Gas leakage risk simulation method and device based on laser remote measurement and medium

Abstract

The embodiment of the invention discloses a gas leakage risk simulation method and device based on laser remote measurement and a medium. The method comprises the following steps: dividing a region to be simulated into a plurality of two-dimensional geographic grids; laser telemetering equipment is used for monitoring the gas pollutant concentration of a plurality of monitoring grids in the to-be-simulated area in real time, the laser telemetering equipment is deployed at the high position of the boundary of a leakage risk area in the to-be-simulated area, and a monitoring view angle covers a leakage risk device in the leakage risk area and surrounding grids of the leakage risk device; and identifying the monitoring grid with the instantaneous increment of the pollutant concentration greater than a set positive threshold value as a suspected leakage grid, adding the suspected leakage grid as a leakage source in the atmospheric diffusion simulation model, and performing minute-level or higher-time-precision simulation on the pollutant leakage process of the leakage source. According to the embodiment, leakage events in a large range can be captured in real time, and the diffusion path can be dynamically simulated.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of atmospheric simulation technology, and in particular to a gas leakage risk simulation method, device and medium based on laser telemetry. Background Art

[0002] With the rapid development of the chemical industry, safety risks in chemical parks and hazardous chemical storage and transportation areas are becoming increasingly prominent. Chemical gas leaks are frequent, posing a serious threat to the surrounding environment and human health. Chemical parks are densely populated with potential leak sources. After a leak occurs, the diffusion of pollutants is influenced by multiple factors, including meteorological conditions and topographical features, and exhibits strong temporal and spatial uncertainty. In particular, sudden releases from multiple leak sources at different times can easily lead to rapid spread of pollutants in a short period of time. Due to the sudden, random nature of leaks, and their complex temporal and spatial distribution, failure to accurately determine the location and impact of a leak immediately poses a serious threat to the health of the surrounding population and the ecological environment, potentially triggering secondary disasters. Therefore, the key tasks after an accident are to rapidly identify the leak source, dynamically simulate the diffusion path, and quickly assess the impact range of the pollution, providing a scientific basis for emergency decision-making, personnel evacuation, and subsequent disposal.

[0003] Currently, the pollutant gas leak detection and alarm systems used in chemical parks primarily utilize fixed gas detectors based on the "Petrochemical Combustible and Toxic Gas Detection and Alarm Design Standard" (GB / T50493-2019). These detectors are unable to meet the requirements for rapid location and response. Patent applications CN201310029240.X disclose a method based on grid-based toxic gas diffusion simulation, and CN201310082010.X develop a method and system for real-time location analysis of gas pipeline leak sources. However, neither system is able to capture leaks over a large area in real time, identify leak sources promptly, or dynamically simulate diffusion paths. Summary of the Invention

[0004] Embodiments of the present invention provide a gas leakage risk simulation method, device, and medium based on laser telemetry to solve at least one of the above problems.

[0005] In a first aspect, an embodiment of the present invention provides a gas leakage risk simulation method based on laser telemetry, comprising:

[0006] Divide the area to be simulated into multiple two-dimensional geographic grids;

[0007] Using laser telemetry equipment, real-time monitoring of gas pollutant concentrations in multiple monitoring grids in the area to be simulated is performed, wherein the laser telemetry equipment is deployed at a high point at the boundary of the leakage risk area in the area to be simulated, and the monitoring angle of the laser telemetry equipment covers the leakage risk device and its surrounding grids in the leakage risk area;

[0008] Monitoring grids with instantaneous increases in pollutant concentration greater than a set positive threshold are identified as suspected leakage grids and added as leakage sources in the atmospheric diffusion simulation model. The pollutant leakage process of the leakage source is simulated at the minute level or higher time accuracy;

[0009] The following operations are performed during the simulation:

[0010] S1, subtract the simulated concentration from the pollutant monitoring concentration of each monitoring grid in real time;

[0011] S2. Identify the first monitoring grid with a positive difference and an instantaneous increment of the difference greater than a set positive threshold as a new suspected leakage grid and add it in real time as a new leakage source in the atmospheric diffusion simulation model, and perform subsequent simulations based on the new and old leakage sources;

[0012] S3. For the second monitoring grid whose difference is negative and whose instantaneous decrement is less than the set negative threshold value in multiple consecutive time steps, extract the continuous area with negative difference around the monitoring grid in the multiple time steps; if the continuous area in the same time step is clustered, and the clustered area gradually expands over time, delete the leakage source covered by the clustered area in each time step, and perform subsequent simulation based on the remaining leakage source.

