Gas leak risk simulation method, apparatus, and media based on laser telemetry

Abstract

Embodiments of the present application disclose a gas leakage risk simulation method and device based on laser remote sensing and a medium. The method comprises: dividing a region to be simulated into a plurality of two-dimensional geographic grids; using a laser remote sensing device to monitor the concentration of gas pollutants in a plurality of monitoring grids in the region to be simulated in real time, wherein the laser remote sensing device is arranged at a high position of a leakage risk region boundary in the region to be simulated, and a monitoring angle covers a leakage risk device and surrounding grids in the leakage risk region; monitoring grids with an instantaneous increment of pollutant concentration greater than a set positive threshold are identified as suspected leakage grids and added as leakage sources in an atmospheric diffusion simulation model, and a minute-level or higher time-precision simulation is performed on the pollutant leakage process of the leakage sources. The embodiments can capture leakage events in a larger range in real time and dynamically simulate diffusion paths.

Description

Technical Field

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

[0002] With the rapid development of the chemical industry, the safety risks in chemical industrial parks and hazardous chemical storage and transportation areas are becoming increasingly prominent. Frequent chemical gas leaks pose a serious threat to the surrounding environment and human health. Chemical industrial parks have a dense distribution of potential leak sources. After a leak occurs, the diffusion behavior of pollutants is influenced by various factors such as meteorological conditions and terrain features, exhibiting strong temporal and spatial uncertainty. In particular, the sudden release of pollutants from multiple leak sources at different times can easily lead to rapid diffusion of pollutants within a short period. Due to the suddenness, randomness, and complex temporal and spatial distribution of leaks, failure to accurately determine the location and impact range of the leak source in the first instance will seriously threaten the health of surrounding populations and the ecological environment, and may trigger secondary disasters. Therefore, the key tasks after an accident are to quickly identify the leak source, dynamically simulate the diffusion path, and rapidly assess the scope of pollution impact to provide a scientific basis for emergency decision-making, personnel evacuation, and subsequent handling.

[0003] Currently, the pollutant gas leak detection and alarm systems used in chemical industrial parks are mainly fixed gas detectors built according to the "Design Standard for Detection and Alarm of Combustible and Toxic Gases in Petrochemical Industry" (GB / T50493-2019), which are insufficient to meet the requirements for rapid location and response. Patent application CN201310029240.X discloses a method based on gridded toxic gas diffusion simulation, and patent application CN201310082010.X discloses a real-time location analysis method and system for gas pipeline leak sources. However, neither of these methods can capture leak events over a large area in real time, identify leak sources in a timely manner, or dynamically simulate diffusion paths. Summary of the Invention

[0004] This invention provides a method, device, and medium for simulating gas leakage risk based on laser telemetry, to solve at least one of the above-mentioned problems.

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

[0006] The area to be simulated is divided into multiple two-dimensional geographic grids;

[0007] Using laser telemetry equipment, the concentration of gaseous pollutants in multiple monitoring grids in the simulated area is monitored in real time. The laser telemetry equipment is deployed at a high position at the boundary of the leakage risk area in the simulated area, and the monitoring angle of the laser telemetry equipment covers the leakage risk device and its surrounding grid in the leakage risk area.

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

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

[0010] S1. Subtract the simulated concentration from the pollutant monitoring concentration in each monitoring grid in real time;

[0011] S2. The first 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 leak grid and added in real time as a new leak source in the atmospheric diffusion simulation model. Subsequent simulations are then performed based on the new and old leak sources.

[0012] S3. For the second monitoring grid with a negative difference and an instantaneous decrease in the difference less than a set negative threshold in multiple consecutive time steps, extract the continuous regions with negative differences around the monitoring grid in the multiple time steps; if the continuous regions in the same time step are clustered and the clustered regions gradually expand over time, delete the leakage sources covered by the clustered regions in each time step, and perform subsequent simulations based on the remaining leakage sources.

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

[0014] One or more processors;

[0015] Memory, used to store 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 as described in any embodiment.

[0017] Thirdly, embodiments of the present invention also provide 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 as described in any embodiment.

