Intelligent hydrogen transmission pipeline leakage detection method based on optical fiber sensor

Abstract

The invention discloses an intelligent hydrogen transmission pipeline leakage detection method based on an optical fiber sensor. The method comprises the steps of obtaining pipeline data, a pipeline path and environment data of a hydrogen transmission pipeline, establishing a pipeline three-dimensional model, performing gridding processing, and constructing a pipeline grid three-dimensional model; simulating a hydrogen leakage diffusion experiment based on the pipeline grid three-dimensional model, and generating simulation experiment data; an initial sensor laying model is constructed for pipeline leakage detection, and simulation detection data are obtained; optimizing the initial sensor laying model to obtain an intelligent sensor laying model; and constructing a detection cost optimization model to optimize the laying scheme. The problem that the detection effect is poor due to the fact that laying depends on artificial experience in the prior art is solved, the hydrogen leakage detection effect can be improved in the complex hydrogen transmission pipeline environment, and the leakage detection requirements of diversified and complicated scenes of hydrogen transmission pipelines can be met.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrogen transmission pipeline detection, and in particular to an intelligent detection method for hydrogen transmission pipeline leakage based on an optical fiber sensor. Background Art

[0002] Hydrogen is a highly flammable gas composed of diatomic molecules. Due to its small molecular size and low viscosity, it is more likely to leak from the joints, valves and flanges of transmission pipelines than other gas fuels such as natural gas. The static flammable concentration of hydrogen in the air ranges from 4 to 75% vol, making it very easy for accidental leakage of hydrogen to cause combustion or explosion accidents. Therefore, real-time monitoring of hydrogen leakage has become a necessary measure to prevent catastrophic events and reduce the risks of hydrogen energy infrastructure.

[0003] Fiber optic sensing technology has become one of the important means for detecting hydrogen transmission pipeline leaks at this stage due to its high sensitivity to environmental changes. Fiber optic sensors mainly include: distributed temperature sensors, distributed acoustic sensors and distributed strain sensors: when hydrogen leaks, distributed temperature sensors detect the pipeline leak location by real-time monitoring of the temperature distribution along the optical fiber, distributed acoustic sensors detect the pipeline leak location by detecting the sound wave vibrations felt by the optical fiber, and distributed strain sensors detect pipeline leaks by detecting the deformation or stress changes of the pipeline.

[0004] However, the laying of optical fiber sensors is usually based on the manual experience of staff, lacking scientific simulation of hydrogen transmission pipeline scenarios, and optical fiber sensors laid based on manual experience are difficult to perform effective detection in complex hydrogen transmission pipeline environments, resulting in poor detection of hydrogen leaks and difficulty meeting actual needs.

[0005] Therefore, an intelligent detection method for hydrogen transmission pipeline leakage based on optical fiber sensor is proposed. Summary of the invention

[0006] The present invention aims at the deficiencies in the prior art and provides an intelligent detection method for hydrogen transmission pipeline leakage based on optical fiber sensors, so as to solve the problem that in the traditional technology, optical fiber sensors are laid according to human experience, but the pipeline leakage detection effect of the hydrogen transmission pipeline is poor and it is difficult to meet the actual needs.

[0007] In order to achieve the above object, the present invention provides a method for intelligent detection of hydrogen transmission pipeline leakage based on optical fiber sensor, comprising the following steps: Step 100: Acquire pipeline data and pipeline path data of a hydrogen transmission pipeline, and acquire environmental data of an environment surrounding the hydrogen transmission pipeline; Step 200: Establishing a three-dimensional pipeline model of the hydrogen transmission pipeline according to the pipeline data, pipeline path data and environmental data; Step 300: performing grid processing according to the pipeline three-dimensional model to obtain a pipeline grid three-dimensional model; Step 400: Based on the pipeline grid three-dimensional model, simulate a hydrogen leakage and diffusion experiment, obtain simulated leakage points and simulated diffusion conditions of the pipeline grid three-dimensional model, and generate simulated experiment data; Step 500: Simulate laying of optical fibers and sensor components on the pipeline grid three-dimensional model to construct an initial sensor laying model, perform pipeline leakage detection on the pipeline grid three-dimensional model simulating hydrogen leakage and diffusion, and obtain simulated detection data; Step 600: Optimizing the initial sensor installation model by analyzing the simulation experiment data and the simulation detection data to obtain a sensor intelligent installation model; Step 700: According to the intelligent sensor installation model, combined with cost and detection response time, a detection cost optimization model is obtained, and detection efficiency and cost are evaluated based on the detection cost optimization model to obtain an optical fiber sensor installation optimization plan for the intelligent detection of hydrogen transmission pipeline leakage.