[0013] In a second aspect, an embodiment of the present invention provides an electronic device, comprising:

[0014] one or more processors;

[0015] a memory for storing one or more programs;

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the gas leakage risk simulation method based on laser telemetry described in any embodiment.

[0017] In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the gas leakage risk simulation method based on laser telemetry described in any embodiment.

[0018] In summary, this embodiment provides a gas leakage risk simulation method based on laser telemetry, which enhances the rapid response capability of leakage simulation through the scanning results of laser telemetry equipment and SCICHEM simulation technology. Among them, the laser gas telemetry equipment can break through the limitations of traditional reliance on fixed micro-stations, has flexible deployment and a wide monitoring range, and can quickly capture the occurrence time and initial distribution characteristics of leaked gas, providing instant and accurate simulation starting conditions for the SCICHEM model; and the SCICHEM model can achieve instantaneous simulation at the minute level or finer time granularity, accurately reflecting the diffusion process of leaked gas, and providing rapid and timely technical support for responding to sudden environmental events. In addition, the method of this embodiment can also achieve effective leakage response and preliminary impact assessment in areas where telemetry conditions are limited or inaccessible, thereby providing data support for the prediction of consequences of leakage accidents and protection optimization in a larger range. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 This is a flow chart of a gas leakage risk simulation method based on laser telemetry provided by an embodiment of the present invention;

[0021] Figure 2 This is a top view of a region after grid division provided by an embodiment of the present invention;

[0022] Figure 3 This is a simulation diagram of the gas diffusion range after a 2-minute leak in an application case provided by an embodiment of the present invention;

[0023] Figure 4 This is a simulation diagram of the gas diffusion range after 4 minutes of leakage in the application case provided by the embodiment of the present invention;

[0024] Figure 5 This is a simulation diagram of the gas diffusion range after a 5-minute leak in an application case provided by an embodiment of the present invention;

[0025] Figure 6 This is a simulation diagram of the gas diffusion range after 10 minutes of leakage in the application case provided by the embodiment of the present invention;

[0026] Figure 7 This is a simulation diagram of the gas diffusion range after 20 minutes of leakage in the application case provided by the embodiment of the present invention;

[0027] Figure 8 This is a simulation diagram of the gas diffusion range after 30 minutes of leakage in the application case provided by the embodiment of the present invention;

[0028] Figure 9 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0029] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

[0030] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0031] In the description of the present invention, it should also be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood broadly. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0032] Figure 1 This is a flow chart of a gas leakage risk simulation method based on laser telemetry provided by an embodiment of the present invention. This method is executed by electronic equipment and combines laser telemetry monitoring equipment with an atmospheric diffusion simulation model to achieve dynamic leakage tracking and spatial diffusion analysis with minute-level or even higher time accuracy, providing data support for environmental risk assessment, emergency dispatch, public health protection, etc. Figure 1 As shown, the method specifically includes:

[0033] S110: Divide the area to be simulated into multiple two-dimensional geographic grids.

[0034] In this embodiment, a geographical area to be monitored and simulated is first determined, and the area is divided into a plurality of plane grids according to the grid resolution. For example, the area to be simulated may be a region including an industrial park.

[0035] In addition, the time range of the monitoring simulation can also be determined, including the starting time and time step. The time step can be comprehensively determined based on the time granularity that can be achieved by subsequent laser telemetry equipment and atmospheric diffusion models.