[0018] In summary, this embodiment provides a gas leak risk simulation method based on laser telemetry. By combining the scanning results of the laser telemetry device with SCICHEM simulation technology, the rapid response capability of leak simulation is enhanced. The laser gas telemetry device overcomes the limitations of traditional methods relying solely on fixed microstations, offering flexible deployment and a wide monitoring range. It can quickly capture the occurrence time and initial distribution characteristics of leaked gas, providing the SCICHEM model with immediate and accurate simulation start conditions. The SCICHEM model, in turn, can achieve instantaneous simulations at the minute level or even finer time granularity, accurately reflecting the diffusion process of leaked gas and providing rapid and timely technical support for responding to sudden environmental events. Furthermore, the method of this embodiment can also achieve effective leak response and preliminary impact assessment in areas with limited or inaccessible telemetry conditions, thereby providing data support for predicting the consequences of leak accidents and optimizing protection measures over a wider range. Attached Figure Description

[0019] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in 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 the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

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

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

[0022] Figure 3 This is a simulation diagram of the gas diffusion range after 2 minutes of leakage in the application case provided in the embodiments 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 in the embodiments of the present invention;

[0024] Figure 5 This is a simulation diagram of the gas diffusion range after 5 minutes of leakage in the application case provided in the embodiments 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 in the embodiments 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 in the embodiments 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 in the embodiments of the present invention;

[0028] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0030] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the 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 this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

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

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

[0034] This embodiment first determines the geographical area to be monitored and simulated, and then divides the area into multiple planar grids according to the grid resolution. For example, the area to be simulated can be a region including an industrial park.

[0035] In addition, the time range to be monitored and simulated can be determined, including the start time and time step. The time step can be determined comprehensively based on the time granularity that can be achieved by subsequent laser telemetry equipment and atmospheric diffusion models.

[0036] S120. Using a laser telemetry device, the concentration of gaseous pollutants in multiple grids in the area to be simulated is monitored in real time. The laser telemetry device is deployed at a high position at the boundary of the leakage risk area in the area to be simulated, and the monitoring angle of the laser telemetry device covers the leakage risk device and its surrounding area within the leakage risk area.

[0037] Once the simulation area is determined, this embodiment further defines a leakage risk area within that area as the deployment location for the laser telemetry equipment. This area can be a larger region than the leakage risk device itself, covering the leakage risk device in the simulation area. Deploying the laser telemetry equipment at a higher position on the boundary of the leakage risk area facilitates scanning and monitoring of gaseous pollutant concentrations of the leakage risk device and its surrounding grid from a higher and farther distance. Gaseous pollutants include toxic gases, combustible gases, or other gaseous chemicals that need to be monitored.

[0038] For example, taking the simulated area including the industrial park as an example, the leakage risk area can be the industrial park itself, and the leakage risk devices are equipment and buildings within the industrial park that pose a leakage risk, such as pipes and chimneys. The laser telemetry equipment will be deployed at a high position on the boundary of the industrial park (e.g., 20 meters or more), and by adjusting the angle of the laser telemetry equipment, it can monitor in real time the grid where the leakage risk devices such as pipes and chimneys are located and the surrounding grid. For ease of distinction and description, this embodiment refers to the grid monitored in real time by the laser telemetry equipment as the monitoring grid, which is usually only a part of the leakage risk area. In addition, the simulated area can also be the same as the leakage risk area, and this embodiment does not impose specific limitations.

[0039] Furthermore, the laser telemetry equipment here includes non-contact remote sensing devices based on laser / infrared spectroscopy. Compared to traditional detection methods, laser telemetry equipment has significant advantages such as mobility, rapid response, and wide coverage, making it 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 broad monitoring range, provides rapid identification and alarm functions, and presents results intuitively, achieving true "what you see is what you get." Optionally, in addition to scanning and monitoring data from multiple grids using laser telemetry equipment, monitoring data provided by fixed micro-stations can also be used as a combined monitoring data source.

[0040] S130. Identify monitoring grids where the instantaneous increase in pollutant concentration is greater than a set positive threshold as suspected leak grids and add them as leak sources in the atmospheric diffusion simulation model. Simulate the pollutant leakage process of the leak source at the minute level or with higher time accuracy.

[0041] This embodiment identifies suspected leaking grids based on the instantaneous increase in pollutant concentration within the monitored grid. The instantaneous increase is calculated by subtracting the pollutant concentration from the previous time step from the current time step. For a grid with a concentration of 0 in the previous time step, if the concentration in the monitored grid suddenly increases to above a set positive threshold in the current time step, a leak can be preliminarily considered to have occurred in that grid. Using this grid as a leak source for atmospheric diffusion simulation allows for timely understanding of the approximate diffusion process of pollutants throughout the simulated area.