[0008] Furthermore, the step 200 is specifically as follows: Step 210: constructing a corresponding equipment physical model according to the pipeline data; Step 220: placing the equipment physical model in the modeling space according to a preset scaling ratio, and adjusting the orientation of the equipment physical model according to the actual connection conditions of the pipeline; Step 230: obtaining the topological relationship of the physical model of the equipment according to the pipeline path data, connecting the pipeline equipment, and constructing a virtual hydrogen transmission pipeline; Step 240: adjusting the buried depth of the virtual hydrogen transmission pipeline according to the terrain data in the environmental data, and constructing the geological environment around the virtual hydrogen transmission pipeline to generate the three-dimensional model of the pipeline.

[0009] Furthermore, the step 300 is specifically as follows: Step 310: Acquire a virtual hydrogen transmission pipeline in the three-dimensional pipeline model; Step 320: gridding the straight pipe section in the virtual hydrogen transmission pipeline according to a preset standard grid; Step 330: Meshing the complex structure segment in the virtual hydrogen transmission pipeline according to the local encrypted grid; Step 340: Obtain historical leakage information of the hydrogen transmission pipeline, analyze historical fault points and historical pipeline damage information of the hydrogen transmission pipeline, dynamically encrypt corresponding pipeline locations and equipment in the virtual hydrogen transmission pipeline, and obtain a pipeline grid three-dimensional model.

[0010] Furthermore, the step 400 is specifically as follows: Step 410: simulating hydrogen transmission based on the virtual hydrogen transmission pipeline in the pipeline grid three-dimensional model, and constructing a hydrogen turbulence model; ; in, k is the turbulent kinetic energy, is the turbulent energy dissipation rate, is the partial derivative with respect to time, is the first component of the turbulent mean velocity, is the second component of the turbulent mean velocity, is the first coordinate component of the detection point, is the second coordinate component of the detection point, is the kinematic viscosity coefficient, is the turbulent viscosity coefficient, is the empirical parameter of the turbulent energy transfer equation, are the empirical parameters of the turbulent energy dissipation power transfer equation, is the first empirical parameter of the model, is the second empirical parameter of the model; ; in, is the proportionality coefficient, is the turbulence intensity, is the average turbulent flow velocity strain rate at the detection point; Step 420: randomly selecting a leakage point in the virtual hydrogen transmission pipeline to simulate hydrogen leakage, obtaining hydrogen leakage diffusion conditions through a hydrogen turbulence model, and recording the simulated leakage point and simulated diffusion conditions to obtain simulation experimental data.

[0011] Furthermore, the step 500 is specifically as follows: Step 510: Preset the optical fiber laying path to perform the optical fiber winding and laying on the path of the virtual hydrogen transmission pipeline; Step 520: The preset optical fiber laying method is to arrange the sensor components at equal intervals, and the sensor components are set according to default parameters; Step 530: laying the entire path of the optical fiber and the sensor assembly on the virtual hydrogen transmission pipeline according to the preset optical fiber laying path and the preset optical fiber laying method, and setting the device parameters of the sensor assembly to form an initial sensor laying model; Step 540: Perform pipeline leakage detection on the virtual hydrogen transmission pipeline that simulates hydrogen leakage and diffusion through the initial sensor laying model, obtain the detection leakage point and detection leakage situation, and constitute simulated detection data.

[0012] Furthermore, the step 600 is specifically as follows: Step 610: Analyze the deviation between the simulated experimental data and the simulated detection data by constructing a comprehensive loss function to obtain simulated deviation data; ; in, is the comprehensive loss function, To simulate the detection data in the leakage point coordinates, is the coordinate of the simulated leakage point in the simulated experimental data, To simulate the weight of the leakage point loss function, is the weight of hydrogen diffusion loss function, The first fiber optic sensor i The incident light frequency of each sensor component, is the speed of light in vacuum, The first fiber optic sensor i The refractive index of the core medium of each sensor component, The first fiber optic sensor i The acoustic velocity in the fiber of each sensor component, To simulate the experimental data in i Strain data of hydrogen diffusion at each sensor component, is a constant, is the coverage of the 3D virtual pipeline by the optical fiber sensor, is the detection surface area of ​​the three-dimensional virtual pipeline; Step 620: Based on the simulation deviation data, the model parameters of the initial sensor laying model are optimized with the goal of minimizing the comprehensive loss function. After optimizing the model parameters, the optical fiber and sensor components are re-laid on the virtual hydrogen transmission pipeline until the comprehensive loss function meets the set threshold requirements. The initial sensor laying model that meets the requirements is used as the sensor intelligent laying model.