[0036] S120. Use laser telemetry equipment to monitor the gas pollutant concentrations of multiple grids in the area to be simulated in real time, wherein the laser telemetry equipment is deployed at a high place at the boundary of the leakage risk area in the area to be simulated, and the monitoring angle of the laser telemetry equipment covers the leakage risk device and its surrounding area in the leakage risk area.

[0037] After the simulated area is determined, this embodiment further defines a leakage risk zone within that area, which serves as the deployment location for the laser telemetry equipment. This zone can be an area that covers and is larger than the leakage risk device in the simulated area. Deploying the laser telemetry equipment at a higher position on the boundary of the leakage risk zone facilitates the laser telemetry equipment to scan and monitor the gaseous pollutant concentrations of the leakage risk device and its surrounding grid from a higher and farther distance. Gaseous pollutants include toxic gases, flammable gases, or other gaseous chemicals that require monitoring.

[0038] For example, taking the above-mentioned area to be simulated including the industrial park as an example, the leakage risk area can be the industrial park, and the leakage risk device is the equipment, buildings, etc. with leakage risks in the industrial park, such as pipelines and chimneys. The laser telemetry equipment will be deployed at a higher position (such as 20 meters and above) at the boundary of the industrial park, and by adjusting the angle of the laser telemetry equipment, it can monitor in real time the grid where the pipelines, chimneys and other leakage risk devices are located and the surrounding grids. For the convenience of distinction and description, this embodiment refers to the grid monitored in real time by the laser telemetry equipment as a monitoring grid, and these monitoring grids are usually only part of the leakage risk area. In addition, the area to be simulated may also be the same as the leakage risk area, and this embodiment does not impose specific restrictions.

[0039] Furthermore, the laser telemetry equipment here includes laser / infrared spectroscopy non-contact remote sensing equipment. Compared with traditional detection methods, laser telemetry equipment has significant advantages such as flexibility, rapid response, and wide coverage, and is particularly suitable for safe operations in high-risk environments. This type of equipment can detect a wide variety of gases, is less restricted by site conditions, has a wide monitoring range, rapid identification and alarm, and intuitive results, which can achieve the true meaning of "what you see is what you get". Optionally, in addition to the scanning monitoring data of multiple grids by the laser telemetry equipment, the monitoring data provided by fixed micro stations can also be called as a monitoring data source.

[0040] S130. Identify the monitoring grids whose instantaneous increment of pollutant concentration is greater than the set positive threshold as suspected leakage grids and add them as leakage sources in the atmospheric diffusion simulation model, and simulate the pollutant leakage process of the leakage source with a time accuracy of minutes or higher.

[0041] This embodiment identifies suspected leaking grids based on the instantaneous increase in pollutant concentration in the monitoring grid. This instantaneous increase can be calculated by subtracting the pollutant concentration in the previous time step from the pollutant concentration in the current time step. For a grid with a concentration of zero in the previous time step, if the concentration in the monitoring grid suddenly increases above a set positive threshold in the current time step, a leak can be preliminarily identified in that grid. Using this grid as a leak source in atmospheric diffusion simulation allows for a timely understanding of the approximate diffusion process of pollutants throughout the simulated area.

[0042] In a specific embodiment, the SCICHEM (SCIPUFF with chemistry, a chemical coupling extension based on the second-order closed integral puff model framework) model can be used to simulate the leakage and diffusion of gaseous chemicals, aiming to accurately simulate the actual release process of the source, thereby capturing the emission conditions of the leakage source at different time points. First, meteorological data simulation can be performed according to the time range determined in S110. Optionally, high-resolution meteorological data generated by the WRF (Weather Research and Forecasting) model or measured data from ground micro-monitoring stations / conventional meteorological stations can be used to construct a real-time three-dimensional meteorological field covering the simulation area, and key meteorological elements required by the SCICHEM model (such as wind speed, wind direction, temperature, turbulence, etc.) can be extracted and converted into meteorological data files that conform to the SCICHEM model input format.