[0042] In one specific implementation, the SCICHEM (SCIPUFF with chemistry, a chemical coupling extension based on a second-order closed integral plume model framework) model can be used to simulate the leakage and diffusion of gaseous chemicals. This aims to accurately simulate the actual release process from the source, thereby capturing the emission status of the leakage source at different time points. First, meteorological data simulation can be performed based on 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-based micro-monitoring stations / conventional weather stations, can be used to construct a real-time three-dimensional meteorological field covering the simulation area. Key meteorological elements required by the SCICHEM model (such as wind speed, wind direction, temperature, turbulence, etc.) can then be extracted and converted into meteorological data files conforming to the SCICHEM model input format.

[0043] Specifically, the SCICHEM model is a Lagrange diffusion model, specifically a Lagrange photochemical diffusion mode based on a second-order closed integrated plume diffusion model. SCIPUFF (Second-order Closure Integrated PUFF) is the core module of SCICHEM, incorporating a second-order closure method for the atmospheric boundary layer. Based on Gaussian theory, it simulates complex, time-varying three-dimensional plumes from one or more sources, and is widely used in pollution source tracing, pollution diffusion simulation, and risk leakage simulation. Furthermore, SCIPUFF is also the core module of the hazardous substance leakage simulation software HPAC (HazardPrediction And Assessment Capability). Therefore, the SCICHEM model exhibits good accuracy and effectiveness in leakage simulation, enabling it to effectively simulate pollutant leakage and diffusion processes.

[0044] Optionally, in this embodiment, once a suspected leak grid is detected within each time step, it is added to the emission grid in the SCICHEM model. The current time is taken as the emission start time of this emission grid, and parameters such as release rate, source type, and height are set. Simultaneously, current meteorological driving field data and topographic data are input into the SCICHEM model, allowing SCICHEM to simulate the entire process of pollutant diffusion from the leak source point to the outside at each subsequent time step. The release rate is measured in g / s (grams per second), which can be calculated based on the rate of change of pollutant concentration at the suspected leak grid. Leak source types include point sources and area sources. The type and height of the leak source can be determined based on the equipment distribution within the leak risk area. Specifically, based on the location of equipment within the park, the leak-risk equipment at the leak source can be identified; based on the type of equipment, the type and height of the new leak source can be determined. For example, if a chemical transport pipeline exists within the leak source grid, then the pipeline height is the leak source height. Pipeline leaks are typically point leaks, thus the leak source is a point source. At each time step, the simulation of the new leakage source is started immediately based on the pollutant concentration distribution obtained from the simulation of the old leakage source, according to the type and height of the new leakage source, while the simulation of the old leakage source continues.

[0045] After the simulation is complete, the results of the SCICHEM simulation can be visualized to provide a more intuitive understanding of the emission impact of the leak source. For each leakage process, the concentration distribution map output by SCICHEM can be visualized. Combined with geographic information system tools, dynamic concentration distribution maps can be generated to vividly illustrate the leakage process of the leak source. Time series plots can show the impact of the leak source on the surrounding area at different time points, emphasizing the concentration changes at different times and locations. The spatiotemporal visualization of the simulation results can more realistically reflect the movement and emission of the leak source over a certain period of time, providing intuitive evidence for leak 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 overcomes the spatiotemporal limitations of traditional fixed micro-station monitoring, allowing for flexible deployment around the plant area. It possesses rapid response and multi-point grid scanning capabilities, capturing the specific time and location of leaks in real time, providing the SCICHEM model with high-precision leak source initiation conditions. Through the coupling of the telemetry equipment and the model, not only is the timeliness and accuracy of leak simulation improved, but a more practical decision support tool is also provided for sudden environmental events. More specifically, this embodiment has the following advantages:

[0047] (1) The SCICHEM model supports input from multiple leakage sources, enabling accurate simulation of complex leakage scenarios. In real chemical environments, leakage is often not a sudden occurrence from a single source, but may involve multiple grid sources leaking at different time points. SCICHEM allows for flexible setting of 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 high time resolution simulation results output, which can simulate the diffusion behavior of pollutants at minute and second time scales. It can more sensitively capture the temporal characteristics of multiple leakage sources and provide a more timely and realistic leakage diffusion process for sudden environmental events.