[0013] Furthermore, the step 700 is specifically as follows: Step 710: setting a cost threshold according to the pipeline length and pipeline area of ​​the virtual hydrogen transmission pipeline; Step 720: assigning cost parameters and response time parameters to the optical fiber and sensor components in the sensor intelligent installation model to obtain a detection cost optimization model; Step 730: When the laying cost of the optical fiber and the sensor assembly is lower than the cost threshold, the simulated leakage point and the position point of the sensor assembly that detects the simulated leakage point are analyzed, and the laying plan of the optical fiber and the sensor assembly is optimized by adjusting the position point of the sensor assembly and the laying quantity of the sensor assembly to improve the detection response time performance; Step 740: Adjust the connection paths between the sensor components to reduce the cost and make the cost lower than the cost threshold.

[0014] Furthermore, the step 740 is specifically as follows: Step 741: Get two connected sensor components Sensor components , based on the sensor components in the pipeline mesh 3D model Sensor components The position relationship of the nodes is used to construct the path optimization space; Step 742: Set sensor components in the path optimization space The position point is set as the starting position, the sensor component The position point is set as the end position, the expected value of the laying direction of the connection path between the sensor components is calculated according to the starting position, the laying direction corresponding to the maximum expected value is selected, the connection path with the end position is constructed, and the test connection path is generated; Step 743: Calculate the fiber cost of the test connection path and compare it with the existing fiber cost. When the fiber cost of the test connection path is lower than the existing fiber cost, set the fiber cost of the test connection path as the optimal fiber cost. Step 744: Generate a test connection path in the path optimization space according to a preset number of iterations, iteratively optimize the optimal fiber cost, and obtain a connection path corresponding to the optimal fiber cost as a sensor component. Sensor components The optimal connection path between Step 745: Perform optical fiber cost optimization adjustment on the connection paths between all sensor components respectively to optimize the optical fiber and sensor component laying plan.

[0015] The beneficial effects of this solution can be known from the description of the above solution. Compared with the prior art, it has the following beneficial effects: (1) A three-dimensional pipeline grid model is built for the hydrogen transmission pipeline, and the laying of optical fiber and sensor components is simulated based on the sensor intelligent laying model. This solves the problem of poor detection effect caused by the reliance on manual experience of workers in traditional technologies. It can improve the hydrogen leakage detection effect in a complex hydrogen transmission pipeline environment and meet the leakage detection needs of the diversified and complex scenarios of hydrogen transmission pipelines. (2) The laying plan is optimized through the detection cost optimization model, which ensures the detection accuracy while improving the detection efficiency and reducing the fiber optic laying cost, making the output fiber optic sensor laying optimization plan more practical; (3) The straight pipe section of the virtual hydrogen transmission pipeline in the pipeline three-dimensional model is gridded according to the preset standard grid, and the complex structure section is gridded according to the local encrypted grid. According to the historical leakage of the hydrogen transmission pipeline, the corresponding pipeline positions and equipment in the virtual hydrogen transmission pipeline are dynamically grid encrypted to facilitate the refined detection of the virtual hydrogen transmission pipeline in the simulated hydrogen leakage experiment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0017] In order to clearly illustrate the technical features of this solution, this solution is described below through a specific implementation method.