[0043] Specifically, the SCICHEM model is a Lagrangian diffusion model, based on the Lagrangian photochemical diffusion model of the second-order closed integrated puff diffusion model. SCIPUFF (Second-order Closure Integrated PUFF, second-order closed integrated puff model) is the core module of SCICHEM. It combines the second-order closure method of the atmospheric boundary layer and simulates the three-dimensional plume of arbitrary time complex changes from one or more sources based on Gaussian theory. It is widely used in research such as pollution tracing, pollution diffusion simulation and risk leakage simulation. In addition, the core module of the hazardous substance leakage simulation software HPAC (Hazard Prediction And Assessment Capability) is also SCIPUFF. Therefore, the SCICHEM model has good accuracy and effectiveness in leakage simulation, so that it can better simulate the pollutant leakage and diffusion process.

[0044] Optionally, in each time step of this embodiment, once a suspected leakage grid is monitored, it is added as an emission grid in the SCICHEM model, the current moment is used as the emission start moment of the emission grid, and parameters such as the release rate, source type, and height are set. At the same time, the current meteorological driving field data and terrain data are input into the SCICHEM model, so that SCICHEM simulates the entire process of pollutants diffusing outward from the leakage source point in each subsequent time step. Among them, the unit of release rate is g / s (grams / second), which can be converted based on the rate of change of pollutant concentration at the suspected leakage grid. Leakage source types include point sources and surface sources. The type and height of the leakage source can be determined based on the distribution of equipment in the leakage risk area. Specifically, based on the distribution location of equipment in the park, the leakage risk equipment at the leakage source can be determined; based on the type of the equipment, the type and height of the new leakage source can be determined. For example, if there is a chemical transport pipeline in the leakage source grid, then the pipeline height is the leakage source height. The leakage of the pipeline is usually a point leak, and the leakage source is a point source. Each time step will be based on the pollutant concentration distribution obtained by simulating the old leakage source. According to the type and height of the new leakage source, the leakage process simulation of the new leakage source will be started immediately, while the simulation of the old leakage source will be continued.

[0045] After the simulation is complete, the SCICHEM simulation results can be visualized to more intuitively understand the emission impact of the leakage source. For each leakage process, the concentration distribution map output by SCICHEM can be visualized. In combination with geographic information system tools, a dynamic concentration distribution map can be generated to vividly display the leakage process of the leakage source. Through time series graphs, the impact of the leakage source on the surrounding area at different time points can be displayed, emphasizing the concentration changes at different times and locations. The spatiotemporal visualization of simulation results can more realistically reflect the movement and emissions of the leakage source over a certain period of time, providing an intuitive basis for leakage process analysis, decision support, and environmental impact assessment.

[0046] In summary, this embodiment combines laser gas telemetry equipment with the SCICHEM model to enhance the rapid response capability of leak simulation. The laser gas telemetry equipment breaks through the time and space limitations of traditional fixed micro-station monitoring and can be flexibly deployed around the factory area. It has rapid response and multi-point grid scanning capabilities, capturing the specific time and location of leaks in real time and providing the SCICHEM model with high-precision leak source initiation conditions. By coupling the telemetry equipment with the model, not only is the timeliness and accuracy of leak simulations improved, but it also provides a more practical decision-making support tool for sudden environmental events. More specifically, this embodiment has the following advantages:

[0047] (1) The SCICHEM model supports the input of multiple leakage sources, enabling accurate simulation of complex leakage scenarios. In actual chemical environments, leakage is often not a single source burst, but may involve multiple grid sources leaking at different time points. SCICHEM can flexibly set the spatial location, release start time, release intensity, and duration of each source, thereby accurately simulating the instantaneous emission process of multiple sources at different times.

[0048] (2) The SCICHEM model supports the output of high-time-resolution simulation results, and can simulate the diffusion behavior of pollutants at time scales of minutes and seconds. It can more keenly capture the temporal characteristics of multiple leakage sources and provide more timely and realistic leakage diffusion processes for sudden environmental events.

[0049] (3) SCICHEM output has high temporal and spatial resolution, visualizing the temporal and spatial changes during the leakage process. The model calculation results can show the temporal changes in pollutant concentrations, making it easier to observe the pollution superposition effect and diffusion path caused by multiple leakage sources released at different times, improving the understanding of the overall leakage impact range and development trend, and providing scientific support for emergency response and protection decision-making.