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

[0050] (4) By combining telemetry equipment with the SCICHEM model, rapid capture and simulation of the leak time can be achieved. This embodiment introduces a laser gas telemetry device, which breaks through the monitoring limitations of traditional fixed micro-stations. It can be flexibly deployed and scan multiple grid areas in real time to quickly identify the time and location of the leak. The telemetry results can be directly used to drive the SCICHEM model to set the release initiation conditions of the leak source, realizing efficient coupling between monitoring and simulation, and greatly improving the response speed and accuracy of sudden leak event simulation.

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

[0052] During monitoring, the telemetry equipment detected an abnormal emission in grid number 188 within the first minute. The initial assessment indicated a ruptured pipeline, with the leak source identified as the pipeline and a leakage height of 1 meter. Within the third minute, the telemetry equipment detected a sudden increase in concentration in another grid (grid number 588). Further investigation determined that volatile gases were escaping from the top of a storage tank within the industrial park, with a release height of 10 meters.

[0053] Based on the above identification results and meteorological conditions, corresponding emission grids, emission start times, release rates, source types, and heights can be set for the leakage process. Taking into account the influence of meteorological driving fields and topography, SCICHEM is used to simulate the entire process of pollutants spreading outward from the leakage source point in each release stage. The simulated concentration results are then visualized to complete the simulation of the leakage source.

[0054] Specifically, this embodiment uses the SCICEHM model version 3.3, employing the Universal Transverse Mercator Grid System (UTC) coordinates (unit: km). Topographic elevation data for the region is sourced from the U.S. Geological Survey (a research dataset), with a precision of 90m. Meteorological data was input from surface meteorological stations in Jiujiang City, Jiangxi Province, and upper-air simulated meteorological data. Surface meteorological data is provided by the China Meteorological Administration, including daily and hourly data from the Jiujiang City meteorological station in 2023 (station number 54594, 39.72°N, 116.35°E), and includes wind direction, wind speed, and temperature. The data was converted into a SCICHEM model-recognizable input format using AERMET (AMS / EPA Regulatory Model Meteorological Preprocessor).

[0055] The 2023 Jiujiang City upper-level simulated meteorological data was obtained by converting the WRF model simulation results through the MMIF (Mesoscale Model Interface Program) tool. It includes air pressure, ground height, dry bulb temperature, wind direction and wind speed at different isobaric surfaces at 8:00 am and 8:00 pm every day. The vertical direction is divided into 21 layers, with ground height ranging from 0 to 1919 meters.

[0056] Based on the concentration distribution map output by SCICHEM, and combined with geographic information system tools, the leakage process was visualized. Time series plots were used to show the impact of the leakage source on the surrounding area at different time points, emphasizing concentration changes at different times and locations. Figures 3-8 The graphs show the concentration changes of the leak source at different time points. The horizontal and vertical axes in the graphs are the UTM coordinates of each spatial location. The color values ​​represent the concentration of pollutants (unit: grams per cubic meter). 1E-05 represents 10 to the power of -5. Other color values ​​are similar.

[0057] Furthermore, the leakage source identification method in the above embodiments is applicable to the case where the concentration of the monitoring grid was 0 in the previous time step. In this case, the monitoring grid can be preliminarily identified as a leaking grid as long as a sudden increase in concentration occurs in the current time step. However, in practical applications, another situation may exist: due to the diffusion of existing leakage sources, some grids already have a certain concentration of pollutants before 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 diffusion of existing leakage sources or by a leakage that has occurred itself. In a specific embodiment, this situation can be addressed 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 monitoring concentration of each monitoring grid in real time. For the grids described above, the simulated concentration represents the pollutant diffusion from the old leak source, while the monitoring concentration from the laser telemetry equipment represents the actual pollutant detected.

[0060] S2. Monitoring grids with positive differences and instantaneous increments of differences greater than a set positive threshold are identified as new suspected leakage grids and added in real time as new leakage sources in the atmospheric diffusion simulation model. Subsequent simulations are then performed based on the new and old leakage sources.

[0061] If a leak occurs in a monitoring grid, the instantaneous concentration change caused by the leak is obtained by subtracting the simulated concentration from the monitored concentration. Ideally, this difference should be greater than 0 to indicate a leak. However, considering that there are certain errors in both equipment monitoring and model simulation, and that even a brief period of drifting gas can cause a small increase in concentration, this embodiment uses a set 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 a set positive threshold. It is also applicable to grids with an initial concentration of 0 and can identify new leakage sources more accurately.