[0018] like Figure 1 As shown, this embodiment is a hydrogen transmission pipeline leakage intelligent detection method based on optical fiber sensor, comprising the following steps: Step 100: Acquire pipeline data and pipeline path data of the hydrogen transmission pipeline, and acquire environmental data of the surrounding environment of the hydrogen transmission pipeline; Step 200: Establishing a three-dimensional pipeline model of the hydrogen transmission pipeline according to the pipeline data, pipeline path data and environmental data; Step 300: Performing mesh processing according to the pipeline three-dimensional model to obtain a pipeline mesh three-dimensional model; Step 400: Based on the pipeline grid three-dimensional model, simulate the hydrogen leakage and diffusion experiment, obtain the simulated leakage point and simulated diffusion situation of the pipeline grid three-dimensional model, and generate simulation experiment data; Step 500: Simulate laying of optical fibers and sensor components on the pipeline grid three-dimensional model, construct an initial sensor laying model, perform pipeline leakage detection on the pipeline grid three-dimensional model simulating hydrogen leakage and diffusion, and obtain simulated detection data; Step 600: Optimizing the initial sensor deployment model by analyzing the simulation experiment data and the simulation detection data to obtain a sensor intelligent deployment model; Step 700: According to the intelligent sensor installation model, combined with the cost and detection response time, a detection cost optimization model is obtained, and the detection efficiency and cost are evaluated based on the detection cost optimization model, and the optical fiber and sensor component installation plan is optimized to obtain the optical fiber sensor installation optimization plan for intelligent detection of hydrogen transmission pipeline leakage.

[0019] The pipeline data in step 100 includes the pipe diameter data, material data, pipe wall thickness and pump station equipment data, valve equipment data, and joint equipment data of the hydrogen transmission pipeline; The pipeline path data of step 100 includes the main pipeline position data, branch pipeline position data, pipeline bifurcation position data, elbow position data and branch point position data of the hydrogen transmission pipeline; The environmental data in step 100 includes terrain data, building data, obstacle data, and vegetation coverage around the hydrogen transmission pipeline.

[0020] Step 200 is specifically as follows: Step 210: constructing a corresponding equipment physical model according to the pipeline data; Step 220: placing the physical model of the equipment in the modeling space according to a preset scaling ratio, and adjusting the orientation of the physical model of the equipment according to the actual connection conditions of the pipeline; Step 230: Obtain the topological relationship of the equipment physical model according to the pipeline path data, connect the pipeline equipment, and build a virtual hydrogen transmission pipeline; Step 240: Adjust the burial depth of the virtual hydrogen transmission pipeline according to the terrain data in the environmental data, construct the geological environment around the virtual hydrogen transmission pipeline, add environmental elements in the modeling space according to the building data, obstacle data and vegetation coverage in the environmental data, and generate a three-dimensional model of the pipeline.

[0021] Step 300 is specifically as follows: Step 310: Acquire a virtual hydrogen transmission pipeline in the three-dimensional pipeline model; Step 320: gridding the straight pipe section in the virtual hydrogen transmission pipeline according to a preset standard grid; Step 330: Meshing the complex structure segment in the virtual hydrogen transmission pipeline according to the local encrypted grid; Among them, the complex structure section includes the pipeline bifurcation section, elbow location section and equipment connection section.

[0022] Step 340: Obtain historical leakage information of the hydrogen transmission pipeline, analyze historical fault points and historical pipeline damage information of the hydrogen transmission pipeline, dynamically encrypt the corresponding pipeline locations and equipment in the virtual hydrogen transmission pipeline, and obtain a pipeline grid three-dimensional model.

[0023] Step 400 is specifically as follows: Step 410: simulating hydrogen transmission based on a virtual hydrogen transmission pipeline in the pipeline grid three-dimensional model, and constructing a hydrogen turbulence model; ; in, k is the turbulent kinetic energy, is the turbulent energy dissipation rate, is the partial derivative with respect to time, is the first component of the turbulent mean velocity, is the second component of the turbulent mean velocity, is the first coordinate component of the detection point, is the second coordinate component of the detection point, is the kinematic viscosity coefficient, is the turbulent viscosity coefficient, is the empirical parameter of the turbulent energy transfer equation, are the empirical parameters of the turbulent energy dissipation power transfer equation, is the first empirical parameter of the model, is the second empirical parameter of the model; ; in, is the proportionality coefficient, is the turbulence intensity, is the average turbulent flow velocity strain rate at the detection point; Step 420: randomly selecting leakage points in the virtual hydrogen transmission pipeline to simulate hydrogen leakage, obtaining hydrogen leakage diffusion conditions through a hydrogen turbulence model, and recording simulated leakage points and simulated diffusion conditions to obtain simulation experimental data.

[0024] Step 500 is specifically as follows: Step 510: Preset the optical fiber laying path to perform optical fiber winding and laying on the path of the virtual hydrogen transmission pipeline; Step 520: The preset optical fiber laying method is to arrange the sensor components at equal intervals, and the sensor components are set according to default parameters; Step 530: laying the entire path of the optical fiber and the sensor components on the virtual hydrogen transmission pipeline according to the preset optical fiber laying path and the preset optical fiber laying method, and setting the equipment parameters of the sensor components to form an initial sensor laying model; Step 540: Perform pipeline leakage detection on the virtual hydrogen transmission pipeline that simulates hydrogen leakage and diffusion through the initial sensor laying model, obtain the detection leakage point and detection leakage situation, and constitute simulated detection data.