[0050] (4) Combining telemetry equipment with the SCICHEM model enables rapid capture and simulation of leaks. This embodiment introduces laser gas telemetry equipment, breaking through the monitoring limitations of traditional fixed microstations. It can be flexibly deployed and scan multiple grid areas in real time to quickly identify the time and location of leaks. The telemetry results can be directly used to drive the SCICHEM model to set the release start conditions for the leak source, achieving efficient monitoring-simulation coupling and significantly improving the response speed and accuracy of sudden leak event simulations.

[0051] Furthermore, to intuitively demonstrate the simulation effect of this embodiment, a case application is introduced below. Assume that a chemical park in Jiujiang City has an area of ​​3×3 kilometers and a grid resolution of 100 meters. The chemical park is used as the area to be simulated and the dangerous leakage area, and is divided into 30×30 (900) grids. Figure 2 As shown, the different numbers represent the second grid number. Laser telemetry equipment, deployed high above the park boundary, boasts rapid scanning capabilities, enabling high-frequency grid-like scans of the park. Once the equipment identifies a localized concentration anomaly, it can quickly identify the suspected leak grid.

[0052] During monitoring, the telemetry equipment identified abnormal emissions in grid No. 188 in the first minute. The initial diagnosis was a rupture in the transmission pipeline, with the source of the leak being the pipeline and the height being 1 meter. The telemetry equipment detected a sudden increase in concentration in another grid (No. 588) in the third minute. This was further determined to be volatile gas escaping from the top of the park's storage tank, at a height of 10 meters.

[0053] Based on the above identification results and meteorological conditions, corresponding emission grids, emission start time, release rate, source type and height parameters can be set for the leakage process. Taking into account the influence of meteorological driving fields, terrain, etc., SCICHEM is used to simulate the entire process of pollutants diffusing from the leakage source point to the outside in each release stage. The simulated concentration results are visualized to complete the simulation of the leakage source.

[0054] Specifically, this embodiment uses the SCICEHM model version 3.3 mode to adopt (Universal Transverse Mercator Grid System) coordinates (unit: kilometer). The terrain height data in the area comes from the United States Geological Survey (scientific research unit data set), and the terrain data accuracy is 90m. The meteorological data input includes the ground meteorological station data of Jiujiang City, Jiangxi Province and the high-altitude simulated meteorological data. The ground meteorological data comes from the daily and hourly data of the Jiujiang City Meteorological Station in 2023 provided by the China Meteorological Administration (station number 54594, 39.72°N, 116.35°E). The ground observation data include wind direction, wind speed, temperature, etc. It is converted into a ground meteorological data input format recognizable by the SCICHEM model through AERMET (AMS / EPA Regulatory Model Meteorological Preprocessor, meteorological preprocessor of the American Meteorological Society / USEPA statutory model).

[0055] The high-altitude simulated meteorological data for Jiujiang City in 2023 were converted from the WRF model simulation results through the MMIF (Mesoscale Model Interface Program) tool, including the air pressure, altitude above the ground, dry-bulb temperature, wind direction and wind speed on different isobaric surfaces at 8 am and 8 pm every day. The vertical direction is divided into 21 layers, with altitudes from 0 to 1919 meters above the ground.

[0056] Based on the concentration distribution map output by SCICHEM and combined with geographic information system tools, the leakage process was visualized. The time series graph shows the impact of the leakage source on the surrounding area at different time points, emphasizing the concentration changes at different times and locations. Figures 3 to 8 They are concentration change diagrams of the leakage source at different time points. The horizontal and vertical coordinates in the figure are the UTM coordinates of each spatial position. The color scale value represents the concentration of pollutants (unit: grams / cubic meter). 1E-05 means 10 to the power of -5, and the other color scale values ​​are similar.

