each target sensor are calculated. , And calculate the first derivative of the residual with respect to the reference leakage rate. Jacobi, or Jacobi, is expressed as Furthermore, residual vectors are constructed based on the residuals and Jacobians of each target sensor. And Jacobian vectors Furthermore, the constructed system of correction equations is solved based on the residual vector and Jacobian vector to obtain the target correction amount.

[0062] In this embodiment, the target correction can be solved using the Gauss-Newton method or the Levenberg-Marquardt method. Taking the Gauss-Newton method as an example, the target correction... By solving the corrected equation system Received, among which Let be a Jacobian vector. Let be the residual vector. The above correction equations can be understood as approximating the original problem with a quadratic Taylor expansion of the objective function at the current point, and finding the minimum point of this approximation as the correction direction. Furthermore, update the reference leakage rate for the current iteration: .

[0063] In this embodiment, the iteration termination condition can be reaching a preset number of iterations, or it can be determined based on the updated reference model parameters. Specifically, in a certain iteration, the updated reference model parameters are obtained based on the updated reference leakage rate. The reference model parameters are determined based on the offline calibrated power-law function and height data, wherein the power-law function is... and , Determined based on altitude data. Further, the objective function is solved using the updated target model parameters. When both the objective function value and the target correction amount are less than a set threshold, the current iteration is considered the final iteration.

[0064] The technical solution provided in this embodiment refines the iterative solution method for hydrogen leakage rate. Specifically, an initial leakage rate for iteration is selected through a coarse search within a preset leakage rate range. Subsequent iterations are performed based on the reference leakage rate updated in the previous round. In each iteration, the Jacobian of the residual function with respect to the leakage rate is calculated. A specific optimization algorithm is used to solve the correction equations to obtain the leakage rate correction. The leakage rate value is iteratively updated until the iteration termination condition is met. The final converged leakage rate is used as the inversion result. The iterative optimization method of this technical solution can ensure the convergence accuracy of the hydrogen leakage rate solution process, thereby achieving a fast and accurate hydrogen leakage rate inversion solution.

[0065] In one embodiment, the steady-state concentration profile formed by a symmetrical target sensor at the same distance from the vertical projection point approximately follows a Gaussian distribution within a specified horizontal diameter range. For example, please refer to Figure 4(a), which shows the steady-state hydrogen concentration values ​​at different relative distances (from -1.2m to 1.2m from the projection point) under different leakage rates (400ml / min to 20000ml / min). Understandably, within the steady-state concentration region, the concentration distribution curves at different leakage rates all exhibit a Gaussian distribution shape, high in the middle and low at both ends. However, the edge concentrations do not tend to 0 but rather tend towards a distribution baseline. Therefore, the above concentration distribution model can employ a modified Gaussian model, i.e., adding a distribution baseline term to the standard Gaussian model.

[0066] In one embodiment, the standard deviation of the distribution standard deviation term or the concentration standard deviation term is linearly positively correlated with the vertical projection distance H. For example, please refer to Figure 4(b), which illustrates different spatial heights. The standard deviation σ obtained from the simulation shows a linear positive correlation at each point, which can be expressed as a linear regression fit. ,in, It is a dimensionless proportionality constant that depends on the geometric characteristics of the confined space.

[0067] In one embodiment, when constructing the parameter database, steady-state concentration data for each operating condition is extracted and analyzed according to the concentration distribution model. Regression fitting is performed to establish , and , The power-law function relationship between them. Please refer to Figures 4(c) and 4(d). Figure 4(c) shows the leakage rates at a fixed height H. corresponding Value and Value, understandably and With leakage rate The growth exhibits a power-law characteristic (a straight line in a double logarithmic coordinate system), and Figure 4(d) shows the growth at different spatial heights. Down, Power law coefficient ( )and Power law coefficient ( The change in the power-law coefficient with height can be understood. It exhibits power-law decay, and the two together construct... and The form of a binary power-law function.