[0025] Step 600 is specifically as follows: Step 610: Analyze the deviation between the simulated experimental data and the simulated detection data by constructing a comprehensive loss function to obtain simulated deviation data; ; in, is the comprehensive loss function, To simulate the detection data in the leakage point coordinates, is the coordinate of the simulated leakage point in the simulated experimental data, To simulate the weight of the leakage point loss function, is the weight of hydrogen diffusion loss function, The first fiber optic sensor i The incident light frequency of each sensor component, is the speed of light in vacuum, The first fiber optic sensor i The refractive index of the core medium of each sensor component, The first fiber optic sensor i The acoustic velocity in the fiber of each sensor component, To simulate the experimental data in i Strain data of hydrogen diffusion at each sensor component, is a constant, is the coverage of the 3D virtual pipeline by the optical fiber sensor, is the detection surface area of ​​the three-dimensional virtual pipeline; The comprehensive loss function analyzes the deviation between the simulated experimental data and the simulated detection data according to the deviation between the detection leakage point coordinates in the simulated detection data and the simulated leakage position point coordinates in the simulated experimental data, the deviation between the detection strain data in the simulated detection data and the strain data in the simulated experimental data, and the sensor coverage rate; the detection strain data in the simulated detection data is , the strain data in the simulated experimental data is ; Step 620: According to the simulation deviation data, the model parameters of the initial sensor laying model are optimized with the goal of minimizing the comprehensive loss function. After optimizing the model parameters, the optical fiber and sensor components are laid again on the virtual hydrogen transmission pipeline until the comprehensive loss function meets the set threshold requirements. The initial sensor laying model that meets the requirements is used as the sensor intelligent laying model. By constructing a comprehensive loss function, the deviation analysis between the simulated experimental data and the simulated detection data is realized. Based on the obtained simulation deviation data, the model parameters of the initial sensor laying model are optimized to obtain the sensor intelligent laying model. The optical fiber sensor laying plan generated by the sensor intelligent laying model has high hydrogen leakage detection accuracy.

[0026] Step 700 is specifically as follows: Step 710: setting a cost threshold according to the pipeline length and pipeline area of ​​the virtual hydrogen transmission pipeline; Step 720: assigning cost parameters and response time parameters to the optical fiber and sensor components in the sensor intelligent deployment model to obtain a detection cost optimization model; Step 730: When the laying cost of the optical fiber and the sensor assembly is lower than the cost threshold, the simulated leakage point and the position point of the sensor assembly that detects the simulated leakage point are analyzed, and the laying plan of the optical fiber and the sensor assembly is optimized by adjusting the position point of the sensor assembly and the laying quantity of the sensor assembly to improve the detection response time performance; Step 740: Adjust the connection paths between the sensor components to reduce the cost and the cost must be lower than the cost threshold.

[0027] Step 740 is specifically as follows: Step 741: Obtain two connected sensor components, respectively defined as sensor components Sensor components , based on the sensor components in the pipeline mesh 3D model Sensor components The position relationship of the nodes is used to construct the path optimization space; Step 742: Set sensor components in the path optimization space The position point is set as the starting position, the sensor component The position point is set as the end position, the expected value of the laying direction of the connection path between the sensor components is calculated according to the starting position, the laying direction corresponding to the maximum expected value is selected, the connection path with the end position is constructed, and the test connection path is generated; Step 743: Calculate the fiber cost of the test connection path and compare it with the existing fiber cost. When the fiber cost of the test connection path is lower than the existing fiber cost, set the fiber cost of the test connection path as the optimal fiber cost. Step 744: Generate a test connection path in the path optimization space according to the preset number of iterations, iteratively optimize the optimal fiber cost, and obtain the connection path corresponding to the optimal fiber cost as the sensor component Sensor components The optimal connection path between Step 745: Perform optical fiber cost optimization adjustment on the connection paths between all sensor components respectively to optimize the optical fiber and sensor component laying plan.

[0028] Technical features not described in the present invention can be achieved through or by adopting existing technologies and will not be described in detail herein. Of course, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by ordinary technicians in this technical field within the essential scope of the present invention should also fall within the scope of protection of the present invention.