[0063] Furthermore, in another specific embodiment, after performing operation S1, another situation may occur: the difference between the measured concentration and the simulated concentration of some grids is negative. This may be due to measurement error or simulation error, or it may be due to the original leakage source being controlled in time and the leakage stopping, or it may be due to the original leakage source being incorrectly identified. For such grids, this embodiment provides the following methods to correct the deviation in a timely manner:

[0064] If the difference of a certain monitoring grid is negative in the current time step T and several consecutive time steps prior to it, then for each pair of adjacent time steps, the difference Δc from the next time step can be used. t Subtract the difference Δc from the previous time step t―1 This yields the instantaneous change in the difference. If this instantaneous change is decreasing (i.e., Δc) t ―Δc t―1 <0), and the decrease Δc t ―Δc t―1 If the simulated concentration at a given time step is less than the set negative threshold, it indicates that the simulated concentration at that grid point is consistently higher than the monitored concentration by a certain level, which is very likely due to the original leak source ceasing to leak or being incorrectly identified.

[0065] To further verify whether this is the cause, the following operation can be performed for each of multiple consecutive time steps: extract the grids with negative differences around a certain monitoring grid and determine whether these grids form a continuous, clumped region. If such a continuous, clumped region exists in all time steps, then it is further determined whether the clumped region gradually increases in size over time. If the clumped regions in these time steps gradually expand over time, it can be basically determined that these clumped regions 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, leakage sources covered by the clumped region in each time step can be found in the simulation model, deleted, and subsequent simulations can be 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 earlier), the pollutant concentration distribution of the last time step preceding the multiple consecutive time steps can be used as the initial concentration distribution. A leak process simulation with a duration equal to the total duration of the multiple consecutive time steps is then 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, normally each simulation calculates the concentration result based on the diffusion time of Δt. However, in this case of deleting the leak source, assuming the total duration of the multiple consecutive time steps is N×Δt (N being the number of time steps), the pollutant concentration distribution of the last time step preceding the multiple consecutive time steps can be used as the basic concentration distribution. The concentration distribution result for the current time step is calculated based on the diffusion time of N×Δt to fill the gaps in the intermediate time steps. It is worth noting that although simulation errors have appeared in multiple time steps, since these errors have not spread widely and past errors are no longer significant for decision analysis in the current time step, it is only necessary to correct the errors in the current time step without resimulating the time steps with past errors.

[0067] Furthermore, the aforementioned clustered regions can be identified by analysts based on experience, or automatically determined by electronic equipment using contour lines. Optionally, for continuous regions formed by grids with negative differences in a single time step, contour lines can be drawn within these regions using pollutant concentration as the highest value data. If multiple closed contour lines are ultimately obtained, the continuous region can be automatically determined to be clustered. If, during the contour line drawing process, it is impossible to divide suitable height intervals to obtain multiple contour lines due to smooth data changes between grids or an insufficient number of grids, the spatial granularity of the data can be refined. More spatial locations can be selected for interpolation between the concentration data of adjacent grids, and then contour lines can be drawn based on the interpolated pollutant concentration distribution. This avoids the inability to identify clustered regions due to grid scale, thus improving the accuracy of identification.

[0068] By using the aforementioned special differential values, it is possible to promptly identify and stop leak sources, as well as correct incorrectly identified leak sources. Other differential values ​​can be considered as monitoring or simulation errors, or provided to analysts for further judgment, thereby improving the simulation accuracy and response speed in complex leak scenarios.

[0069] Of course, the above-mentioned specific implementation methods can exist independently or in combination, and all fall within the protection scope of this embodiment. For ease of distinction and description, the monitoring grid with a positive difference value and an instantaneous increment of the difference value greater than a set positive threshold can be referred to as the first monitoring grid, and the monitoring grid with a negative difference value and an instantaneous decrease of the difference value less than a set negative threshold value in multiple consecutive time steps can be referred to as the second monitoring grid. In all embodiments, "difference value" refers to the difference between the monitored concentration and the simulated concentration of the same grid. In the implementation method that identifies both the first and second monitoring grids, 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 leak risk simulation method based on laser telemetry. By combining the scanning results of the laser telemetry device with SCICHEM simulation technology, the rapid response capability of leak simulation is enhanced. The laser gas telemetry device overcomes the limitations of traditional methods relying solely on fixed microstations, offering flexible deployment, a wide monitoring range, and rapid capture of the occurrence time and initial distribution characteristics of leaked gas, providing the SCICHEM model with immediate and accurate simulation start conditions. The SCICHEM model, in turn, can achieve instantaneous simulation at the minute level or even finer time granularity, accurately reflecting the diffusion process of leaked gas and providing rapid and timely technical support for responding to sudden environmental events. Furthermore, the method of this embodiment can also achieve effective leak response and preliminary impact assessment in areas with limited or inaccessible telemetry conditions, thereby providing data support for predicting the consequences of leak accidents and optimizing protection measures over a wider range.