[0057] Furthermore, the leakage source identification method in the above embodiment is applicable to the case where the concentration of the monitoring grid is 0 in the previous time step. In this case, the monitoring grid can be preliminarily identified as a leakage grid as long as a sudden increase in concentration occurs in the current time step. However, in actual applications, there may be another situation: due to the spread of existing leakage sources, some grids already have a certain pollutant concentration when no leakage occurs. In this case, if an instantaneous increase in concentration occurs in the current time step, it is necessary to further determine whether the increase is caused by the continued spread of the existing leakage source or by the leakage itself. In a specific embodiment, this situation can be dealt with in the following way:

[0058] During the simulation, the following operations are performed at each time step:

[0059] S1. Subtract the simulated concentration from the pollutant concentration at each monitoring grid in real time. For the grid described in the above scenario, the simulated concentration represents the spread of pollutants from the old leak source, while the concentration monitored by the laser telemetry equipment represents the actual pollutants monitored.

[0060] S2. A monitoring grid with a positive difference and an instantaneous increment of the difference greater than a set positive threshold is identified as a new suspected leakage grid and added in real time as a new leakage source in the atmospheric diffusion simulation model, and subsequent simulation is performed based on the new and old leakage sources.

[0061] If a leak occurs in a monitoring grid, the simulated concentration is subtracted from the monitored concentration to obtain the instantaneous concentration change caused by the leak. Ideally, a difference greater than 0 indicates a leak. However, given that both device monitoring and model simulations have certain errors, and that brief drifting gas may cause small concentration spikes, this embodiment uses a positive threshold to accommodate these errors and reduce unstable false alarms.

[0062] The above method subtracts the simulated concentration from the monitored concentration and then compares it with the set positive threshold. It is also applicable to grids with an initial concentration of 0 and can more accurately identify new leakage sources.

[0063] Furthermore, in another specific embodiment, after performing S1, another situation may occur, that is, the difference between the measured concentration and the simulated concentration in some grids is negative. This may be caused by measurement error or simulation error, or it may be caused by the original leakage source being promptly controlled and stopped, or the original leakage source being misidentified. For such grids, this embodiment provides the following methods to promptly correct the deviation:

[0064] If the difference value of a monitoring grid is negative in the current time step T and the previous multiple consecutive time steps, then the difference value Δc of the next time step can be used for each two adjacent time steps. t Subtract the difference Δc from the previous time step t―1 , get the instantaneous change of the difference. If the instantaneous change is decreasing (ie Δc t ―Δc t―1 <0), and the reduction amount Δc t ―Δc t―1 If the value is less than the set negative threshold at multiple time steps, it means that the simulated concentration at the grid is continuously higher than the monitored concentration by a certain level, which is most likely caused by the original leakage source stopping leakage or identification error.

[0065] In order to further verify whether this is the cause, the following operation can be performed for each of the multiple consecutive time steps: extract the grids with negative difference values ​​around the monitoring grid, and determine whether these grids form a continuous clustered area. If such a continuous clustered area exists in all time steps, continue to determine whether the clustered area gradually increases over time. If the clustered areas in these time steps gradually expand over time, it can be basically determined that these clustered areas are caused by the simulation model having more leakage sources than the actual situation, and the leakage source should be removed from the simulation model. Optionally, the leakage source covered by the clustered area in each time step can be found in the simulation model, deleted, and subsequent simulations are performed based on the remaining leakage sources.

[0066] Specifically, in the first time step after deleting a leak source (i.e., time step T mentioned above), the pollutant concentration distribution of the last time step before the previous time step can be used as the initial concentration distribution. A leakage process simulation equal to the total duration of the previous time steps is performed based on the remaining leak source to obtain the simulation result for the current time step. For example, if the duration of each time step is Δt, then under normal circumstances, the concentration result is calculated based on the diffusion duration of Δt for each simulation. However, in the case of deleting the leak source, assuming the total duration of the previous time steps is N×Δt (N is the number of time steps), the pollutant concentration distribution of the last time step before the previous time steps can be used as the basic concentration distribution, and the concentration distribution result for the current time step is calculated based on the diffusion duration of N×Δt to compensate for the vacancies in the intermediate time steps. It is worth noting that although simulation result errors have occurred in multiple time steps, since the errors have not spread widely and the past errors are no longer significant for the decision analysis of the current time step, it is only necessary to correct the errors in the current time step, without resimulating the past time steps with errors.