Claims

1. An intelligent detection method for hydrogen transmission pipeline leakage based on optical fiber sensor, characterized in that: The following steps are involved: Step 100: Acquire pipeline data and pipeline path data of a hydrogen transmission pipeline, and acquire environmental data of an environment surrounding the hydrogen transmission pipeline; Step 200: Establishing a three-dimensional pipeline model of the hydrogen transmission pipeline according to the pipeline data, pipeline path data and environmental data; Step 300: performing grid processing according to the pipeline three-dimensional model to obtain a pipeline grid three-dimensional model; Step 400: Based on the pipeline grid three-dimensional model, simulate a hydrogen leakage and diffusion experiment, obtain simulated leakage points and simulated diffusion conditions of the pipeline grid three-dimensional model, and generate simulated experiment data; Step 500: Simulate laying of optical fibers and sensor components on the pipeline grid three-dimensional model to construct an initial sensor laying model, and perform pipeline leakage detection on the pipeline grid three-dimensional model simulating hydrogen leakage and diffusion to obtain simulated detection data; Step 600: Optimizing the initial sensor installation model by analyzing the simulation experiment data and the simulation detection data to obtain a sensor intelligent installation model; Step 700: According to the intelligent sensor installation model, combined with cost and detection response time, a detection cost optimization model is obtained, and detection efficiency and cost are evaluated based on the detection cost optimization model to obtain an optical fiber sensor installation optimization plan for the intelligent detection of hydrogen transmission pipeline leakage.

2. According to claim 1, a hydrogen transmission pipeline leakage intelligent detection method based on optical fiber sensor is characterized in that: The step 200 is specifically as follows: Step 210: constructing a corresponding equipment physical model according to the pipeline data; Step 220: placing the equipment physical model in the modeling space according to a preset scaling ratio, and adjusting the orientation of the equipment physical model according to the actual connection conditions of the pipeline; Step 230: obtaining the topological relationship of the physical model of the equipment according to the pipeline path data, connecting the pipeline equipment, and constructing a virtual hydrogen transmission pipeline; Step 240: adjusting the buried depth of the virtual hydrogen transmission pipeline according to the terrain data in the environmental data, and constructing the geological environment around the virtual hydrogen transmission pipeline to generate the three-dimensional model of the pipeline.

3. The intelligent detection method for hydrogen transmission pipeline leakage based on optical fiber sensor according to claim 2 is characterized in that: The step 300 is specifically as follows: Step 310: Acquire a virtual hydrogen transmission pipeline in the three-dimensional pipeline model; Step 320: gridding the straight pipe section in the virtual hydrogen transmission pipeline according to a preset standard grid; Step 330: Meshing the complex structure segment in the virtual hydrogen transmission pipeline according to the local encrypted grid; Step 340: Obtain historical leakage information of the hydrogen transmission pipeline, analyze historical fault points and historical pipeline damage information of the hydrogen transmission pipeline, dynamically encrypt corresponding pipeline locations and equipment in the virtual hydrogen transmission pipeline, and obtain a pipeline grid three-dimensional model.

4. The intelligent detection method for hydrogen transmission pipeline leakage based on optical fiber sensor according to claim 3 is characterized in that: The step 400 is specifically as follows: Step 410: simulating hydrogen transmission based on the virtual hydrogen transmission pipeline in the pipeline grid three-dimensional model, and constructing a hydrogen turbulence model; ； in, k is the turbulent kinetic energy, is the turbulent energy dissipation rate, is the partial derivative with respect to time, is the first component of the turbulent mean velocity, is the second component of the turbulent mean velocity, is the first coordinate component of the detection point, is the second coordinate component of the detection point, is the kinematic viscosity coefficient, is the turbulent viscosity coefficient, is the empirical parameter of the turbulent kinetic energy transfer equation, are the empirical parameters of the turbulent energy dissipation power transfer equation, is the first empirical parameter of the model, is the second empirical parameter of the model; ； in, is the proportionality coefficient, is the turbulence intensity, is the average turbulent flow velocity strain rate at the detection point; Step 420: randomly selecting a leakage point in the virtual hydrogen transmission pipeline to simulate hydrogen leakage, obtaining hydrogen leakage diffusion conditions through a hydrogen turbulence model, and recording the simulated leakage point and simulated diffusion conditions to obtain simulation experimental data.