[0068] Please see Figure 5 This application also provides an inversion device for hydrogen leakage rate in a confined space, the device comprising: The location determination unit 100 is used to obtain the location coordinates of the leakage source within the confined space. The data acquisition unit 200 is used to determine the target sensor based on the leak location coordinates and a specified diameter range, and to acquire the steady-state concentration value and relative center distance of the target sensor within a specific time window; The model determination unit 300 is used to obtain matching target model parameters from a pre-built parameter database based on the vertical projection distance from the leakage source to the top of the confined space, and to build a concentration inversion model based on the target model parameters; The data determination unit 400 is used to input the relative center distance and steady-state concentration value into the concentration inversion model to obtain the hydrogen leakage rate of the leakage source. The hydrogen leakage rate is used to conduct risk assessment and graded early warning of the current leakage situation.

[0069] in, In one embodiment, the device further includes a database construction unit, specifically used to acquire the spatial height of any pre-confined space, acquire steady-state operating data of the pre-confined space under multiple operating conditions, acquire a pre-constructed concentration distribution model, fit the concentration distribution model according to the steady-state operating data and the spatial height to obtain the pre-model parameters corresponding to any operating condition, determine the mapping relationship between the spatial height and the pre-model parameters, and construct a parameter database based on the mapping relationship.

[0070] In one embodiment, the data determination unit 400 is specifically used to update the residual function corresponding to each sensor in the concentration inversion model based on the relative center distance and steady-state concentration value, update the objective function of the concentration inversion model based on the residual function, and iteratively optimize the objective function to determine the hydrogen leakage rate of the current leakage source.

[0071] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0072] The hydrogen leakage rate inversion device in this application embodiment is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, or other devices that can provide the above functions.

[0073] Please see Figure 6 , Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application, such as... Figure 6 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 6 Take a processor 10 as an example.

[0074] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0075] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0076] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0077] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0078] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0079] This application also provides a computer-readable storage medium. The methods described in this application can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code downloaded over a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and subsequently stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the methods shown in the above embodiments are implemented.

[0080] The apparatus or unit described in the above embodiments can be implemented by a computer chip or entity, or by a product having a certain function. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0081] For ease of description, the above devices are described separately by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0082] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer devices. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0083] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus, and computer devices according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0084] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0085] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0086] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0087] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0088] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

[0089] Although embodiments of this application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of this application, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for inverting hydrogen leakage rate in a confined space, characterized in that, The method includes: Obtain the location coordinates and vertical projection distance of the leak source within the confined space, wherein the vertical projection distance is the vertical distance from the leak source to the top of the confined space; The target sensor is determined based on the leak location coordinates and the specified diameter range. Within a specific time window, the steady-state concentration value and relative center distance of the target sensor are obtained. Based on the vertical projection distance, the matching target model parameters are obtained from the pre-built parameter database, and a concentration inversion model is constructed based on the target model parameters; The relative center distance and the steady-state concentration value are input into the concentration inversion model to obtain the hydrogen leakage rate of the leakage source, wherein the hydrogen leakage rate is used to conduct risk assessment and graded early warning of the current leakage situation; Wherein, the specified diameter range is centered on the vertical projection point of the leakage source at the top of the confined space, and the vertical projection distance is the diameter; the relative center distance is the distance between the target sensor and the vertical projection point; the specific time window starts at the steady-state arrival time of the leaked hydrogen within the specified diameter range and ends at the moment when the leaked hydrogen reflected from the side wall of the confined space enters the specified diameter range; The parameter database is pre-constructed based on the working condition data of different confined spaces. The parameter database includes multiple pre-confined space pre-model parameters, and the target model parameters are pre-confined space pre-model parameters that match the current leakage scenario. The concentration inversion model includes a residual function and an objective function, wherein the residual function is constructed based on the parameters of the objective model. Inputting the relative center distance and the steady-state concentration value into the concentration inversion model to obtain the hydrogen leakage rate of the current leakage source includes: updating the residual function corresponding to each sensor based on the relative center distance and the steady-state concentration value; updating the objective function based on the residual function; and iteratively optimizing the objective function to determine the hydrogen leakage rate of the current leakage source.