[0067] Furthermore, the above-mentioned clustered areas can be identified by analysts based on experience, or they can be automatically determined by electronic equipment using the contour method. Optionally, for a continuous area composed of grids with negative difference values ​​in a single time step, contour lines can be drawn in the area with pollutant concentration as high-value data; if multiple closed contour lines can be obtained in the end, it can be automatically determined that the continuous area is clustered. If, during the contour line drawing process, it is impossible to divide a suitable height interval to obtain multiple contour lines due to smooth changes in data between grids or too few grids, the spatial granularity of the data can be refined, and more spatial positions can be selected for interpolation between the concentration data of adjacent grids, and then contour lines can be drawn based on the pollutant concentration distribution after interpolation. This can avoid the inability to identify clustered areas due to grid scale, etc., and improve the accuracy of identification.

[0068] Through the above-mentioned special difference situations, the leakage source that has stopped leaking can be identified in time, and the misidentified leakage source can be corrected. Other difference situations can be regarded as monitoring errors or simulation errors, or provided to analysts for further judgment, thereby improving the simulation accuracy and response speed in complex leakage scenarios.

[0069] Of course, the above-mentioned specific implementation methods can exist independently or in combination with each other, and all fall within the scope of protection of this embodiment. For the sake of convenience in distinction and description, the monitoring grid in which the difference is positive and the instantaneous increment of the difference is greater than the set positive threshold value can be referred to as the first monitoring grid, and the monitoring grid in which the difference is negative and the instantaneous decrement of the difference is less than the set negative threshold value in multiple consecutive time steps can be referred to as the second monitoring grid. The "difference" in all embodiments refers to the difference between the monitored concentration of the same grid and the simulated concentration. In the implementation method of identifying both the first monitoring grid and the second monitoring grid, dynamic identification and mutual correction of the two types of grids are more conducive to maintaining accurate simulation and rapid response.

[0070] In summary, this embodiment provides a gas leakage risk simulation method based on laser telemetry, which enhances the rapid response capability of leakage simulation through the scanning results of laser telemetry equipment and SCICHEM simulation technology. Among them, the laser gas telemetry equipment can break through the limitations of traditional reliance on fixed micro-stations, and has flexible deployment and a wide monitoring range. It can quickly capture the occurrence time and initial distribution characteristics of leaked gas, and provide instant and accurate simulation starting conditions for the SCICHEM model; and the SCICHEM model can achieve instantaneous simulation at the minute level or finer time granularity, accurately reflecting the diffusion process of leaked gas, and providing rapid and timely technical support for responding to sudden environmental events. In addition, the method of this embodiment can also achieve effective leakage response and preliminary impact assessment in areas where telemetry conditions are limited or inaccessible, thereby providing data support for the prediction of leakage accident consequences and protection optimization in a larger range.

[0071] Figure 9 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention is shown in FIG. Figure 9 As shown, the device includes a processor 60, a memory 61, an input device 62 and an output device 63; the number of processors 60 in the device can be one or more. Figure 9 In the embodiment, a processor 60 is used as an example; the processor 60, the memory 61, the input device 62 and the output device 63 in the device can be connected by a bus or other means. Figure 9 The bus connection is taken as an example.

[0072] Memory 61, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the laser telemetry-based gas leakage risk simulation method in the embodiments of the present invention. Processor 60 executes the software programs, instructions, and modules stored in memory 61 to perform various functional applications and data processing of the device, thereby implementing the aforementioned laser telemetry-based gas leakage risk simulation method.

[0073] The memory 61 may primarily include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function; the data storage area may store data generated based on the use of the terminal. Furthermore, the memory 61 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state memory device. In some instances, the memory 61 may further include memory remotely located relative to the processor 60, and these remote memories may be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0074] The input device 62 may be used to receive input digital or character information and generate key signal input related to user settings and function control of the device. The output device 63 may include a display device such as a display screen.