5. The intelligent detection method for hydrogen transmission pipeline leakage based on optical fiber sensor according to claim 4 is characterized in that: The step 500 is specifically as follows: Step 510: Preset the optical fiber laying path to perform the optical fiber winding and laying on the path of the virtual hydrogen transmission pipeline; Step 520: The preset optical fiber laying method is to arrange the sensor components at equal intervals, and the sensor components are set according to default parameters; Step 530: laying the entire path of the optical fiber and the sensor assembly on the virtual hydrogen transmission pipeline according to the preset optical fiber laying path and the preset optical fiber laying method, and setting the device parameters of the sensor assembly to form an initial sensor laying model; Step 540: Perform pipeline leakage detection on the virtual hydrogen transmission pipeline that simulates hydrogen leakage and diffusion through the initial sensor laying model, obtain the detection leakage point and detection leakage situation, and constitute simulated detection data.

6. The intelligent detection method for hydrogen transmission pipeline leakage based on optical fiber sensor according to claim 5 is characterized in that: The step 600 is specifically as follows: Step 610: Analyze the deviation between the simulated experimental data and the simulated detection data by constructing a comprehensive loss function to obtain simulated deviation data; ； in, is the comprehensive loss function, To simulate the detection data in the leakage point coordinates, is the coordinate of the simulated leakage point in the simulated experimental data, To simulate the weight of the leakage point loss function, is the weight of hydrogen diffusion loss function, The first fiber optic sensor i The incident light frequency of each sensor component, is the speed of light in vacuum, The first fiber optic sensor i The refractive index of the fiber core medium of each sensor component, The first fiber optic sensor i The acoustic velocity in the fiber of each sensor component, To simulate the experimental data in i Strain data of hydrogen diffusion at each sensor component, is a constant, is the coverage of the 3D virtual pipeline by the optical fiber sensor, is the detection surface area of ​​the three-dimensional virtual pipeline; Step 620: Based on the simulation deviation data, the model parameters of the initial sensor laying model are optimized with the goal of minimizing the comprehensive loss function. After optimizing the model parameters, the optical fiber and sensor components are re-laid on the virtual hydrogen transmission pipeline until the comprehensive loss function meets the set threshold requirements. The initial sensor laying model that meets the requirements is used as the sensor intelligent laying model.

7. The intelligent detection method for hydrogen transmission pipeline leakage based on optical fiber sensor according to claim 6 is characterized in that: The step 700 is specifically as follows: Step 710: setting a cost threshold according to the pipeline length and pipeline area of ​​the virtual hydrogen transmission pipeline; Step 720: assigning cost parameters and response time parameters to the optical fiber and sensor components in the sensor intelligent installation model to obtain a detection cost optimization model; Step 730: When the laying cost of the optical fiber and the sensor assembly is lower than the cost threshold, the simulated leakage point and the position point of the sensor assembly that detects the simulated leakage point are analyzed, and the laying plan of the optical fiber and the sensor assembly is optimized by adjusting the position point of the sensor assembly and the laying quantity of the sensor assembly to improve the detection response time performance; Step 740: Adjust the connection paths between the sensor components to reduce the cost and make the cost lower than the cost threshold.

8. The intelligent detection method for hydrogen transmission pipeline leakage based on optical fiber sensor according to claim 7 is characterized in that: The step 740 is specifically as follows: Step 741: Get two connected sensor components Sensor components , based on the sensor components in the pipeline mesh 3D model Sensor components The position relationship of the nodes is used to construct the path optimization space; Step 742: Set sensor components in the path optimization space The position point is set as the starting position, the sensor component The position point is set as the end position, the expected value of the laying direction of the connection path between the sensor components is calculated according to the starting position, the laying direction corresponding to the maximum expected value is selected, the connection path with the end position is constructed, and the test connection path is generated; Step 743: Calculate the fiber cost of the test connection path and compare it with the existing fiber cost. When the fiber cost of the test connection path is lower than the existing fiber cost, set the fiber cost of the test connection path as the optimal fiber cost. Step 744: Generate a test connection path in the path optimization space according to a preset number of iterations, iteratively optimize the optimal fiber cost, and obtain a connection path corresponding to the optimal fiber cost as a sensor component. Sensor components The optimal connection path between Step 745: Perform optical fiber cost optimization adjustment on the connection paths between all sensor components respectively to optimize the optical fiber and sensor component laying plan.

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