2. The method according to claim 1, characterized in that, The parameter database is constructed in the following manner: For any pre-confined space, obtain the spatial height of the pre-confined space, and obtain the steady-state operating data of the pre-confined space under multiple operating conditions; A pre-constructed concentration distribution model is obtained, and the concentration distribution model is fitted according to the steady-state operating condition data and the spatial height to obtain the preliminary model parameters corresponding to any operating condition. Determine the mapping relationship between the spatial height and the preliminary model parameters, and construct a parameter database based on the mapping relationship.

3. The method according to claim 2, characterized in that, The concentration distribution model includes a distribution baseline term, a distribution peak term, and a distribution standard deviation term; wherein: The distribution baseline term is used to characterize the steady-state concentration of leaked hydrogen at the edge of a specified diameter range, the distribution peak term is used to characterize the leakage intensity of the target leak source, and the distribution standard deviation term is used to characterize the distribution of leaked hydrogen in the horizontal direction at the top of the confined space.

4. The method according to claim 1, characterized in that, The concentration inversion model is constructed based on a concentration baseline term, a concentration peak term, and a concentration standard deviation term, wherein the concentration baseline term and the concentration peak term are constructed based on the target model parameters; wherein: The concentration baseline term is used to characterize the steady-state concentration of leaked hydrogen at the edge of a specified diameter range after steady-state diffusion, the concentration peak term is used to characterize the leakage intensity of the leakage source, and the concentration standard deviation term is used to characterize the distribution of leaked hydrogen in the horizontal direction at the top of the confined space.

5. The method according to claim 1, characterized in that, Iterative optimization of the objective function to determine the hydrogen leakage rate of the current leakage source includes: In any iteration of the iterative optimization, a reference leakage rate for the current iteration is obtained, and the Jacobian of the objective function is determined based on the reference leakage rate. The target correction amount is determined based on the Jacobian, and the reference leakage rate of the current iteration is updated based on the target correction amount. The updated reference leakage rate from the last iteration is used as the hydrogen leakage rate of the current leakage source.

6. The method according to claim 5, characterized in that, Determining the target correction amount based on the Jacobian includes: Obtain the reference model parameters corresponding to the reference leakage rate; Based on the reference model parameters, the residuals of each target sensor are determined, and based on the residuals, the Jacobian of the target sensor is determined. Based on the residual and the Jacobian, the pre-constructed modified variance set is solved to obtain the target correction amount for the reference leakage rate.

7. A device for inverting hydrogen leakage rate in a confined space, characterized in that, The device includes: The location determination unit is used to obtain the coordinates of the leakage location of the leakage source within the confined space; The data acquisition unit is used to determine the target sensor based on the coordinates of the leak location and a specified diameter range, and to acquire the steady-state concentration value and relative center distance of the target sensor within a specific time window; The model determination unit is used to obtain matching target model parameters from a pre-built parameter database based on the vertical projection distance from the leakage source to the top of the confined space, and to construct a concentration inversion model based on the target model parameters; The data determination unit is used to input the relative center distance and the steady-state concentration value into the concentration inversion model to obtain the hydrogen leakage rate of the leakage source, wherein the hydrogen leakage rate is used to conduct risk assessment and graded early warning of the current leakage situation; Wherein, the specified diameter range is centered on the vertical projection point of the leakage source at the top of the confined space, and the vertical projection distance is the diameter; the relative center distance is the distance between the target sensor and the vertical projection point; the specific time window starts at the steady-state arrival time of the leaked hydrogen within the specified diameter range and ends at the moment when the leaked hydrogen reflected from the side wall of the confined space enters the specified diameter range; The parameter database is pre-constructed based on the working condition data of different confined spaces. The parameter database includes multiple pre-confined space pre-model parameters, and the target model parameters are pre-confined space pre-model parameters that match the current leakage scenario. The concentration inversion model includes a residual function and an objective function, wherein the residual function is constructed based on the parameters of the objective model. Inputting the relative center distance and the steady-state concentration value into the concentration inversion model to obtain the hydrogen leakage rate of the current leakage source includes: updating the residual function corresponding to each sensor based on the relative center distance and the steady-state concentration value; updating the objective function based on the residual function; and iteratively optimizing the objective function to determine the hydrogen leakage rate of the current leakage source.

8. A computer device, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform the method for inverting the hydrogen leakage rate in a confined space as described in any one of claims 1 to 6.

Images