[0075] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the gas leakage risk simulation method based on laser telemetry of any embodiment.

[0076] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or components, or any combination thereof. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by an instruction execution system, device or device or used in combination with it.

[0077] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0078] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0079] Computer program code for performing the operations of the present invention can be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as C or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A gas leakage risk simulation method based on laser telemetry, characterized in that: include: Divide the area to be simulated into multiple two-dimensional geographic grids; Using laser telemetry equipment, real-time monitoring of gas pollutant concentrations in multiple monitoring grids in the area to be simulated is performed, wherein the laser telemetry equipment is deployed at a high point at the boundary of the leakage risk area in the area to be simulated, and the monitoring angle of the laser telemetry equipment covers the leakage risk device and its surrounding grids in the leakage risk area; Monitoring grids with instantaneous increases in pollutant concentration greater than a set positive threshold are identified as suspected leakage grids and added as leakage sources in the atmospheric diffusion simulation model. The pollutant leakage process of the leakage source is simulated at the minute level or higher time accuracy; The following operations are performed during the simulation: S1, subtract the simulated concentration from the pollutant monitoring concentration of each monitoring grid in real time; S2. Identify the first monitoring grid with a positive difference and an instantaneous increment of the difference greater than a set positive threshold as a new suspected leakage grid and add it in real time as a new leakage source in the atmospheric diffusion simulation model, and perform subsequent simulations based on the new and old leakage sources; S3, for a second monitoring grid whose difference is negative and whose instantaneous decrement is less than a set negative threshold value in multiple consecutive time steps, extracting a continuous area with a negative difference around the second monitoring grid in the multiple time steps; If the continuous areas at the same time step are clumped and the clumped areas gradually expand over time, the leakage sources covered by the clumped areas at each time step are deleted, and subsequent simulations are performed based on the remaining leakage sources.

2. The method according to claim 1, characterized in that If the continuous areas at the same time step are clustered, and the clustered areas gradually expand over time, the leakage sources covered by the clustered areas at each time step are deleted, including: In the continuous area at the same time step, the contour lines are drawn with the pollutant concentration as the high value data; If multiple closed contour lines are obtained, it is determined that the continuous region is in a cluster shape.

3. The method according to claim 2, characterized in that The method of drawing contour lines with pollutant concentration as high value data in continuous areas at the same time step includes: In the continuous area of ​​the same time step, the pollutant concentration of each grid is interpolated in two dimensions; In the interpolated pollutant concentration distribution, contour lines are drawn with pollutant concentration as high-value data.

4. The method according to claim 1, wherein The subsequent simulation based on new and old leakage sources includes: Determining the type and height of the new leakage source based on the leakage risk equipment at the new leakage source, wherein the types include point source and area source; Based on the pollutant concentration distribution obtained by simulating the old leakage source, the leakage process simulation of the new leakage source is immediately started according to the type and height of the new leakage source, while the simulation of the old leakage source is continued.

5. The method according to claim 1, wherein The subsequent simulation based on the remaining leakage source includes: Based on the pollutant concentration distribution of the last time step before the multiple time steps, a leakage process simulation equal to the total duration of the multiple time steps is performed according to the remaining leakage sources to obtain a simulation result of the current time step.

6. The method according to claim 1, characterized in that The atmospheric diffusion simulation model is the SCICHEM model.

7. The method according to claim 1, characterized in that The laser telemetry equipment includes laser or infrared spectrum non-contact remote sensing equipment.

8. The method according to claim 1, characterized in that The method of using laser telemetry equipment to monitor the concentration of gas pollutants in a plurality of monitoring grids in the area to be simulated in real time includes: Laser telemetry equipment and fixed microstations are used to monitor the gas pollutant concentrations of multiple monitoring grids in the area to be simulated in real time.

9. An electronic device, characterized in that: include: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the gas leakage risk simulation method based on laser telemetry as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the program is executed by a processor, the gas leakage risk simulation method based on laser telemetry according to any one of claims 1 to 8 is implemented.

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