[0071] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention, such as... 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 Taking a processor 60 as an example; the processor 60, memory 61, input device 62, and output device 63 in the device can be connected via a bus or other means. Figure 9 Taking the example of a connection between China and Israel via a bus.

[0072] The 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 leak risk simulation method in this embodiment of the invention. The processor 60 executes various functional applications and data processing of the device by running the software programs, instructions, and modules stored in the memory 61, thereby realizing the aforementioned laser telemetry-based gas leak 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 the operating system and at least one application program required for a given function; the data storage area may store data created based on terminal usage. 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, or other non-volatile solid-state storage device. In some instances, the memory 61 may further include memory remotely located relative to the processor 60, which can be connected to the 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.

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

[0075] This invention also provides a computer-readable storage medium storing a computer program that, 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 this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0077] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying 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. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0078] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0079] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—as well as 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 standalone 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 remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via 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, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate 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: The area to be simulated is divided into multiple two-dimensional geographic grids; Using laser telemetry equipment, the concentration of gaseous pollutants in multiple monitoring grids in the simulated area is monitored in real time. The laser telemetry equipment is deployed at a high position at the boundary of the leakage risk area in the simulated area, and the monitoring angle of the laser telemetry equipment covers the leakage risk device and its surrounding grid in the leakage risk area. Monitoring grids with instantaneous increases in pollutant concentration greater than a set positive threshold are identified as suspected leak grids and added as leak sources in the atmospheric diffusion simulation model. The pollutant leakage process of the leak source is simulated with minute-level or higher time accuracy. The following operations are performed during the simulation: S1. Subtract the simulated concentration from the pollutant monitoring concentration in each monitoring grid in real time; S2. The first 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 leak grid and added in real time as a new leak source in the atmospheric diffusion simulation model. Subsequent simulations are then performed based on the new and old leak sources. S3. For the second monitoring grid with a negative difference and an instantaneous decrease in the difference that is less than a set negative threshold in multiple consecutive time steps, extract the continuous region with a negative difference around the second monitoring grid in the multiple time steps. If the continuous regions at the same time step are clustered and the clustered regions gradually expand over time, the leakage sources covered by the clustered regions 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 a continuous region at the same time step is clumped together, and the clumped region gradually expands over time, the leakage source covered by the clumped region at each time step will be deleted, including: Contour lines are drawn in continuous regions at the same time step, using pollutant concentration as the high-value data. If multiple closed contour lines are obtained, it is determined that the continuous region is in the form of a cluster.

3. The method according to claim 2, characterized in that, The process of drawing contour lines in a continuous region at the same time step, using pollutant concentration as the high-value data, includes: In a continuous region at 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 using the pollutant concentration as the high value data.

4. The method according to claim 1, characterized in that, The subsequent simulation based on the old and new leakage sources includes: Based on the leakage risk equipment at the new leakage source, determine the type and height of the new leakage source, wherein the type includes point sources and area sources; Based on the pollutant concentration distribution obtained from the simulation of the old leak source, the leakage process simulation of the new leak source is started in real time according to the type and height of the new leak source, while the simulation of the old leak source continues.

5. The method according to claim 1, characterized in that, 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 with a total duration equal to the multiple time steps is performed according to the remaining leakage source to obtain the 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 non-contact remote sensing equipment based on laser or infrared spectroscopy.

8. The method according to claim 1, characterized in that, The method of using laser telemetry equipment to monitor the concentration of gaseous pollutants in multiple monitoring grids in the area to be simulated in real time includes: Using laser telemetry equipment and fixed micro-stations, the concentration of gaseous pollutants in multiple monitoring grids in the area to be simulated is monitored in real time.

9. An electronic device, characterized in that, include: One or more processors; Memory, used to store 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, It stores a computer program that, when executed by a processor, implements the gas leakage risk simulation method based on laser telemetry as described in any one of claims 1-8.

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